CITA Comple Modelling by CITA

CITA complex modelling

Mette Ramsgaard Thomsen / Martin Tamke / Phil Ayres / Paul Nicholas

The four year Complex Modelling research project investigates the infrastructures of our design models. By questioning the tools for integrating information across the expanded digital design chain, the project asks how to support feedback between different scales of design engagement moving from material design, across design, simulation and analysis to specification and fabrication. The project focuses on the integration of material performance as a particular challenge opening up new horizons for a sustainable building culture. The ability to design for and with material performance is a core resource for design innovation closely tied to material optimisation. The project introduces three scales of design engagement by which to examine material performance: the structure, the element and the material. Positioning feedback as a central concern cascading through all scales of engagement, the project asks how dynamic modes of organisation including self-organisation, multi-scalar modelling and self-adaptive modelling can introduce new logics into the design of architectural information models.

Riverside Architectural Press

CITA centre for information technology and architecture CITA is an innovative research environment exploring the intersections between architecture and digital technologies. By identifying core research questions into how space and technology can be probed, CITA investigates how the current forming of a digital culture impacts on architectural thinking and practice. CITA examines how architecture is influenced by new digital design- and production tools as well as the digital practices that are informing our societies culturally, socially and technologically. CITA consolidates new collaborations with interdisciplinary partners from the fields of computer science, robotics, engineering as well as the practice based fields such as furniture design, fashion and textiles, industrial design, film, dance and interactive arts.

CITA complex modelling

Mette Ramsgaard Thomsen Martin Tamke Phil Ayres Paul Nicholas

CITA complex modelling

CITA Complex Modelling Authors: Mette Ramsgaard Thomsen, Martin Tamke, Phil Ayres, Paul Nicholas Design Concept: Johanne Lian Olsen Layout and Design Refinements: Yuliya Ĺ inke Baranovskaya Cover Image: Hybrid Tower Project (2016) Proof Reading: Sandra Greig Published by Riverside Architectural Press. www.riversidearchitecturalpress.com First edition. ÂŠ 2019 Riverside Architectural Press All rights reserved. No part of this publication may be reproduced, or transmitted, in any form or by any means, electronic, mechanical, including photocopying, recording, or any other information storage and retrieval system, without prior permission. Every reasonable attempt has been made to identify owners of copyright. Errors or omissions will be corrected in subsequent editions. Library and Archives Canada Cataloguing in Publication CITA complex modelling / Mette Ramsgaard Thomsen, Phil Ayres, Martin Tamke, Paul Nicholas. ISBN 978-1-926724-72-0 (paperback) 1. Architecture--Computer-aided design. 2. Architectural design-Data processing. 3. Building materials. 4. Centre for Information Technology and Architecture. I. Ayres, Phil, author, architect II. Tamke, Martin, 1974-, author, architect III. Ramsgaard Thomsen, Mette, 1969-, author, architect IV. Nicholas, Paul, 1978-, author, architect V. Centre for Information Technology and Architecture, architect NA2728.C57 2015

720.2840285

C2015-904852-4

CITA complex modelling is set in nevis and Adobe Caslon Pro Printing by Regal Printing Limited

This publication was made possible through the support of:

Det Kongelige Danske Kunstakademis Skoler for Arkitektur, Design og Konservering Arkitektskolen

CITA complex modelling Mette Ramsgaard Thomsen Martin Tamke Phil Ayres Paul Nicholas

720.2840285

C2015-904852-4

CITA complex modelling is set in nevis and Adobe Caslon Pro Printing by Regal Printing Limited

This publication was made possible through the support of:

Det Kongelige Danske Kunstakademis Skoler for Arkitektur, Design og Konservering Arkitektskolen

CITA complex modelling Mette Ramsgaard Thomsen Martin Tamke Phil Ayres Paul Nicholas

ADAPTIVE PARAMETRISATION A central focus in Complex Modelling is the exploration of methods for enabling feedback in the design process to develop ways by which models can be interfaced to support increased design intelligence produced through the dynamic activation of algorithmically driven computational modelling systems. Contemporary architectural design takes place within a network of models. Whether in the applied realm of practice or the speculative realm of research, current design process is established across a network of relations in which smaller dedicated models distribute defined tasks. The ability to interface these dedicated models and pass information between traditionally separate design environments has profound impact on design practice. It allows direct sharing of knowledge, method and technique between disciplines and enables stronger feedback between processes. While design has traditionally been understood as a process of refinement, a process in which we know increasingly more about the design object as we descend in scale from site, environment and programme to specification and material, these new interfaces enable us to pass information

up the design chain. This allows the design agency of small-scale fabrication and material to affect the high-scale agendas of structure and form. What emerges is a high-order design space in which self-regulating mechanisms of feedback become central components. In the process of feedback, models actively impact upon one another. This necessitates an ability to fundamentally change the underlying data structures of the design space. Through the application of methods for adaptive parameterisation, we ask how design models can flexibly adapt to variably structured incoming or generated information, tuning themselves through the creation of new parameters and the shedding of old. Current methods for multi-objective search and optimisation give architects the ability to navigate parameterised design spaces. While these methods entail fixed design spaces, adaptive parameterisation provides the means to move beyond existing concepts of ‘optioneering’ or ‘versioning’ by allowing feedback to affect change on the underlying topology, or body plan, of the model. The concept of body plan has long informed computational thinking in ar-

chitectural design (1). The distinction between weak and strong body plans suggests a differentiation between body plans that are merely deformed, i.e. where the topology of the parametric model remains intact despite the input of new values, or fundamentally re-formed, creating a new topological structure. Our first foray into adaptive parameterisation explores means of re-forming model body plans. In The Rise, growth algorithms are employed as prototypical methods for emergent parameterisation. Where The Rise cannot reverse prior growth steps, it proposes how feedback from the environment, as well as the structure itself, can inform design evolution. In Social Weavers, emergent parameterisation is further developed. Here, designers effectively change the model body plan by interactively adding or discarding elements throughout the design process.

ADAPTIVE PARAMETRISATION

DAVID STASIUK

ACTIVATING INFORMATION THRESHOLDS IN MODEL NETWORKS

Architectural design projects are realised through multiple representational engines that comprise a network of discrete but inter-related partial models, whose negotiability and efficacy are central to the successful execution and integration of distributed and variably defined tasks. Traditionally, modelling methodologies have managed these concerns by aiming for stability in the information transfers or parameter spaces that exist between adjacent partial models. A central focus in the Complex Modelling project has been to develop methodologies that enable partial models to more effectively work together as a holistic system, enabling deeper feedback mechanisms within design and production processes. In this pursuit it then experimentally examines means by which partial models may better interface with one another to elicit the increased design intelligence that may be produced through

the dynamic activation of algorithmically-driven, computational modelling systems. Here Adaptive Parameterisation is presented as a modelling methodology that aims to address these concerns by focusing on the information thresholds that bind discrete model elements with one another. It describes an approach to model formulation where underlying data structures behave as mutable substrates: while they are persistent in their basic typology enabling consistent approaches to parameterisation across multiple interconnected partial models - they are also changeable in both number and the types of relationships they can describe for designed elements. They are therefore set up to support open-ended design systems that can react to the variable contexts of both internal (material) and external (functional) constraints in goal-seeking behaviours. These mutable substrates are then dynamically

activated through the implementation of transformational algorithms within the partial models they parameterise. Contemporary modelling methods for architectural practices and the building sciences enable the deployment of complex computational algorithms that support the production of key representations across the design chain. In contrast with more traditional, explicitly-directed CAD authoring techniques â&#x20AC;&#x201C; which tend to apply embedded knowledge or established design decisions â&#x20AC;&#x201C; algorithmically-driven, procedural design systems may contribute important new intelligence about the target system of interest, which is derived through the modelâ&#x20AC;&#x2122;s execution. The intelligence produced within any given algorithm may be broadly varied, including (among many others) global form-finding exercises, the specification of local detail configurations for geometrically dynam-

ical assemblies, or analytical results, such as those that relate to structural behaviour or energy performance. This variety of output is reflective of the fact that contemporary architectural projects of even modest complexity are designed, developed, and ultimately realised through collections of partial representations, which organised as interconnected components within a larger model network. Model networks tend to be heterogeneous in their makeup, varied at least according to both typology and intent. For example, while certain partial models may be responsible for leveraging bottom-up, algorithmically driven agents to enact complex algorithmic transformations, others may necessarily be deployed through more explicitly directed, top-down interventions from the designer, such as in the definition of site constraints. The question of how multiple partial mod-

1 Mesh subdivision with face

inheritance

2 (next page) Bone structure 3 (next page) Diffusion-

limited aggregation

4 (next page) Stochastic fractal branching 5 (next page) Wrapped

curve network

CITA Complex Modelling

DISCUSSION

ADAPTIVE PARAMETRISATION

DAVID STASIUK

ACTIVATING INFORMATION THRESHOLDS IN MODEL NETWORKS

1 Mesh subdivision with face

inheritance

2 (next page) Bone structure 3 (next page) Diffusion-

limited aggregation

4 (next page) Stochastic fractal branching 5 (next page) Wrapped

curve network

CITA Complex Modelling

DISCUSSION

GROWTH AND OPEN TOPOLOGIES

ADAPTIVE PARAMETRISATION

uent elements in this way may simplify the operation of more straightforward supply chains, it does so through the simultaneous introduction of inflexibility into the model space. This rigidity of underlying elements leads to less interaction between model elements, making it increasingly difficult for discrete each to re-inform any other. It prevents partial models from effectively working conjunctively to create new design intelligence, or to behave as open-ended design systems capable of adapting to unknown conditions that might arise during design either internal to the design system itself, or external in terms of the design environment. It then becomes important to identify and pursue alternative modelling methodologies that question the static nature of these informational interfaces and instead explore the potential for model networks to perform both more holistically

– wherein the whole of the network’s behaviour becomes greater than the “sum of its parts” – and as open-ended, “creative” modelling environments that can better engage “ill-defined problems that defy direct solution…[where] we want the system itself to come up with a solution that we not some sense foreseen.” (Cariani 2008) The Complex Modelling project then focuses on the information thresholds that exist between the constituent partial models within a model network, especially regarding their capacity to its support improved holistic performances and open-ended design systems. Exploring the formulation of parameter space between partial models then becomes an essential topic of inquiry, especially for: how they share information with one another; how their information exchange may deepen or take on emergent characteristics; and how a more fluid changeability of both the number and

types of parameters shared may ultimately enhance design intelligence. Through a series of design experiments, Adaptive Parameterisation has been formulated as a modelling methodology that implements increasingly integrated and holistically performing partial model networks. Adaptive Parameterisation refers explicitly to modelling setups that facilitate the dynamic activation of mutable substrates. Here a mutable substrate is comprised of a topologically open-ended but organisationally persistent data structure that (at least partly) defines the parameter spaces which operate as thresholds between different partial models within the network. These data structures behave as synthetic information carriers whose geometric elements may be directly imbued with locally differentiated, semantically rich, descriptive labels. This flexible parameter space is thus configured to support

the dynamic activation increased design intelligence through a series of algorithmic methods that accumulate, transform, integrate, and command its underlying elements across the range of the project’s demands for design and realisation. Crucially, this dynamic activation supports the establishment of bi- or multi-directional constraints between discrete modelling systems, embedding interdependent relationships between models through more robust feedback loops, and enhancing the modelling system’s performance. It is important that these data structures and algorithms are configured to support the frequently heterogeneous makeup of the underlying partial models operating within complex networks, which are varied at least according to both typology and intent. For example, while certain partial models may be responsible for leveraging bottom-up, algorithmically driven agents

to enact complex algorithmic transformations, others may necessarily be deployed through more explicitly directed, top-down interventions from the designer, such as in the definition of site constraints. Model setups that effect positive holistic performances from their composite partial models negotiate this heterogeneity through the establishment of flexible data structures that ensure that the information produced along each stage of the supply chain will effectively interface with others, ensuring that wide ranges of design concerns can not only be reconciled, but used to enhance the performance of each other. This may be effectively achieved through the support of more robust feedback loops or the establishment of bi- or multi-directional dependencies between partial models. An experimental approach has been employed for identifying and testing this

methodology. Here, a series of experiments have been developed employing different vehicles of inquiry that provide a constructive basis for exploring adaptive parameterisation for design modelling, some of which include open topologies, material simulation, the consideration of design agency as a continuum, and multi-scalar modelling. This section briefly reviews some of these experiments, in relation to these vehicles of inquiry, and how they employ adaptive parameterisation in their model formulation. In modelling practices, it is common for form-making decisions or morphogenesis to follow the explicit direction of the designer. Even where advanced more dynamic form-finding techniques are employed, both the number and relationship between underlying elements tends to be pre-determined. This approach to form-making has been fundamentally

questioned through the experimental projects The Rise, The Social Weavers, and The ACADIA Rise. Each of these projects engages a growth-based algorithm, where the designed artefact emerges from a set of initial environmental conditions and goal-seeking behaviours, and elements are incrementally aggregated toward that end. Crucially, for these projects, feedback loops between structural assembly simulation and the underlying growth processes are tightly integrated such that material behaviours are directly embedded within the form as it grows into shape. In both The Rise and The ACADIA Rise, the growth model diagrammatically emulates natural plant growth processes whose properties are called tropisms. These include such environmentally triggered mechanisms as those reacting to light (phototropism), gravity (geotropism) or touch (thigmotropism), and which in-

els within a network may interact with or inform one another as a significant point of interest. Many contemporary approaches to architectural modelling describe the ability for data exchange between partial models as interoperability. Interoperability is most typically used to describe uni-directional translations of information along the supply chain. Most historical modelling methods have relied on the topological fixity of underlying design and data elements for managing interoperability between partial models. In this context, topology does not refer to the mathematical description of shape – such as an object being either a disc or a torus – but rather to the number of and connectivity between a set of values or objects. Here, the general numbers and relationships between designed elements is “known” before-hand, and explicitly defined by the designer. While constraining the topology of constit-

CITA Complex Modelling

GROWTH AND OPEN TOPOLOGIES

ADAPTIVE PARAMETRISATION

CITA Complex Modelling

GROWTH AND OPEN TOPOLOGIES

ADAPTIVE PARAMETRISATION

tinuous material simulation during morphogenesis, but engages with an especial focus on the implications of agency in the formulation computational design models, identifying bottom-up processes as distinct from top-down approaches. The experiment partly emerges as a response to The Rise, examining how its open-ended design modelling systems that implements tight, simulation-based feedback loops for the integration of material behaviours may limit designer agency: as morphogenesis increasingly relies on algorithmic bottom-up systems to produce an artefact, the designer’s top-down authorship becomes relegated to boundary definition and initial parameterisation. The Social Weavers then becomes a means to question this dichotomy and identify an alternative approach that considers agency along a continuum, where both designer authorship and algorithmic systems that

take advantage of the flexibility of open topologies may be better synthesised. While still considering the continuous simulation of underlying material properties during incremental and environmentally sensitive morphogenesis, the model network for The Social Weavers is further extended to allow for real-time, feedback-driven interaction from the designer. For each of these projects, the model networks that are employed for their development describe tightly collapsed feedback loops for operations that are more traditionally treated as discrete steps along the supply chain. Each of these generative modelling systems also further directly informs modelling processes for assembly detailing, material specification, digital fabrication, and installation. Custom data structures – or mutable substrates – were developed for each project to support this array of operations.

Stressed Skins is an installation whose design and fabrication processes were motivated by the continued exploration of both open topologies and design simulation. Here, however, the primary vehicle of inquiry was the investigation of multi-scalar modelling techniques, with an aim to better understand their potentials within the discipline of architectural design modelling for generative, analytical, and fabrication-related processes. The potentials of a multi-scalar modelling approach explored here apply to the computation of specific material properties in the context of experimental structural systems and digitally-driven production processes. Fundamental to these interests was the development and implementation of a method for managing data structures within and across the multiple models required for each stage of the supply-chain, from concept to build.

The material and assembly system used is of incrementally-formed, thin-sheet steel panels arrayed within a stressed-skin structure. The technique used is robotic single-point incremental forming (SPIF), whereby the slow application of a point force along a proscribed toolpath to a thin steel sheet steadily presses it into bespoke forms. The effects of the material transformation are such that strain hardening is locally introduced into the material to different degrees, depending on the depth and angle attained through the SPIF process. These variable material effects and properties are central to the multi-scalar modelling interests, which aim to understand the structure at several scales from the macro to the meso to the micro. Crucial here is identifying and deploying an interface that can negotiate changes in model scale while retaining critical information about geometry and material

properties. Here a half-edge mesh data structure operates as the primary vehicle for geometry development and model traversal. Half-edge mesh data structures allow for the efficient topological reading and transformation of mesh objects. Meshes of many types are routinely used for managing data structures related to both simulation and analysis within structural assemblies, but half-edge meshes are particularly well-suited to support the remeshing processes that are central to a multi-scalar modelling approach. Indeed, careful management of such a data structure allows a designer to effectively couple it with key information that persists across these different scales throughout the different stages of the design process. Central to the network model ecology is the development of both new implementations of existing computational approaches, and the formulation of novel tech-

niques and tools for form finding. These all take advantage of different capabilities of half-edge meshes, and in particular their utility in coupling geometry with multiple layers of semantically rich data about the assembly system. Through the development of these instruments, the model network becomes capable of producing coincident understandings of coarser topological relationships between individual panels in relation to each other within and across skins, granular understandings of local material behaviours related to geometric transformation within each panel, and highly refined geometries for defining digital fabrication drivers and toolpaths. The proliferation of new modelling techniques and availability of powerful algorithms for architectural designers presents both opportunities and challenges. On the one hand, access to new modelling systems that afford expanded descriptive

capabilities enables designers to employ higher-fidelity models at multiple stages in the design chain, from ideation through morphogenesis, development and fabrication. On the other hand, because any given project of even modest scope demands the application of multiple partial models and their organisation into a network of inter-related representational engines, this increasing specialisation and variation, makes it more difficult for architects and other stakeholders in the building sciences to deploy the types of open-ended creative systems that are desirable for addressing complex design problems. Adaptive Parameterisation aims to address this issue through its focus on the information thresholds – or parameter spaces – that bind partial models to one another. By formulating parameter spaces as mutable substrates that are dynamically changeable in both their number and the nature of

form morphogenesis such that the model then grows in response to its environment, extending and directing its morphogenesis according to the variations of light in the space. Crucially, this growth model is interfaced with a continuously running simulation model, where gravity and the emerging form’s contact to the surroundings are all enacted through the affordances and limitations endemic to its own materiality. The ACADIA Rise iterates on the fundamental approach employed for The Rise, first by extending the configurational possibilities for the branching behaviours of the growth process, and secondly by interfacing a more refined approach to dynamically specifying structural member size during morphogenesis and integrating its adaptive values into the continuous physical simulation of the material system. The modelling system of The Social Weavers employs a similar approach to con-

CITA Complex Modelling

GROWTH AND OPEN TOPOLOGIES

ADAPTIVE PARAMETRISATION

CITA Complex Modelling

ADAPTIVE PARAMETRISATION

DATE

VENUE

SUPPORT

TEAM

2013

ALIVE - Designing with

The Danish Council for Independent Research

Martin Tamke

Living Systems

Foundation EDF, France

Mette Ramsgaard Thomsen

Exhibition,

Dave Stasiuk

Fondation EDF, France

Hollie Gibbons Shirin Zeynab Zaghi Hasti Valipor

THE RISE

The Rise examines growth algorithms as a model for adaptive parametrisation. To preserve design control, parametric models necessarily operate with a reduced number of design parameters. Where this is practical, it also limits our way of understanding the potential of design synthesis and leads to an inherently reductive design process that contradicts the inherently emergent nature of design as a process of discovery. The Rise examines how the concept of growth can allow us to design system systems that self-evaluate and respond to evolving design parameters. Natural plant growth presents a diagrammatic framework for investigating these questions. Plant formation is accretive, and successive growth iterations depend on the physical properties of previously accumulated matter, in relation to both the plant itself and its environment. As a result, the physical manifestation of a plant â&#x20AC;&#x201C; its

evolving body plan - reflects the interplay between an internal rule structure unique to each species and each plantâ&#x20AC;&#x2122;s individual environment (1). The Rise is a fibrous structure made of bundled bending active elements branching in structural nodes. Built in rattan, the project examines the integration of processes of parametrisation, generation and analysis of material behaviour into consolidated feedback loops. In The Rise, we design a bespoke particle-based spring and gravity simulation system that embeds both material intelligence - a model of the behaviour and performance of the material system - and environmental sensing, calibrated through measured, real-world material behaviours. The Rise employs the concept of tropism as a way of guiding growth. Tropism in biology indicate the growth tendencies of plant organisms in response to environ-

mental stimulus. In The Rise we focussed on three types of tropisms: phototropism (light-driven response), geotropism (gravity-driven response) and thigmotropism (touch-driven response) (2). We create an algorithmic growth system in which a synthetic metabolism steers the structureâ&#x20AC;&#x2122;s ability to negotiate between different attractors and distribute energy to differentiated tasks including branching, self-grafting and climbing. The growth system uses a time-based cellular accretion model realised through the accumulation of minimal triangulated truss-like modules which are managed in a mesh. By carefully managing the emerging model topology, we can continually simulate the physical system and analyse for bending and torsional rotation as well as trigger and steer new growth cycles. The branching structure is a realised as a set of increasingly dense struts made

of numerous rattan strands with varying thicknesses. Held together by customised packing nodes, the struts behave like a textile in that they rely on the friction between fibres. The struts are able to branch by splitting into multiple bundles. This branching is managed by simulating the bending action of the individual rattan strands and calibrating them against each other. The Rise investigates methods of accumulative parametrisation of a design space and builds fundamental concepts for understanding design integrated simulation and adaptive parametrisation and the link between high level simulation of material behaviour and the modelling of all-encompassing fabrication and assembly information data. The structure makes use of low scale material behaviour and orchestrates these into higher scale structural performances. Built in the image of the bush, The

1 The Rise Installation at

the ALIVE - Designing with Living Systems Exhibition, Fondation EDF, Paris

CITA Complex Modelling

PROJECT

ADAPTIVE PARAMETRISATION

DATE

VENUE

SUPPORT

TEAM

2013

ALIVE - Designing with

The Danish Council for Independent Research

Martin Tamke

Living Systems

Foundation EDF, France

Mette Ramsgaard Thomsen

Exhibition,

Dave Stasiuk

Fondation EDF, France

Hollie Gibbons Shirin Zeynab Zaghi Hasti Valipor

THE RISE

1 The Rise Installation at

the ALIVE - Designing with Living Systems Exhibition, Fondation EDF, Paris

CITA Complex Modelling

PROJECT

THE RISE

ADAPTIVE PARAMETRISATION

GROWTH AND AWARENESS IN COMPUTATIONAL MODELLING

2 Speculative physical

model investigating tropisms, branching, grafting and flowering

3 Close up of the model

CITA Complex Modelling

The Rise imagines a growing architecture. By We using investigate growth as a novel approach towards computational design, means of understanding the necessary parametrisation of design, not as a terminal, but as an accretive process in which design criteria are continually added during the design process. Like a bush, the installation has its own internal growth patterns that guide the evolution of the structure through the material accumulation, orientation and distribution of bundled fibrous struts. The struts lengthen, branch, climb, self-graft and flower, all as a result of an encoded synthetic metabolism. The computation design system takes a conceptual point of departure in biological plant growth. Like a plant, The Rise is guided by a series of tropisms that steer its growth cycles. These are set in relationship to the installation environment; the floor and walls of the space providing structural support, and a diagrammatic simulation of light providing â&#x20AC;&#x2DC;energyâ&#x20AC;&#x2122; thereby activating growth. What emerges is a self-aware model. Informed by this structured relationship to its environment as well as a fully integrated and continually looped simulation of its own evolving body plan, its direction, orientation and self-weight, the structure builds on an awareness not only of its containing environment, but also of its own reactions to external stimuli.

THE RISE

ADAPTIVE PARAMETRISATION

GROWTH AND AWARENESS IN COMPUTATIONAL MODELLING

2 Speculative physical

model investigating tropisms, branching, grafting and flowering

3 Close up of the model

CITA Complex Modelling

THE RISE

ADAPTIVE PARAMETRISATION

NATURAL GROWTH SYSTEMS

natural growth systems GEOTROPISM

PHOTOTROPISM

geotropism

THIGMOTROPISM

phototropism

additional growth

thigmotropism

growth slowed along edge growth slowed along edge saturated with saturated with light-drawn auxin, allowing auxin, opposite light-drawn edge to “bend“ towards allowing opposite the light edge to “bend” towards light

stimulated along additional growth stimulated edge saturated with along edge saturated with gravity-drawn auxin, auxin, bending gravity-drawn it bending away fromit theaway earth from the earth

growth heavily restricted by growth is heavily restricted touch-drawn auxin, by touch-drawn auxin, elongating the outer elongating the outer edge edge and causing and causing shoot to wrap around the obstruction shoot to wrap around obstruction

ACCRETION accretion

initial direction determined by both

initial direction determined by both geotropism and geotropismaccretion and phototropism, accretion phototropism, afforded by acquistion of light afforded by acquistion of light energy energy

BRANCHING branching

branch direction and shoot-type coded by branch direction and shoot-type coded by baseline orientation, baseline orientation, geotropism, phototropism geotropism, phototropism and environmental sensing and environmental sensing

CLIMBING climbing

branch growth tips sense the physical branch growth tips sense the physical environment environment and fix themselves by and fix touch themselves by touch

GRAFTING grafting

branch growth tips sense other branch growth sense branches the model branches in theother model andinfuse into andthem fuse into them

codedCODED growth systems GROWTH SYSTEMS

The Rise uses the concept of tropisms as a means of steering growth. Tropisms – in Greek “turning” – was first proposed in 1927 as differential growth responses that reorient plant organs in response to direction of physical stimuli, and is today widely used to describe the continuous change and transformation expressed during growth (3). In The Rise we interpret tropisms through the algorithmic deployment of directional orientation and task assignment during branching, self-grafting and climbing. The Rise emulates three types of tropism: phototropism (light-driven response) informing the direction and branch type for new growth tips that emerge during branching moments. Based on their orientation toward both the simulation light source and their physical environment, new branches are assigned roles as either being light-seeking or structural and given an initial growth vector. Geotropism (gravity-driven response) informs the relationship to gravity and a perception of self-weight and thigmotropism (touch-driven response) enabling a proximity sensing to both the physical environment, which leads them to fix as climbers, or to other branches, which leads them to graft on to these as new circular branches providing structural strength.

4 Diagrammatic interpretation of auxindriven tropisms in vegetative growth for “The Rise” 5 Experiment with Closed

growth systems based on leaf venation strategy, using a generative fibrous system (grey lines) guided by distributed auxins in space (red spheres)

6 The Rise grows towards

an artificial sun in the digital model

CITA Complex Modelling

TROPISM

THE RISE

ADAPTIVE PARAMETRISATION

NATURAL GROWTH SYSTEMS

natural growth systems GEOTROPISM

PHOTOTROPISM

geotropism

THIGMOTROPISM

phototropism

additional growth

thigmotropism

stimulated along additional growth stimulated edge saturated with along edge saturated with gravity-drawn auxin, auxin, bending gravity-drawn it bending away fromit theaway earth from the earth

ACCRETION accretion

initial direction determined by both

initial direction determined by both geotropism and geotropismaccretion and phototropism, accretion phototropism, afforded by acquistion of light afforded by acquistion of light energy energy

BRANCHING branching

CLIMBING climbing

branch growth tips sense the physical branch growth tips sense the physical environment environment and fix themselves by and fix touch themselves by touch

GRAFTING grafting

branch growth tips sense other branch growth sense branches the model branches in theother model andinfuse into andthem fuse into them

codedCODED growth systems GROWTH SYSTEMS

4 Diagrammatic interpretation of auxindriven tropisms in vegetative growth for “The Rise” 5 Experiment with Closed

growth systems based on leaf venation strategy, using a generative fibrous system (grey lines) guided by distributed auxins in space (red spheres)

6 The Rise grows towards

an artificial sun in the digital model

CITA Complex Modelling

TROPISM

THE RISE

ADAPTIVE PARAMETRISATION

AUXIN AND LEAF VENATION AS A DYNAMIC AND ADAPTIVE MODELLING PARADIGM

7 Leaf venataion structure 8 Open 2D venation growth diagrams with multiple sources

CITA Complex Modelling

In plants, the operating mechanism for growth differentiation is auxin – a hormone that directs new cellular growth and coordinates the emergence of the plant’s geometry. Within the plant’s metabolism, the presence or absence of auxin triggers the distribution of those available resources required for growth. These hormones will often suppress (or activate) growth in certain cells or locations by restricting (or promoting) energy-based resources in order to allow for an uneven and ultimately directed cellular growth. This localized cellular variation serves to orient the plant according to an internalized rule system that ultimately produces goal-oriented growth and organizational emergence. During the growth process the metabolism constantly assesses its environment for energy and opportunities to gain strength and its current structural condition (stresses and utilisation of members). One such system we examine is that of leaf venation patterning. In The Rise we simulate a synthetic metabolism based on the modelling methodology described by Runions et al (4). This system depends on the interpretation of morphogenesis put forth by Pavel Dimitrov and Steven Zucker (5), whereby the hormone auxin, randomly distributed over the leaf surface, is transported along paths of least resistance in the canalization of new vein structures, whose directionality and splitting are determined according to each vein source’s proximity to each auxin and the available growth space.

THE RISE

ADAPTIVE PARAMETRISATION

AUXIN AND LEAF VENATION AS A DYNAMIC AND ADAPTIVE MODELLING PARADIGM

7 Leaf venataion structure 8 Open 2D venation growth diagrams with multiple sources

CITA Complex Modelling

ADAPTIVE PARAMETRISATION

GROWTH

THE RISE

ENERGY

Flowering

Branching

Grafting

Accretion

Photosynthetic

Embedded ( seed )

Climbing

SIMULATION ( material behavior)

Self - sensing ( thigmo-)

Environment sensing ( thigmo-)

Light ( photo-)

Gravity ( geo-)

THE RISE METABOLISM

CITA Complex Modelling

The Rise models a synthetic metabolism in which a series of dependencies are negotiated. In addition to the simulation of tropisms, which enable building of an internal sensing of its containing environment, The Rise integrates a tightly coupled on-going simulation of its material system. In this way it holds a perception of its own presence; it direction and orientation including the bending and twisting under self-weight. This simulation builds on data gathered through physical experiments with the rattan material. Through tests, we build a formalised understanding of the bending behaviours and performances of the different radii of rattan material. These are inputted into the simulation allowing each growth cycle to equally determined by an understanding of the internal mutability and performance of the material system as the attractors of the external environment. As a result, the form is as much a non-deterministic material response to its own geometry and performance as it is to the integral formation algorithms that dictate the properties of its modular accretion.

TROPISM

initial angle up

9 The Rise grows towards an artificial sun in the EDF exhibition space

element length

10 Diagram of the metabolistic system developed for The Rise 11 Analysis of bending

behavior in particle system examining initial growth angle, final length, and spring stiffness

stiffness 9

ADAPTIVE PARAMETRISATION

GROWTH

THE RISE

ENERGY

Flowering

Branching

Grafting

Accretion

Photosynthetic

Embedded ( seed )

Climbing

SIMULATION ( material behavior)

Self - sensing ( thigmo-)

Environment sensing ( thigmo-)

Light ( photo-)

Gravity ( geo-)

THE RISE METABOLISM

CITA Complex Modelling

TROPISM

initial angle up

9 The Rise grows towards an artificial sun in the EDF exhibition space

element length

10 Diagram of the metabolistic system developed for The Rise 11 Analysis of bending

behavior in particle system examining initial growth angle, final length, and spring stiffness

stiffness 9

THE RISE

ADAPTIVE PARAMETRISATION

symmetrical: single element straightening

asymmetrical configurations

14 12 Catalog of the beam self connections 13 Rattan core comes in a variety of different thickness. Colour and size varies according to the species and where it is grown 14 Early prototypes of LDPE

8mm double star nodes

15 Early investigations of active bending in branch geometry

The Rise is built in rattan core wood. Rattan is a Southeast Asian vine-like palm that climbs host trees in search for light. The woody material is soft comprised of continuous, tightly packed hollow fibres. In difference to other long woody plants, like bamboo, the material organisation does rely on regular linear segments. This is because rattan relies on other plants for structural support. The long fibres give the material high tensile performance, great flexibility and resilience to breaking needed for winding along other plants and enable efficient water and nutrient transport from the ground. The inherent flexibility is maintained post harvest. In The Rise we use these behaviours to create a bending active structure. The Rise is made of sustainably harvested Malaysia rattan knife-extruded into round sections of 5, 10 and 19mm. Each thickness indicates a different bending radius. By calibrating these and embedding them into the integrated simulation system we are able to give the model an understanding of its own prescriptive behaviours.

symmetrical: dual element straightening

CITA Complex Modelling

MATERIAL SYSTEM

THE RISE

ADAPTIVE PARAMETRISATION

symmetrical: single element straightening

asymmetrical configurations

14 12 Catalog of the beam self connections 13 Rattan core comes in a variety of different thickness. Colour and size varies according to the species and where it is grown 14 Early prototypes of LDPE

8mm double star nodes

15 Early investigations of active bending in branch geometry

symmetrical: dual element straightening

CITA Complex Modelling

MATERIAL SYSTEM

THE RISE

ADAPTIVE PARAMETRISATION

BUNDLING AND BRANCHING LOGIC

16 Early investigation of

active bending in branch geometry

17 A simplified section of a

branch reveals its complex fibrous setup, which works in compression as well as in tension

18 Strangler fig tree demonstrating a common growth habit, adapting for growing in dark forests

CITA Complex Modelling

The material system of The Rise uses bundling to emulate a fibrous structure and regulate stiffness and bending strength. In nature, bundling of fibres provides organic systems with methods that direct generation, adaptation and variation and provides means for compartmentalization, redundancy, robustness and flexibility (6). In many instances, long fibres are oriented in parallel and arrayed in nested hierarchies of stacked bundles, often beginning at the molecular scale. These stiff fibres are generally unconnected physically and are either embedded in a matrix material – such as tree fibrils in a soft mix of lignin and hemicellulose (7) – or are organized through friction – such as muscle fibers (8). In The Rise bundling is used to accrue stiffness in order to support structural performance or conversely to diminish in order to enable bending. The bundle is held together by an assembly of packing nodes milled in high density polyethylene that tie the bundle together in a compressive action and thereby act like a matrix coordinating fibre to fibre friction. The bundle is used as base structure for three dimensional branching in which a strut can split and become three new branches. These connections are facilitated through the invention of an oppositional bending-active connection assembly in which counter bent support members strengthen and steer the bending radii. In this way the system can direct at each node the growth direction of each of the spawning branches. To support branching the packing node is inverted into a ‘star-element’ that organises the material and orients it towards the inferred bending. The computational system automates this organisation, based on the integrated simulation of discretised material behaviour of the individual strand thicknesses.

THE RISE

ADAPTIVE PARAMETRISATION

BUNDLING AND BRANCHING LOGIC

16 Early investigation of

active bending in branch geometry

17 A simplified section of a

branch reveals its complex fibrous setup, which works in compression as well as in tension

18 Strangler fig tree demonstrating a common growth habit, adapting for growing in dark forests

CITA Complex Modelling

THE RISE

ADAPTIVE PARAMETRISATION

GRAFTING BRANCHES

relative total spring deformation

connection node total section material distribution 19 Diagram of the spatial

relative total spring deformation

20 Diagram of the material

distribution through the connection nodes

CITA Complex Modelling

Our interest in The Rise is to understand how growth can allow an accretive understanding of parametrisation allowing the body plan to emerge through the design process. Similar to strangler fig and other types of ficus, a central interest in The Rise is to allow individual branches to meet and self-graft together in circular networks in order to create structural strength through spatial topologies. Existing biologically inspired systems for algorithmic branching such as l-systems (both deterministic and stochastic), diffusion-limited aggregation, and viscous fingering tend to result in open branch networks, such that any one terminus will have a single path to the root of growth. Our interest in self-grafting is both structural and topological. Self-grafted branches and triangular geometries create strong framelike moments in the emerging network, increasing overall structural strength. The Rise aims hence for high degree of interconnectivity and triangulation. At the same time, the self-grafting of the branches challenges the inherent linearity of the evolving computational model body plan by creating new vertices in the underlying model graph.

THE RISE

ADAPTIVE PARAMETRISATION

GRAFTING BRANCHES

relative total spring deformation

connection node total section material distribution 19 Diagram of the spatial

relative total spring deformation

20 Diagram of the material

distribution through the connection nodes

CITA Complex Modelling

bend ( side view )

110 100 90

21 Spring model exhibiting

r40.33, (min radius)

64.0

used for capturing growth, registering branching orientations and geometries, and passing critical topological and bending deformation information from the morphogenetic model to the fabrication model

r50.63, (pre bending)

49.0

23 Triangulated system

r18.05 (radius without pre bending)

24 Early bending test of

rattan bundle

r7.40, (pre bending) r6.01 (min radius) 17.0 9.0

11.4

25 Identification of minimum bending radius by rattan section 17 10 5

5.5

time

6.0kg

modular accretion and branching logics for management of springbased system and growth/ branching topologies

5.0kg

22 Minimally triangulated

torque/rotation due to asymmetrical loading/ orientation of branches combined with bending

(min radius without pre bending)

Radius (cm)

CITA Complex Modelling

4.0 kg

3.5 kg

torque (front view)

1.5 kg

The Rise integrates simulation that estimates the behaviour of the rattan strands. Each growth step is registered as part of an active and interdependent simulation system that synthesizes the interplays between energy acquisition and metabolism, algorithmic growth tropisms, environmental sensing, and physical response. In The Rise, the simulation does not take point of departure in material properties. Firstly, rattan is an unusual architectural material with very heterogeneous behaviour changing from harvest to harvest and between locations. Secondly, these simulations are too detailed for the complex accumulative processes of the growth algorithm. Instead, we implement a geometric simulation based on observed behaviours. The simulation uses a bespoke coded particle engine that calculates the bundle sizes and their distribution at each growth cycle. The simulation problem in The Rise is its torsional behaviour at moments of branching. Where simpler particle systems can capture the bending forces, the torsional simulation must account for the particleâ&#x20AC;&#x2122;s orientation around a primary axis as well as the desired angle of bending between particles. In branching moments, these local forces must be composed and understood together as members operate against each other in oppositional active bending. The spring deformation data, as it reacts to further accretion, is registered and later used for assigning material thickness to each connection node and managing local compressive and tensile stresses. By embedding information about the materialâ&#x20AC;&#x2122;s maximum bending radii and bending geometry and coupling this with orientation and deformation information, we can dynamically size the bundles at each node and along each strut.

0.5 kg

120

SIMULATING BENDING AND TORSION IN THE RISE

16.3

21.5

28.5

Diameter (cm)

104

THE RISE

ADAPTIVE PARAMETRISATION

bend ( side view )

110 100 90

21 Spring model exhibiting

r40.33, (min radius)

64.0

r50.63, (pre bending)

49.0

23 Triangulated system

r18.05 (radius without pre bending)

24 Early bending test of

rattan bundle

r7.40, (pre bending) r6.01 (min radius) 17.0 9.0

11.4

25 Identification of minimum bending radius by rattan section 17 10 5

5.5

time

6.0kg

modular accretion and branching logics for management of springbased system and growth/ branching topologies

5.0kg

22 Minimally triangulated

torque/rotation due to asymmetrical loading/ orientation of branches combined with bending

(min radius without pre bending)

Radius (cm)

CITA Complex Modelling

4.0 kg

3.5 kg

torque (front view)

1.5 kg

0.5 kg

120

SIMULATING BENDING AND TORSION IN THE RISE

16.3

21.5

28.5

Diameter (cm)

104

THE RISE

ADAPTIVE PARAMETRISATION

THE RISE

ADAPTIVE PARAMETRISATION

EMERGING TOPOLOGIES

26 Stills captured from

animation from the digital growth

27 Testing growth algorithm 28 Accumulated stress in

branching

CITA Complex Modelling

The Rise requires careful topological management. The use of a centralised geometry system â&#x20AC;&#x201C; a simplified triangulated truss - enables the integration of the continuous physical simulation of the accumulated time-based transformations of the structure. In contrast to the commonly used polyline models for bending active structure, triangulated trusses allows us to approximate both bending and torsional behaviours as observed in the physical prototypes. The model topology is unfixed in each growth step enabling a dynamic and adaptive parameter space. The triangulated truss is a digital mesh whose vertex, edge and face topologies become a central shared data structure that informs the multiple, interdependent fabrication drivers including: information designating variable connection types (including regular branching, grafting, and structural tie-back), strut connectivity assignments, assembly sequencing, and member sizing. In this manner, the mesh becomes the interface - a means for full model integration. It combines the simulated physical performances with multiple custom classes used for capturing vital information about the modelâ&#x20AC;&#x2122;s growing, branching, grafting and flowering events. The spring-based system also endows the model geometry with direct indicators of material performance (1).

THE RISE

ADAPTIVE PARAMETRISATION

EMERGING TOPOLOGIES

26 Stills captured from

animation from the digital growth

27 Testing growth algorithm 28 Accumulated stress in

branching

CITA Complex Modelling

THE RISE

ADAPTIVE PARAMETRISATION

110

100

2 3

90 3

2 1

The simulation - parameterisation of spring stiffness, particle mass, strength of gravity, and the radius and length of each growth module - is based on the analysis of material tests and physical prototypes allowing us to infer a formalised understanding of behaviour and calibrate the simulation accordingly. Early material testing examine the bending behaviour thought three key properties: minimum bending radius, bending action under force and creep. The tests are done for the three different material thicknesses employed in The Rise. A second set of tests examine the aggregate behaviour of the bundle. A full scale prototype was built to test branching geometries and performance. Here, the sectional thickness of the bundling and the distribution of different rattan thickness is analysed and understood. The prototype is 3D scanned and overlaid the digital simulation to account for deviation enabling a final tuning of the simulation.

60 3

20 29 3D scan for evaluation of one of the build10 prototypes in CITA space 30 Analysis of bending and creep by section and variable 0 loading conditions

4mm

5mm

10mm

17mm

30mm

CITA Complex Modelling

CALIBRATING THE SIMULATION

THE RISE

ADAPTIVE PARAMETRISATION

110

100

2 3

90 3

2 1

60 3

20 29 3D scan for evaluation of one of the build10 prototypes in CITA space 30 Analysis of bending and creep by section and variable 0 loading conditions

4mm

5mm

10mm

17mm

30mm

CITA Complex Modelling

CALIBRATING THE SIMULATION

THE RISE

ADAPTIVE PARAMETRISATION

37-3

373

375

203 374

377 378

F60-1

376 381

379

200

442

202

443

440439 438 441437

270 274 436

201 271

275

380

199

The final design can be understood as an aggregate of branches, stretching towards the ceiling light, finding support by grafting on to the walls of the interior and self-grafting onto other branches. The Rise springs from two seed points at two columns in the exhibition space. As the structure grows it propagates structural shoots and gripping feet that gain support from the floor. The final design implementation takes place through a final tuning and setting of design parameters. The design focuses on a high degree of branching in the middle of the installation, creating a complex interconnected topology and a high degree of structural stability. As the structure rises towards the light the high degree of accumulated cantilever results in the generation of a forest of slender columns that people move through.

31 The digital model

provides information on every part of the assembly

32 Caption 33 Caption 34 Rattan elements laid

out sequentially according to installation order, with temporary tags showing locations of associated star nodes and packing nodes along the length of each member

CITA Complex Modelling

DESIGN IMPLEMENTATION

THE RISE

ADAPTIVE PARAMETRISATION

37-3

373

375

203 374

377 378

F60-1

376 381

379

200

442

202

443

440439 438 441437

270 274 436

201 271

275

380

199

31 The digital model

provides information on every part of the assembly

32 Caption 33 Caption 34 Rattan elements laid

out sequentially according to installation order, with temporary tags showing locations of associated star nodes and packing nodes along the length of each member

CITA Complex Modelling

DESIGN IMPLEMENTATION

ADAPTIVE PARAMETRISATION

THE R I SE Apri l. 2013

THE RISE

THE RI SE Apr il. 2013

Early bundle detail

Early bundle detail BundleBundle

Bundle

Early bundle detail Early bundle detail

Early bundle detail

Bundle

Early bundle detail

B Bundle

Early bundle detail Bundle

Early bundle detail 1

1 2

TH THEE R RIISSEE A Ap p ri rill.. 22001133

2 3

2mm acrylic

http://cita.karch.dk

http://cita.karch.dk 3

2mm acrylic

http://cita.karch.dk

THE RISE April. 2013 THE RISE A pr il. 2013

Bundle Bundle

undle

Bundle

Early bundle detail

Bundle Early Early bundle bundle detail detailBundle

Early bundle detail

Bundle

Early bundle detail

Bundle D

Early bundle detail Early bundle detail

Early bundle detail

Bundle

3 2

1 1

2 2

Early bundle detail

3 3 http://cita.karch.dk http://cita.karch.dk

8mm LDPE

Early bundle detail Early bundle detail

Early bundle detail

FABRICATION 1

4mm PP

In The Rise, the generative growth model interfaces with a fabrication model. The fabrication model received the topological relationships between the branches and the distribution of material for structural performance. It converts this data into digital fabrication files for milling of 500 bespoke high-density polyethylene components and for sizing, arrangement and enumeration of over 500 individual rattan members. It also supports fabrication sequencing. http://cita.karch.dk http://cita.karch.dk

6mm HDPE

35 Types of the bundling plastic details 36 Early prototypes of star

nodes

12mm HDPE

http://cita.karch.dk

12mm LDPE

12mm HDPE

CITA Complex Modelling

4mm ABS

ADAPTIVE PARAMETRISATION

THE R I SE Apri l. 2013

THE RISE

THE RI SE Apr il. 2013

Early bundle detail

Early bundle detail BundleBundle

Bundle

Early bundle detail Early bundle detail

Early bundle detail

Bundle

Early bundle detail

B Bundle

Early bundle detail Bundle

Early bundle detail 1

1 2

TH THEE R RIISSEE A Ap p ri rill.. 22001133

2 3

2mm acrylic

http://cita.karch.dk

http://cita.karch.dk 3

2mm acrylic

http://cita.karch.dk

THE RISE April. 2013 THE RISE A pr il. 2013

Bundle Bundle

undle

Bundle

Early bundle detail

Bundle Early Early bundle bundle detail detailBundle

Early bundle detail

Bundle

Early bundle detail

Bundle D

Early bundle detail Early bundle detail

Early bundle detail

Bundle

3 2

1 1

2 2

Early bundle detail

3 3 http://cita.karch.dk http://cita.karch.dk

8mm LDPE

Early bundle detail Early bundle detail

Early bundle detail

FABRICATION 1

4mm PP

6mm HDPE

35 Types of the bundling plastic details 36 Early prototypes of star

nodes

12mm HDPE

http://cita.karch.dk

12mm LDPE

12mm HDPE

CITA Complex Modelling

4mm ABS

ADAPTIVE PARAMETRISATION

THE RISE

T HE R IS E A p r il . 2013

1 2 3 4

Diagram explaining overlaying system of star connections

Overlaying system of star connections

Bundling, A system of growth

Growth 1

Not unlike structures in nature stresses that come through the expansion of the systems are encountered by radial growth. The addition of rings creates positions for additional layers of rattan that give the needed strength when the structure is built up. Early nodes from ABS Plastic hold the bundles of Rattan Core in place. The developed node system uses the plastics material properties and ability to be CNC machined.

The materials flexibility and durability allows to construct joints that are holding the rattan simply through friction. Plates with precisely cut

openings are stacked. Their precisely cut openings close around the rattan and grab faster the closer the plates are pushed together. A snap in principle is combined with natural material.

013 Growth 1

CITA Complex Modelling

T H E R IS E A p ril . 2013

Growth 1

Growth 2

Growth 3

THE RISE April. 2013

1 2

4 4

Growth 2

Growth A

ying system of star connections

Growth 1

BUNDLING, SYSTEM OF GROWTH

Growth 2

Growth Growth3C

Growth B

Growth 3

Growth D

Growth 4

http://cita.karch.dk

Diagram explaining overlaying system of star connections Diagram explaining overlaying system of star connections

g , A s y st e m o f Bguro of growth n dwl itnhg , A s y stBundling, e m o f g r oAwsystem th Growth 1

Growth 1

Growth 2

Growth 3

nature stresses that come through the expansion Notthrough unlike structures in nature stresses that come through the expansion Not unlike structures in nature stresses that come the expansion of the systems are of encountered by radial growth. The addition of rings untered by radial growth. The addition of rings of the systems are encountered by radial growth. The addition rings creates positions for additional layers of rattan that give the needed dditional layers of rattan that give the needed creates positions for additional layers of rattan that give the needed

strength when the structure is built up. Early nodes from ABS Plastic cture is built up. Early nodes from ABS Plastic strength when the structure is built up. Early nodes from ABS Plastic hold the bundles of Rattan Core in place. The developed node system ttan Core in place. The developed node system hold the bundles of Rattan Core in place. The developed node system

uses the plastics material properties and ability to be CNC machined.

uses the plastics material properties and ability to be CNC machined. ial properties and ability to be CNC machined. The materials flexibility and durability allows to construct joints that y and durability allows to construct jointsThe thatmaterials flexibility and durability allows to construct joints that are holding the rattan simply through friction. Plates with precisely cut

arecut holding the rattan simply through friction. Plates with precisely cut imply through friction. Plates with precisely 1 openings are stacked. Their precisely cut openings close around the are stacked. Their 1precisely cut openings close around the Their precisely cut openings close aroundopenings the rattan and grab faster the closer the plates are pushed together. A snap rattan and grab faster the closer the plates are pushed together. A snap he closer the plates are pushed together. A snap in principle is combined with natural material. 2 in principle is combined with natural material. d with natural material.

1 2

Growth 4

The rattan bundle strut are held together by a matrix of packing nodes that organise different rattan strands and interface fibre to fibre friction. The packing nodes are milled as a set of bespoke rings with indents – or teeth – that grip and secure the rattan members in a tight packing. The fabrication model outputs the local geometry of each individual packing node by referencing the generative growth model and the precise distribution of the different thickness rattan members. http://cita.karch.dk

37 Diagram explaining overlaying system of star connections

38 Different strategises for the ratan rods bundling nodes A - “star“ type B - “packing“ type C - “growth“ plate iterations 39 Computationally generated digital model of rattan struts and connection nodes as organized by HDPE “packing nodes” and “stars” 40 Fabrication of the nodes

3 37

3 4

by CNC-milling

Growth 4

ADAPTIVE PARAMETRISATION

THE RISE

T HE R IS E A p r il . 2013

1 2 3 4

Diagram explaining overlaying system of star connections

Overlaying system of star connections

Bundling, A system of growth

Growth 1

The materials flexibility and durability allows to construct joints that are holding the rattan simply through friction. Plates with precisely cut

openings are stacked. Their precisely cut openings close around the rattan and grab faster the closer the plates are pushed together. A snap in principle is combined with natural material.

013 Growth 1

CITA Complex Modelling

T H E R IS E A p ril . 2013

Growth 1

Growth 2

Growth 3

THE RISE April. 2013

1 2

4 4

Growth 2

Growth A

ying system of star connections

Growth 1

BUNDLING, SYSTEM OF GROWTH

Growth 2

Growth Growth3C

Growth B

Growth 3

Growth D

Growth 4

http://cita.karch.dk

Diagram explaining overlaying system of star connections Diagram explaining overlaying system of star connections

g , A s y st e m o f Bguro of growth n dwl itnhg , A s y stBundling, e m o f g r oAwsystem th Growth 1

Growth 1

Growth 2

Growth 3

uses the plastics material properties and ability to be CNC machined.

1 2

Growth 4

37 Diagram explaining overlaying system of star connections

3 37

3 4

by CNC-milling

Growth 4

CITA Complex Modelling

THE RISE

ADAPTIVE PARAMETRISATION

are laid out before the fabrication

42 “Packing“ type of notes just from the CNC-milling bed

41 The Rise “star” details

CITA Complex Modelling

THE RISE

ADAPTIVE PARAMETRISATION

are laid out before the fabrication

42 “Packing“ type of notes just from the CNC-milling bed

41 The Rise “star” details

THE RISE

ADAPTIVE PARAMETRISATION

4 4

5 6

6 2

7 1

9 11

0 10

4 6

6 2

5 1

9 11

0 8

10 10

9 0

43 Photo demonstrating the labelling strategy of the nodes 44 “Star nodes“ accomodating various thickness ratans 45 Digital representation of connection node #6 and the physical manifestation of connection node #17, demonstrating two different, bespoke branching geometries achieved through variably-sized and numbered oppositional active-bending rattan members, managed through the HDPE “star” configurations

46 Final version of a packing

node, cut to the specified bundle arrangement of rattan

CITA Complex Modelling

The packing nodes also orchestrate the strengthening of the structure. Like a tree, the radial growth occurs as the addition of rings creates positions for further layers of rattan thickening the strut. Strut connections between nodes are designed to maximize the continuity of single rattan members. After each connection has been configured, a comparative an analysis is performed between stars that share a strut. The section of each member for each star is mapped to an average plane between connecting stars. Member of identical size from adjacent starts that falls within a set radius of each other on this plane are fused into a continuous member. All remaining members are set to overlap with terminating members from the other node within the strut and cut. The packing nodes are milled in high density polyethylene. The material is flexible allowing us to create snap joints without cutting or breaking the rattan. The joints hold the strut together through pure friction.

THE RISE

ADAPTIVE PARAMETRISATION

4 4

5 6

6 2

7 1

9 11

0 10

4 6

6 2

5 1

9 11

0 8

10 10

9 0

46 Final version of a packing

node, cut to the specified bundle arrangement of rattan

CITA Complex Modelling

THE RISE

ADAPTIVE PARAMETRISATION

node area: 26.5cm2

node total sectional area: 26.5 cm²

individual member individual member assignment assignment

111°

4.3 cm²

2-3

99°

4.1 cm²

1-3

66°

2.1 cm²

1-2

80°

2.7 cm²

0-3

155°

7.3 cm²

0-2

136°

6.1 cm²

0-1

topological topological distribution distribution

relative star relative star orientations orientations

sectionarea area section distribution distribution

75 74

BRANCHING

68 72

Details play an important role in the system. The detailing is developed in CNC milled HDPE (Hight Density PolyEthilene) which allows us to use the materials inherent flexibility and strength. All details follow a snap-fit logic in which material bending allow the locking of connections on to the fibreglass beams and allow tightening of the cable net. Details were explored through a series of iteration in which the connection logic, snap fitting and its local tensioning were optimised. The detailes are divided into three categories: (1)Beam-to-beam connectors, (2)Cable-tobeam connectors, (3)Cable-to-cable connectors. The development of the details were undertaken through the iterative fabrication of designed detailes and load testing.

75 74

255

68 72

255

continuous members non-continuous members

continuous members continuous members non-continuous members non-continuous members

47 Topological array of individual rattan elements across each bespoke CNCmilled HDPE “star” element within connection node #6 48 Diagram demonstrating

continious and discontinious members running through the node

49 Steel rod and ball joint detail activated by “thigmotropism” in the generative algorithm, used in climbing and secondary environmentally responsive connections 50 Aluminum “column

hugger” collar system, utilized for securing the installation at its two primary growth “seeds”

51 Solution for the end of the

branch

CITA Complex Modelling

THE RISE

ADAPTIVE PARAMETRISATION

node area: 26.5cm2

node total sectional area: 26.5 cm²

individual member individual member assignment assignment

111°

4.3 cm²

2-3

99°

4.1 cm²

1-3

66°

2.1 cm²

1-2

80°

2.7 cm²

0-3

155°

7.3 cm²

0-2

136°

6.1 cm²

0-1

topological topological distribution distribution

relative star relative star orientations orientations

sectionarea area section distribution distribution

75 74

BRANCHING

68 72

75 74

255

68 72

255

continuous members non-continuous members

continuous members continuous members non-continuous members non-continuous members

47 Topological array of individual rattan elements across each bespoke CNCmilled HDPE “star” element within connection node #6 48 Diagram demonstrating

continious and discontinious members running through the node

49 Steel rod and ball joint detail activated by “thigmotropism” in the generative algorithm, used in climbing and secondary environmentally responsive connections 50 Aluminum “column

hugger” collar system, utilized for securing the installation at its two primary growth “seeds”

51 Solution for the end of the

branch

CITA Complex Modelling

THE RISE

ADAPTIVE PARAMETRISATION

CITA Complex Modelling

CONNECTIONS AND END POINTS The two seed points are connected to the columns with a steel ring interface holding the flexible high-density polyethylene packing joint in place and creating a stiff fastening. Further endpoints in the form of structural shoots are fastened using pinning the ‘star-element’ joint to a gripping foot. This point connection gives support to the structure while allowing a degree of torsion. Free end points are interpreted through flowering. Like many plants in nature, the end of a growth strand culminates in blooming. Flowering is interpreted as a splitting of the tapered strut and a furling of fine counter bent bending active members.

52 Early investigations of terminating growth 53 “Flower” assembly kit 54 Assembled “flower“

55 Red Maple Blossom

THE RISE

ADAPTIVE PARAMETRISATION

CITA Complex Modelling

52 Early investigations of terminating growth 53 “Flower” assembly kit 54 Assembled “flower“

55 Red Maple Blossom

THE RISE

ADAPTIVE PARAMETRISATION

INSTALLATION

56 Zoom in, generated detailed model overlaid with 3D scan of built 57 Zoom in, generated

detailed model overlaid with 3D scan of built installation

58 Overlay of initial specification geometry and built structure

CITA Complex Modelling

The installation of The Rise took place over a period of 5 days through 4 persons. This time included preparation work on site, the cutting and labeling of all rattan strands and finally the assembly with the help of two mobile scaffolds. In order to direct the installation process, the main topology of the structure is outlined with physical ‘guide lines’ made from pre-cut 4mm rattan strands that define the exact length of each bundled strut. The ‘guide lines’ slot into a pre-drilled hole in the centre of each ‘star-element’. Where they do not perform structurally, they act as a physical measures meaning that further measurement during installation is avoided. To evaluate the design system and the ability to predict performance through the processes of integrated simulation, we 3D scan the final installation and undertake an analytic comparison between the two. In this comparison, we see that the branching nodes generally are more compressed than assumed. We expect this deviation to be caused by an imprecision in the simulation of the oppositional bending. A better understanding of the compound effect of the variable sectional elements would be necessary for better fidelity. The deviation is however assumed to be within tolerance for the installation requirements.

THE RISE

ADAPTIVE PARAMETRISATION

INSTALLATION

56 Zoom in, generated detailed model overlaid with 3D scan of built 57 Zoom in, generated

detailed model overlaid with 3D scan of built installation

58 Overlay of initial specification geometry and built structure

CITA Complex Modelling

THE RISE

ADAPTIVE PARAMETRISATION

EVALUATION

59 Co-existing of The Rise with the other installations at the ALIVE - Designing with Living Systems Exhibition at the Fondation EDF, Paris 60 Detail of the flowering

To evaluate the design system and the ability to predict performance through the processes of integrated simulation, we 3D scan the final installation and undertake an analytic comparison between the two. In this comparison, we see that the branching nodes generally are more compressed than assumed. We expect this deviation to be caused by an imprecision in the simulation of the oppositional bending. A better understanding of the compound effect of the variable sectional elements would be necessary for better fidelity. The deviation is however assumed to be within tolerance for the installation requirements.

CITA Complex Modelling

THE RISE

ADAPTIVE PARAMETRISATION

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59 Co-existing of The Rise with the other installations at the ALIVE - Designing with Living Systems Exhibition at the Fondation EDF, Paris 60 Detail of the flowering

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61 The close up to the branding of The Rise 62 Star node with branching

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The Rise examines an accumulative understanding of parametrisation. Here, the parameter space, as well as the topology of the structure, emerges across the time of the design process. By employing active bending of the rattan strands as a geometric as well as structural performance, The Rise integrates simulation of material behaviour as a core design driver. In this way, The Rise asks how material performance can become an intuitively understood and controlled part of a design space and how the circularity between design generation, analysis and taking the next design decision can be managed. The introduction of an artificial metabolism is successful in this regard. It is able to balance the many concurring demands in an continuous and autonomous way and accomplishes indeed the given design goals. However this comes with a cost: the agency for any other than macro design decisions is given to the metabolism and most importantly a human intervention during the generative process is not permitted. Similar to a microbiologist the design becomes growing many generations, observing and manipulating parameters in the environment and the DNA of the growing.

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61 The close up to the branding of The Rise 62 Star node with branching

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63 The Rise installation at

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64 Star and packing node

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The Rise demonstrates the potential for using design systems based on ideas of growth to develop working structural systems in a changing environment. It achieves this by collapsing the space between generation, simulation, analysis and feedback. The design system envisages architecture not as static and prescribed, but instead continuously adapting to the dynamics of its surroundings and its own material constraint while it grows into form. The Rise falls outside of the traditional tropes of architectural thinking. Neither a wall, beam nor cantilever, The Rise is modelled in the image of a bush. Itâ&#x20AC;&#x2122;s dense and highly complex topology is an abstract of a structure rather than an assimilation. The Rise introduces ideas of working between the scales of the material and the structure. In difference to other Complex Modelling projects, The Rise does not manipulate or design at material scale. Instead, it operates by differentiating between rattan thicknesses thereby grading performance.

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63 The Rise installation at

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REFERENCES

6 deMoncheaux, N. (2011) Spacesuit, Fashioning Apollo, Cambridge: MIT Press, p. 319

Jeronimidis, G., (2000) Structure-property relationships in biological materials in M. Elices (ed.) Structural biological materials - Design and structure-property relationships. Pergamon, Amsterdam, p. 3-16

8 Macintosh, Br, Gardiner, PF., McComas, AJ, (2006) 1. Muscle Architecture and Muscle Fiber Anatomy in Human Kinetics. Skeletal Muscle: Form and Function, Champaign, IL: p. 3–21

Tamke, M., Stasiuk, D. & Ramsgaard Thomsen, M. (2014) The Rise – Building with Fibrous Systems in F. Gramazio, M. Kohler, & S. Langenberg (eds.) Fabricate: Negotiating Design and Making. Zürich: gta-Verlag Tamke, M., Stasiuk, D. & Ramsgaard Thomsen, M. (2013) ALIVE: Designing with Aggregate Behaviour in Self-Aware Systems in C. Gengnagel, J. Nembrini, A. Kilian & F. Scheurer (eds.) Proceedings of the Design Modelling Symposium: Rethinking Prototyping, Berlin 2013. First ed. Berlin: Universität der Künste Berlin, p. 257-275

Tamke, M., Evers, H. L. & Stasiuk, D. (2013) Growing Timber Structures: Growth algorithms as an alternative approach for integrating design with constraints from materiality, tectonics and production in J. B .Obrębski & R. Tarczewski (eds.) IASS 2013 Proceedings of Symposium Beyond the Limits of Man, Wroclaw, Poland, p. 10 Tamke, M., Stasiuk, D. & Ramsgaard Thomsen, M. (2013) The Rise: Material Behaviour in Generative Design in Proceedings of the 33rd Annual Conference of the Association for Computer Aided Design in Architecture” (ACADIA). Cambridge

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Illustration by CITA Illustration by CITA Photography by CITA Illustration by CITA Illustration by CITA Photography by A. Ingvartsen Photography by A. Ingvartsen Photography by A. Ingvartsen Photography by A. Ingvartsen Photography by CITA Photography by CITA Retrieved from https://carolinahoneybees.com/red-maple-blooms/ 56 Illustration by CITA 57 Illustration by CITA 58 Illustration by CITA 59 Photography by A. Ingvartsen 60 Photography by A. Ingvartsen 61 Photography by A. Ingvartsen 62 Photography by A. Ingvartsen 63 Photography by A. Ingvartsen 64 Photography by A. Ingvartsen 44 45 46 47 48 49 50 51 52 53 54 55

5 Ball, P. (2009) Branches, Oxford University Press 2009

2 Tamke, M., Evers, H. L. & Stasiuk, D. (2013) Growing Timber Structures: Growth algorithms as an alternative approach for integrating design with constraints from materiality, tectonics and production in J. B .Obrębski & R. Tarczewski (eds.) IASS 2013 Proceedings of Symposium Beyond the Limits of Man, Wroclaw, Poland, p. 10

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Runions A., Fuhrer M., Lane B., Federl P., Rolland−Lagan A., and Prusinkiewicz P. (2005) Modeling and visualization of leaf venation patterns in ACM Transactions on Graphics 24(2005) p. 702−711

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Photography by A. Ingvartsen Photography by A. Ingvartsen Photography by A. Ingvartsen Diagram by CITA Illustration by CITA Illustration by CITA Photography by M. Ehlers Illustration by CITA Photography by A. Ingvartsen Diagram by CITA Diagram by CITA Illustration by CITA Photography by CITA Photography by CITA Photography by CITA Illustration by CITA Diagram based on publications of Dr. Alex Shigo, 1994; Gibbons, 2013 18 Retreived from http://herbtospice. com/geographical-herb/america/ america-5 19 Illustration by CITA 20 Illustration by CITA

Tamke, M., Stasiuk, D. & Ramsgaard Thomsen, M. (2013) The Rise: Material Behaviour in Generative Design in Proceedings of the 33rd Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA), Cambridge

3 Esmon, C. A., Pedmale, U., and Liscum, E. (2008) Plant tropisms: providing the power of movement to a sessile organism in The International Journal of Developmental Biology 49: p. 665-674, RIBA publications

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6 deMoncheaux, N. (2011) Spacesuit, Fashioning Apollo, Cambridge: MIT Press, p. 319

8 Macintosh, Br, Gardiner, PF., McComas, AJ, (2006) 1. Muscle Architecture and Muscle Fiber Anatomy in Human Kinetics. Skeletal Muscle: Form and Function, Champaign, IL: p. 3–21

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5 Ball, P. (2009) Branches, Oxford University Press 2009

21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43

Runions A., Fuhrer M., Lane B., Federl P., Rolland−Lagan A., and Prusinkiewicz P. (2005) Modeling and visualization of leaf venation patterns in ACM Transactions on Graphics 24(2005) p. 702−711

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Grimshaw Architects,

Departments of Architecture,

The Danish Council for

Paul Nicholas

Melbourne

Materials Science and Engineering

Independent Research

David Stasiuk

Monash University

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This project explores the design space associated with bending active structures. Bending active structures (1) use the capacity of material systems to self-organise under loading to generate three-dimensionally curved geometries from initially straight two-dimensional elements. In simulating bending active structures, emphasis is typically given to solving for material behaviour while structural topologies are kept locked and unchangeable during the simulation process. To address this limitation upon a designer’s ability to actively explore, this project develops a design space based on an open topological development that continuously synthesises top down designer-control with the bottom-up simulation of bending behaviour throughout the simulation process, without privileging one over the other. Inspiration for the modelling approach is found in nature, where birds such as the

weaverbird weave structures from continuous grasses, one element at a time. The incremental addition of elements to build the nest allows for more complex topologies and forms to emerge. This incremental process also allows for a distinctly ‘designedly’ approach, in which material can be added, its impacts considered, adjustments made, and added to again. The central component is a custom-written, verlet-integrated spring-based simulation library set up specifically to allow for collections of particles to be organized through unfixed and transitional topologies. It allows for the incremental addition of new elements over time, and for existing elements to continuously undergo reassessment of the force relationships in which they participate. In the Social Weavers, the activation of bending is used as a self-formation process. Bending-active structures (1) use the

capacity of material systems to self-organise under loading to generate three-dimensionally curved geometries from initially straight two-dimensional elements. The possible geometries are therefore limited by the physical properties of the structural elements. To gain direct experience of the bending properties associated with gfrp rod, a series of experiments and 3 point bending tests were performed on 5 different diameters of gfrp rod. The information extracted from these tests, regarding the minimum bending radius, young’s modulus and bending strength, was used to calibrate bending forces within the simulation. In addition to forces which implement “natural” material bending behaviours in the design model, the Social Weavers also relies on a series of “artificial” forces that empower the designer to more directly assert agency in a design process

that relies on unfixed topologies that undergo continuous transformation during simulation. These forces create influence on the organisation of the splines in multiple capacities: 1) for movement along the gradient of a scalar field; 2) according to a series of planar orientations, into which elements are grouped; and 3) as instruments for creating separation between elements that share these orientations. At any time during the modeling phase, the designer is capable of making adjustments to any of these forces, effectively reorienting elements or adjusting the underlying scalar field that drives the general organization of individual elements. This integrated computational process supports element self-specification during the design process. As elements are iteratively added to the simulation, their relaxation negotiates the combined natural and artificial forces. Throughout the

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VENUE

COLLABORATION

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TEAM

2013

Grimshaw Architects,

Departments of Architecture,

The Danish Council for

Paul Nicholas

Melbourne

Materials Science and Engineering

Independent Research

David Stasiuk

Monash University

SOCIAL WEAVERS

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simulation, each rod element continually updates its diameter and bending stiffness so that it is optimally sized for its loading. This opens up a very different approach to material specification: rather than assigning material pre- or post- design, specification happens simultaneous to the material self-formation within the design environment. The design and assembly of a built prototype with students at Monash University School of Architecture demonstrates the underlying modeling concepts and methodology. The non-standard grid shell demonstrator comprises 412 three-meter long fibre composite rods of five different diameters between 10mm and 2mm. The diameter, placement and orientation of rods are extracted as results from the computational process – thinner and more flexible rods in areas of greater curvature, and stiffer rods in flatter areas - to mini-

mise reaction forces. While successfully demonstrating an incremental, ‘designerly’ approach to bending active structures, and achieving a high level of shape approximation, a limit revealed in the simulation was the failure to include the effects of connections between crossing splines, which were excluded on account of computational cost.

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REFERENCES Lienhard J., Gengnagel C., Knippers J., Alpermann H. (2013) Active Bending, A Review on Structures where Bending is used as a Self-Formation Process. International Journal of Space Structures. 28. 187-196. 10.1260/0266-3511.28.3-4.187.

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Illustration by CITA Photography by CITA Diagram by CITA Photography by CITA Illustration by CITA Illustration by CITA Photography by CITA Illustration by CITA

Nicholas, P., Stasiuk, D. & Schork, T. (2014) The Social Weaver: Considering Top-down and Bottom-up design processes as a continuum. In Proceedings of the 34th Annual Conference of the Association for Computer Aided Design in Architecture: ACADIA 14 Design Agency. I. Gerber, D., Huang, A. & Sanchez, J. (eds.). Los Angeles: ACADIA, p. 497-508 12 p.

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INTEGRATED ANALYSIS The core inquiry in Complex Modelling is how design practice can integrate simulation to capture the complexity of hybrid and bespoke material systems. If we today regard material behaviour as one of the richest sources of innovation (1), we have very few means by which to formalise and thereby instrumentalise behaviour in design in order to understand the complex interactions between interdependent material systems. Simulation is one of the central means by which we can predict behaviour across the diverse scales of structure, element and material. In Complex Modelling, our interest lies with the integration of simulation across the design chain. Within this integration, simulation underlies both analytical and generative processes to evaluate and propose new design outcomes. Complex Modelling casts simulation as a key tool for a new digital-material design practice in which feedback is foregrounded. Early investigations in Complex Modelling define a conceptual dichotomy between estimative but integrated and fast lightweight simulation practice and precise but disconnected and slow heavyweight systems. The term lightweight is

rooted in computer science and describes systems employing minimal computational power. These simulations are often general in scope and can encompass a wide range of concerns in solving questions of geometry, structure, assembly and fabrication (2). Estimative simulation processes are juxtaposed by heavyweight processes that aim for high-level precision within prescribed practices. Within Complex Modelling, CITAâ&#x20AC;&#x2122;s early work composed these practices as essentially sequential. Here, lightweight projection-based methods allow for more generative processes of form finding and are followed by heavyweight finite element-based methods that validate and verify early assumptions. However, this simple dichotomy is disturbed by the creation of new simulation tools that inform projection-based strategies with explicit material values, such as Youngâ&#x20AC;&#x2122;s Modulus, and expand their capacity for capturing deformations such as torsion and sheer. Projection-based simulations and finite element analysis instead become complementary and their employment more related to the particularity of the design enquiry and the material system in question. What

emerges is a new practice in which the information model comprises multiple design-integrated simulations with varying levels of precision and different tools of calculation (2). As such, simulation is not singular, but instead recurrent with distribution occurring across the modelling environment. Integrated simulation is central to all the Complex Modelling projects. Each project prototypes or further develops particular methods that enable overall design intent to incorporate and be informed by material-scale performance. In Hybrid Tower and Isoropia, a fully integrated projection-based simulation tool is employed for both the form-finding process and the final validation and verification of design decisions (3). In Isoropia, we extend these projection-based methods through iso-geometric analysis, a NURBS-based finite element analysis tool, to calculate external forces and optimise material deployment.

INTEGRATED ANALYSIS

DATE

VENUE

COLLABORATION

SUPPORT

TEAM

2015

Danish Design Museum,

KET - Konstruktives Entwerfen und Tragwerksplanung,

The Danish Council for

Mette Ramsgaard Thomsen

2016

Copenhagen, Denmark

Udk - Universitaet der Kuenste Berlin Berlin, Germany

Independent Research,

Martin Tamke

Contextile Conference

AFF - A. Ferreira & Filhos, Guimaraes, Portugal.

COST Actions - European

Yuliya Ĺ inke Baranovskaya

2016, Guimaraes,

Fibernamics, Universidade de Minho, Guimaraes, Portugal.

Cooperation in Science and

Anders Holden Deleuran

Portugal

Essener Labor fuer Leichte Flaechentragwerke, University of Duisburg

Technology

Ida Friis Tinning Raul Fangueiro Christoph Gengnagel Riccardo La Magna Michael Schmeck Raquel Carvalho Filipa Monteiro Jorge Vieira Raquel Carvalho

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Hybrid Tower is a form of active hybrid structure that embeds bending-active glass fibre reinforced plastic rods in a bespoke tensile membrane to create a stronger whole. The project examines bending active structures as new sustainable building systems that employ material performance so as to conserve material. As an ultra-light structure, Hybrid Tower investigates two key enquiries: 1) the creation of new design methods that are able to predict the interaction between material performance in multi-material systems and 2) how we develop multiscale design strategies for material specification and the fabrication of bespoke materials. Hybrid Tower achieves its equilibrious state and stiffness through interdependency, between the bending-active glass fibre rods and the tensile membrane. In order to design Hybrid Tower, it is important to predict and understand the materi-

al behaviour of two soft material systems with contrasting rigidity and to understand the interaction between the two. The key question is therefore how to integrate the simulation of these interactions, both within early-stage form finding as well as within later-stage verification processes. These methods have been developed across two investigations. The first investigation, Hybrid Tower CPH, focuses on the creation of design workflows between the implementation of real-time physics and constraint solvers and the more time-intensive Finite Element Method, supporting design analysis and form finding respectively, and performance evaluation and verification. Here, information developed in the more lightweight form-finding process is directly interfaced with and informs the second, more heavyweight, verification process. The second process, Hybrid Tower Guimaraes, creates newly integrated methods

for calibrated modelling in which material values, such as Youngâ&#x20AC;&#x2122;s modulus, are incorporated into projection-based simulation methods, allowing us to undertake both form finding and final analysis within the same simulation environment. The central contribution of the project is the creation of methods by which to orchestrate and interface such a design workflow, which thereby determines data structures and enables feedback across high- and lowscale behaviours. Hybrid Tower occupies a multiscale design space. Here, design agency at the highend scale of the structure is interfaced with that of the material scale of the membrane. The membrane material is fabricated as bespoke knitted textiles. Knit is an interesting membrane material in that it is much more flexible and, therefore, more applicable to small-scale structures than traditional laminate weaves. By creating

direct interfaces between design and CNC fabrication, we can detail the material performance, knit to shape and integrate detailing such as channels and pockets. However, knit is also an inherently anisotropic material. This complex material behaviour creates asymmetrical performances across the textile membrane. A key parameter in Hybrid Tower is therefore to test and formalise material behaviour into values that can inform the integrated design simulation. We achieve this by creating bespoke textile testing methods by which the behaviour of our knitted materials can be predicted. Integrating the results of the textile testing back into simulation workflow creates feedback between design decisions at the lower scale and performance at the higher scale. 1 Interiour of Hybrid Tower,

Danish Design Museum, Denmark

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INTEGRATED ANALYSIS

DATE

VENUE

COLLABORATION

SUPPORT

TEAM

2015

Danish Design Museum,

KET - Konstruktives Entwerfen und Tragwerksplanung,

The Danish Council for

Mette Ramsgaard Thomsen

2016

Copenhagen, Denmark

Udk - Universitaet der Kuenste Berlin Berlin, Germany

Independent Research,

Martin Tamke

Contextile Conference

AFF - A. Ferreira & Filhos, Guimaraes, Portugal.

COST Actions - European

Yuliya Ĺ inke Baranovskaya

2016, Guimaraes,

Fibernamics, Universidade de Minho, Guimaraes, Portugal.

Cooperation in Science and

Anders Holden Deleuran

Portugal

Essener Labor fuer Leichte Flaechentragwerke, University of Duisburg

Technology

Ida Friis Tinning Raul Fangueiro Christoph Gengnagel Riccardo La Magna Michael Schmeck Raquel Carvalho Filipa Monteiro Jorge Vieira Raquel Carvalho

HYBRID TOWER

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Danish Design Museum, Denmark

CITA Complex Modelling

PROJECT

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HYBRID TOWER

INTEGRATED ANALYSIS

DESIGNING FOR RESILIENCE

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2 Early design exploration

for the tower topology

3 Shuckhov Tower, Moscow 4 Palm trees as an example of resilient structures in nature 5 Frei Otto model from

Thinking in Models (7)

CITA Complex Modelling

Hybrid Tower is a soft structure, flexible and bendable, and capable of adapting to external impact and changes in its environment. This inherent flexibility is considered a desired property of potential resilience. By building soft, Hybrid Tower stores energy when deformed elastically and releases it upon recovery. This approach allows us to minimise material usage and build ultra-light. In contrast to normative building practice, which seeks to resist deformation, Hybrid Tower absorbs forces and releases them by performing like a bow, permitting the bending action to tension and relax in tune with its environment. In Hybrid Tower, this environmental action takes place with the impact of wind load. Sited outside, in the courtyard of the Danish Design Museum and the public square of Largo do Toural, the structure is designed for impact. Hybrid Tower extends collaborative research by CITA and KET (1,2,3) to explore computational modelling of actively deforming structures and is related to the work on hybrid structures by Ahlquist and Menges (4), Lienhard (5) and Mele et al. (6).

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DESIGNING FOR RESILIENCE

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2 Early design exploration

for the tower topology

3 Shuckhov Tower, Moscow 4 Palm trees as an example of resilient structures in nature 5 Frei Otto model from

Thinking in Models (7)

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HYBRID TOWER

INTEGRATED ANALYSIS

HYBRID SYSTEM COMBINING TENSION AND COMPRESSION

tower design iteration 3 discontinous twisted loops solution

tower design iteration 4 stucking of arches with tension cables towards the middle

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tower design iteration 5 continuous vertical intercrossing arches

tower design iteration 6 stucking of arches through the lower level

6 Early-scale models

investigating interacting behaviour between tensile membrane and compressive actively 7 Close up of one of the

tower models

tower design iteration 2 stucking of arches solution

CITA Complex Modelling

tower design iteration 1 double layer solution

Hybrid Tower is a hybrid structural system that combines elements in tension and compression. Hybrid structures are defined as a combination of two or more structural concepts and materials in order to create a stronger whole (8). In contrast to prevalent form-finding approaches, which work in either tension or compression only, Hybrid Tower creates ways of simulating the interactions between tension and compression forces, which allows the methods to be transferable to other building typologies. Hybrid Tower is constructed from stacked, overlapping glass fibre reinforced plastic rods acting in bending. The rods are bent into archlike shapes using the material’s ability to be deformed elastically. Glass fibre reinforced plastics combine high Young’s modulus with high flexibility and therefore hold particular bending properties. Within Hybrid Tower, the dimension of glass fibre reinforced plastic rods is differentiated and proportioned to allow bending and accommodate further internal and external loads. The rods are connected and braced by a tensile knitted membrane made from high tenacity polyester yarn. The membrane between the rods is pulled radially towards the tower’s central axis. This results in a spoke-wheel effect, which provides horizontal stiffness and braces the rods carrying vertical loads.

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INTEGRATED ANALYSIS

HYBRID SYSTEM COMBINING TENSION AND COMPRESSION

tower design iteration 3 discontinous twisted loops solution

tower design iteration 4 stucking of arches with tension cables towards the middle

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tower design iteration 5 continuous vertical intercrossing arches

tower design iteration 6 stucking of arches through the lower level

6 Early-scale models

investigating interacting behaviour between tensile membrane and compressive actively 7 Close up of one of the

tower models

tower design iteration 2 stucking of arches solution

CITA Complex Modelling

tower design iteration 1 double layer solution

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INTEGRATED ANALYSIS

TWO INVESTIGATIONS IMPROVEMENTS BASED ON THE EXPERIENCE

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8 Hybrid Tower Guimaraes (right) compared with Hybrid Tower CPH (left) 9 Close up of a tensioned facade of the Hybrid Tower Guimaraes

CITA Complex Modelling

Hybrid Tower is developed across two investigations: Hybrid Tower CPH, designed for the Danish Design Museum, and Hybrid Tower Guimaraes, designed for the public square Largo do Toural. The first investigation develops the concept of the design workflow and the key interfacing between lightweight projection-based simulation verified by heavyweight finite element analysis. It also develops the design-to-fabrication workflow, allowing us to develop bespoke material specification. The design process is characterised by repeated physical testing and the creation of full-scale prototypes by which to ascertain relevant design parameters and performance across design scales. This allows us to develop an understanding of the defining feedback loops between specifications at material scale and design agency at structural scale. The second investigation, Hybrid Tower Guimaraes, employs this workflow but improves the integration of simulation, as well as the process of material specification. Hybrid Tower Guimaraes improves feedback and coupling between form finding and the verification process in which precise material values are incorporated to analyse performance. This allows us to interact with the design representation in real time and solve the many layers of design constraints in one integrated modelling environment. Hybrid Tower Guimaraes also consolidated the interface to fabrication, creating parametric design tools by which the bespoke knitting patterns could be generated and imported directly into the CNC knitting machine.

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TWO INVESTIGATIONS IMPROVEMENTS BASED ON THE EXPERIENCE

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8 Hybrid Tower Guimaraes (right) compared with Hybrid Tower CPH (left) 9 Close up of a tensioned facade of the Hybrid Tower Guimaraes

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INTEGRATED ANALYSIS

3 supports, 1 level input

3 supports, 1 level relaxation

3 supports, 1 level stabilisation

3 supports, 1 level settled

FORM FINDING AND VERIFICATION

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3 supports, 1 level membrane

3 supports, 1 level membrane relaxation

3 supports, 1 level membrane stabilisation

3 supports, 1 level membrane settled

3 supports,2 levels input

3 supports, 2 levels relaxation

5 supports, 2 levels input

5 supports, 3 levels input

5 supports, 3 levels relaxation

5 supports, 3 levels stabilisation

5 supports, 3 levels membrane input

5 supports, 3 levels membrane settled

In Hybrid Tower CPH, we create a handshaking interface between projection-based form finding and finite element analysis, which allows us to reduce time-intensive approaches and solve issues of simulation stability. The main form finding is undertaken using an elastic cable approach. Single-element elastic cables are connected to the initially straight rods and then a pre-tension force is applied to the cable, causing the cable to shorten in length and subsequently pull the cable ends towards one another. After the rod has been pulled to its defined curvature, the membrane is then fixed to the deformed rod and the system is released to find its equilibrium. The complexity of Hybrid Tower means that this method quickly finds its limits. The handshaking interface allows us to use lightweight projection-based methods to form find the initial shape of the rods and then import these found geometries into finite element analysis. Here, they are converted into target geometries and initial cross sections, and pre-stresses are determined. When the beam layers have converged in the finite element analysis, the meshes from the projection-based form finding are introduced as membrane surfaces. While this approach has previously been verified on simpler form-active hybrid structures (5), Hybrid Tower CPH demonstrates that we can employ these methods on complex structures with almost one hundred discrete bending beams and several hundred support targets.

10 Overview of different parameters and steps in the parametric design tool for Tower 11 Speculative design with a

minimal amount of very long bending members

CITA Complex Modelling

IN HYBRID TOWER CPH

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INTEGRATED ANALYSIS

3 supports, 1 level input

3 supports, 1 level relaxation

3 supports, 1 level stabilisation

3 supports, 1 level settled

FORM FINDING AND VERIFICATION

123

3 supports, 1 level membrane

3 supports, 1 level membrane relaxation

3 supports, 1 level membrane stabilisation

3 supports, 1 level membrane settled

3 supports,2 levels input

3 supports, 2 levels relaxation

5 supports, 2 levels input

5 supports, 3 levels input

5 supports, 3 levels relaxation

5 supports, 3 levels stabilisation

5 supports, 3 levels membrane input

5 supports, 3 levels membrane settled

10 Overview of different parameters and steps in the parametric design tool for Tower 11 Speculative design with a

minimal amount of very long bending members

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IN HYBRID TOWER CPH

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CITA Complex Modelling

INTEGRATING SIMULATION

12 Early form finding investigations into developing an interactive design tool by which key values can be tested and simulated 13 Step 1: Form finding the beams 14 Step 2: Application of

mesh and form finding of interdependent rod and membrane structure

15 Integrated simulation finds the balance between forces and material properties of skin and structure

IN HYBRID TOWER GUIMARAES In Hybrid Tower Guimaraes, a projection-based method is implemented for both the form-finding and verification processes. As part of our collaboration on the development of the K2Eng solver (9), Hybrid Tower was used as a case study by which to understand and test the requirements for simulating hybrid structures. Here, describing mechanically calibrated behaviours, including axial forces and bending moments, can be extracted and used during structural analysis feedback, allowing direct and free interaction between design generation and design analysis.

125

126

HYBRID TOWER

INTEGRATED ANALYSIS

CITA Complex Modelling

INTEGRATING SIMULATION

12 Early form finding investigations into developing an interactive design tool by which key values can be tested and simulated 13 Step 1: Form finding the beams 14 Step 2: Application of

mesh and form finding of interdependent rod and membrane structure

15 Integrated simulation finds the balance between forces and material properties of skin and structure

125

126

HYBRID TOWER

INTEGRATED ANALYSIS

EXPLORING DESIGN SPACE BOUNDARIES

127

16 Design explorations of topological variation 17 3D scan of the structural

grid of the selected early design models for the tower

CITA Complex Modelling

The boundaries of the design space were explored in a workshop examining the structural impact of topological variation. Here, the shaping of the tower, its height and radius, as well as connections and assembly, was examined. Early experiments with the asymmetrical rotational formation of bending members proved to be unfeasible because of their high bending forces. Variations in the shaping of the tower profile were evaluated with respect to structural criteria, as well as spatial intent. Here, we understand that high curvature at the base creates high stresses in the structure, so a shaping of the top structure is preferred. We also found that the splitting of the rod layer in the lower part of the structure provides an elegant way to increase strength, while maintaining slender and bendable profiles. The workshop concluded with a decision to shape Hybrid Tower CPH using eight rotationally repeated strips consisting of nine height levels. Selected form-finding experiments were prototyped in 1:4 and 1:1, which allowed for an initial testing of performance. By 3D scanning the prototypes and overlaying them onto the digital simulations, we were able to validate our methods and verify results.

128

HYBRID TOWER

INTEGRATED ANALYSIS

EXPLORING DESIGN SPACE BOUNDARIES

127

16 Design explorations of topological variation 17 3D scan of the structural

grid of the selected early design models for the tower

CITA Complex Modelling

128

CITA Complex Modelling

HYBRID TOWER

INTEGRATED ANALYSIS

18 Dynamic section drawings of the design for the Hybrid Tower Guimaraes in Portugal 19 Final design of Hybrid

129

Tower Guimaraes

130

CITA Complex Modelling

HYBRID TOWER

INTEGRATED ANALYSIS

18 Dynamic section drawings of the design for the Hybrid Tower Guimaraes in Portugal 19 Final design of Hybrid

129

Tower Guimaraes

130

HYBRID TOWER

INTEGRATED ANALYSIS

- bending members

- points for the pulling

input

springs

- pulling springs

- input geo with extra support leg

b a

- input geo with mesh

vertices

- relaxation iter 5

- relaxation iter 20

CITA Complex Modelling

- relaxation iter 80

- relaxation iter 150

- relaxation iter 200

- bending radii analysis

20 Final design model

pipeline: from the definition of the bending active rods and membrane, across form-finding and analysis to outputting developed surface geometries for fabrication

21 Hybrid Tower digital

pipeline

131

of membrane

14 - developing of the strip, iter 1

15 - developing of the strip, iter 80

16 - developing of the strip, iter 200

13 - highlighted one strip

132

HYBRID TOWER

INTEGRATED ANALYSIS

- bending members

- points for the pulling

input

springs

- pulling springs

- input geo with extra support leg

b a

- input geo with mesh

vertices

- relaxation iter 5

- relaxation iter 20

CITA Complex Modelling

- relaxation iter 80

- relaxation iter 150

- relaxation iter 200

- bending radii analysis

20 Final design model

pipeline: from the definition of the bending active rods and membrane, across form-finding and analysis to outputting developed surface geometries for fabrication

21 Hybrid Tower digital

pipeline

131

of membrane

14 - developing of the strip, iter 1

15 - developing of the strip, iter 80

16 - developing of the strip, iter 200

13 - highlighted one strip

132

KET · Tower 2.0 – iter 00 : 6 Sides, 6 Floors·

FE Simulations - first results

INTEGRATED ANALYSIS

FE Simulations - first results

Analysis after prestressing the system. Whole system with rods Ø 16mm GFRP circular section. Max von Mises Stresses (+/-) [Limit] = 250 N/mm²

HYBRID TOWER

Max von Mises Stresses (+/-) = 250N/mm2 Normal Forces [kN] Max tesion 1.3 kN Max compr. –1.3 kN

Max von Mises Stresses (+/-) [Limit] = 250 N/mm² Max stress 125 N/mm²

Loadcase: (deadload + shaping of rods + prestressing of membrane+wind)

normal forces [kN] max tension 1,3 kN max compr. -1,3 kN Max von Mises Stresses (+/-) = 250N/ mm2

KET · Tower 2.0 – iter 01 : 8 Sides, 8 Floors·

Max Stress Loadcase: 125 N/mm2

(deadload + shaping of rods + prestressing of membrane + wind)

KET · Tower 2.0 – iter 01 : 8 Sides, 8 Floors·

FE Simulations - first results

Analysis after prestressing the system. Whole system with rods Ø 16mm GFRP circular section. Normal Forces [kN]

Analysis after prestressing the system. Whole system with rods Ø 16mm GFRP circular section. Max von Mises Stresses (+/-) [Limit] = 250 N/mm²

Max von Mises Stresses (+/-) = 250N/mm2 Normal Forces [kN] Max tesion 2.7 kN Max compr. –2.3 kN

ind)

Max von Mises Stresses (+/-) [Limit] = 250 N/mm²

Loadcase: (deadload + shaping of rods + prestressing of membrane+wind)

Max stress 183 N/mm² Max Stress 183 N/mm2 Loadcase:

(deadload + shaping of rods + prestressing of membrane + wind)

KET · KET Tower· Tower 2.0 – iter : 8 Sides, Floors·8 Floors· 2.0 01 – iter 02 : 128 Sides,

KET · KET Tower· Tower 2.0 – iter 2.0 –01iter : 8 02 Sides, : 128Sides, Floors·8 Floors· normal forces [kN] max tension 2,7 kN max compr. -2,7 kN

FE Simulations - first results FE Simulations - first results

FE Simulations FE Simulations - first results - first results

Analysis after Analysis prestressing after prestressing the system.the Whole system. system Whole withsystem rods Øwith 16mm rodsGFRP Ø 16mm circular GFRP section. circular section. Normal Forces Normal [kN]Forces [kN]

Analysis after prestressing the system. the Whole system withsystem rods Øwith 16mm circular section. Analysis after prestressing system. Whole rodsGFRP Ø 16mm GFRP circular section. Max von Mises (+/-)Stresses [Limit] = 250 N/mm² Max Stresses von Mises (+/-) [Limit] = 250 N/mm²

Normal Forces Normal [kN]Forces [kN] Max tesionMax2.7tesion kN 1.1 kN Max compr.Max –2.3compr. kN -0.8 kN

embrane+wind)

Loadcase: Loadcase: (deadload +(deadload shaping of+ shaping rods + prestressing of rods + prestressing of membrane+wind) of membrane+wind)

Max von Mises Stresses (+/-) Max von Mises (+/-)Stresses [Limit] = 250 N/mm² Max Stresses von Mises (+/-) [Limit] = 250 N/mm² =Max250N/mm2 stress 183 MaxN/mm² stress 75 N/mm² Loadcase: Loadcase:

Max (deadloadStress +(deadload shaping of+ rods + prestressing of membrane wind) shaping of rods + prestressing of +membrane+wind) 165 N/mm2

normal forces [kN] max tension 2,3 kN max compr. -2,3 kN

133

estressing of membrane+wind)

A final verification of the projection-based simulation is undertaken in finite element analysis. Here, the performance of the rods and the bending action are tested along with the structural performance of the membrane. The analysis includes an extended set of properties, such as asymmetrical and varying cross-sections, pre-stressing, eccentricities, the coupling and interaction of individual components, nonlinear stress-stiffening effects, the non-linear simulation of stresses and deflections under external loads, patterning and compensation. The finite element analysis is used to proportion the rods according to the stresses in the structure. In Hybrid Tower Guimaraes, a variation of four different rod thicknesses is chosen, ranging from 8 to 14 mm. This material stratification ensures that the tower is strong enough both to support itself and withstand impact, and flexible enough to deflect dynamically.

22 Finite element analysis

of different variants of the Hybrid Tower

23 Design-integrated analysis of curvature in membrane 24 Design-integrated analysis of bending radii

CITA Complex Modelling

FINAL VERIFICATION OF PERFORMANCE

134

KET · Tower 2.0 – iter 00 : 6 Sides, 6 Floors·

FE Simulations - first results

INTEGRATED ANALYSIS

FE Simulations - first results

Analysis after prestressing the system. Whole system with rods Ø 16mm GFRP circular section. Max von Mises Stresses (+/-) [Limit] = 250 N/mm²

HYBRID TOWER

Max von Mises Stresses (+/-) = 250N/mm2 Normal Forces [kN] Max tesion 1.3 kN Max compr. –1.3 kN

Max von Mises Stresses (+/-) [Limit] = 250 N/mm² Max stress 125 N/mm²

Loadcase: (deadload + shaping of rods + prestressing of membrane+wind)

normal forces [kN] max tension 1,3 kN max compr. -1,3 kN Max von Mises Stresses (+/-) = 250N/ mm2

KET · Tower 2.0 – iter 01 : 8 Sides, 8 Floors·

Max Stress Loadcase: 125 N/mm2

(deadload + shaping of rods + prestressing of membrane + wind)

KET · Tower 2.0 – iter 01 : 8 Sides, 8 Floors·

FE Simulations - first results

Analysis after prestressing the system. Whole system with rods Ø 16mm GFRP circular section. Normal Forces [kN]

Analysis after prestressing the system. Whole system with rods Ø 16mm GFRP circular section. Max von Mises Stresses (+/-) [Limit] = 250 N/mm²

Max von Mises Stresses (+/-) = 250N/mm2 Normal Forces [kN] Max tesion 2.7 kN Max compr. –2.3 kN

ind)

Max von Mises Stresses (+/-) [Limit] = 250 N/mm²

Loadcase: (deadload + shaping of rods + prestressing of membrane+wind)

Max stress 183 N/mm² Max Stress 183 N/mm2 Loadcase:

(deadload + shaping of rods + prestressing of membrane + wind)

KET · KET Tower· Tower 2.0 – iter : 8 Sides, Floors·8 Floors· 2.0 01 – iter 02 : 128 Sides,

KET · KET Tower· Tower 2.0 – iter 2.0 –01iter : 8 02 Sides, : 128Sides, Floors·8 Floors· normal forces [kN] max tension 2,7 kN max compr. -2,7 kN

FE Simulations - first results FE Simulations - first results

FE Simulations FE Simulations - first results - first results

Normal Forces Normal [kN]Forces [kN] Max tesionMax2.7tesion kN 1.1 kN Max compr.Max –2.3compr. kN -0.8 kN

embrane+wind)

Loadcase: Loadcase: (deadload +(deadload shaping of+ shaping rods + prestressing of rods + prestressing of membrane+wind) of membrane+wind)

Max von Mises Stresses (+/-) Max von Mises (+/-)Stresses [Limit] = 250 N/mm² Max Stresses von Mises (+/-) [Limit] = 250 N/mm² =Max250N/mm2 stress 183 MaxN/mm² stress 75 N/mm² Loadcase: Loadcase:

Max (deadloadStress +(deadload shaping of+ rods + prestressing of membrane wind) shaping of rods + prestressing of +membrane+wind) 165 N/mm2

normal forces [kN] max tension 2,3 kN max compr. -2,3 kN

133

estressing of membrane+wind)

22 Finite element analysis

of different variants of the Hybrid Tower

23 Design-integrated analysis of curvature in membrane 24 Design-integrated analysis of bending radii

CITA Complex Modelling

FINAL VERIFICATION OF PERFORMANCE

134

HYBRID TOWER

INTEGRATED ANALYSIS

P h y si ca l Prototyping 6

135

B e n d i n g R a d i i A n a l y si s P a r t i cl e S p r i n g S y st e m

SIMULATION OF EXTERNAL FORCES Hybrid Tower is installed outdoors in an open environment and exposed to external forces such as wind load. The aim of designing for resilience and enabling deflection means that we need to understand the structure in its environment. Where projection-based methods are used for form finding the material system, we rely on Finite Element Analysis to understand environmental impact. Here, simulation studies suggest deflection at the top of the structure. As high-impact wind loads affect the structure, the top segments start to collapse. These behaviours are evaluated on site through the erection of a local weather station and video recordings.

FO R M FI N D I N G P a r t i cl e S p r i n g S y st e m

FE M si m u l a t i o n (external loading)

S u p e r i m p o si t i o n o f S t r e sse s

Evaluation 25 Stages of the Finite

Element Analysis Simulation setup 26 FEA-simulation

approach

Total Stress = [Residual Stress from form-finding] + [membrane pre-stress] +

P r o d u ct i o n

[dead load] +

CITA Complex Modelling

136

HYBRID TOWER

INTEGRATED ANALYSIS

P h y si ca l Prototyping 6

135

B e n d i n g R a d i i A n a l y si s P a r t i cl e S p r i n g S y st e m

FO R M FI N D I N G P a r t i cl e S p r i n g S y st e m

FE M si m u l a t i o n (external loading)

S u p e r i m p o si t i o n o f S t r e sse s

Evaluation 25 Stages of the Finite

Element Analysis Simulation setup 26 FEA-simulation

approach

Total Stress = [Residual Stress from form-finding] + [membrane pre-stress] +

P r o d u ct i o n

[dead load] +

CITA Complex Modelling

136

HYBRID TOWER

INTEGRATED ANALYSIS

A sewing seam openings

DESIGNING THE KNITTED MEMBRANE KNITTING STRUCTURE WITH THE BESPOKE BEHAVIOR

CITA Complex Modelling

piquet lacoste

tubular jersey

interlock

137

27 Knitted membrane functional material differentiation 28 Testing different knit

structures for performance: A - tubular jersey: for channels B - piquet lacoste: for strength and near isotropic behaviour C - interlock: for reinforcement

A key concern in Hybrid Tower is the integration of material performance as a design driver. While the glass fibre reinforced rods are specified in respect to pre-fabricated standards defining particular diameters and properties, the knitted membranes can be developed in direct response to application-driven design criteria (1). In Hybrid Tower, the central design tasks are to understand the requirements for the material behaviour and to create methods for knitting the bespoke membranes while, at the same time, developing means by which these can be formally tested so as to be simulated within the design system. The use of knit as a membrane material results in material requirements that knit does not usually fulfil. The material needs to be of high strength and have near-isotropic behaviour and limited elasticity for pre-tensioning. To overcome these, Hybrid Tower creates bespoke strategies for fibre and knit structure selection. Hybrid Tower also employs the knitting process as a method for shaping and detailing the textile. Where traditional laminate membranes rely on pattern-cutting and seaming, thereby incurring a large degree of waste material, and include further processes of cutting and sewing, knit is an additive process so details such as reinforcements, channels and the actual shaping of the membranes are arrived at within the material specification process.

138

HYBRID TOWER

INTEGRATED ANALYSIS

A sewing seam openings

DESIGNING THE KNITTED MEMBRANE KNITTING STRUCTURE WITH THE BESPOKE BEHAVIOR

CITA Complex Modelling

piquet lacoste

tubular jersey

interlock

137

27 Knitted membrane functional material differentiation 28 Testing different knit

structures for performance: A - tubular jersey: for channels B - piquet lacoste: for strength and near isotropic behaviour C - interlock: for reinforcement

138

HYBRID TOWER

INTEGRATED ANALYSIS

INTERFACING DESIGN SPECIFICATION

139

29 Detail of knitted channel, reinforcement and perforations for assembly 30 First test of membranes with high elasticity 31 Prototype knitting file

with embedded details for distributed rod system

32 Prototype textile patch

for distributed rod system

CITA Complex Modelling

The early test membranes are designed on first assumptions. The ability to knit with different structures, as well as different yarns, is explored to develop textiles with differentiated elasticity. Here, the assumption is that we could develop functionally graded membranes, where areas of high elasticity were juxtaposed with reinforcement areas of low elasticity. However, during testing we learned that the membrane logic of pre-tensioning meant that we needed to avoid elasticity in the membrane as pre-tensioning became too large scale and unmanageable otherwise. Early tests explored the incorporation of channels in order to insert the rods without seaming. Here, the knit structure is temporarily spliced into two single jersey textiles that are knitted on either knitting bed and then re-stitched together into a seamless membrane. Early tests also probe the pixel-based interface. Here, we work on a Stoll CNC knitting machine and develop interfaces between our 3D modelling environment and programmed pixel generator by which local specifications can be detailed. The pixel file is then read by the hardware-specific programme and interpreted as structural differentiation.

140

HYBRID TOWER

INTEGRATED ANALYSIS

INTERFACING DESIGN SPECIFICATION

139

29 Detail of knitted channel, reinforcement and perforations for assembly 30 First test of membranes with high elasticity 31 Prototype knitting file

with embedded details for distributed rod system

32 Prototype textile patch

for distributed rod system

CITA Complex Modelling

140

HYBRID TOWER

INTEGRATED ANALYSIS

Pattern

Unit Cell

In order to knit a membrane with a high degree of strength and low elasticity, we selected a high tenacity polyester yarn. The yarn has near to no elasticity, meaning that tensioning the membrane rather stretches the textile into its structural locking point, making the material behaviour easier to predict. In Hybrid Tower, we examined three knit structures for their near-isotropic behaviour: Pique Lacoste, Pique Lacoste Aff and Ponto Di Roma (Fig.36). In order to evaluate their behaviour and deduce values by which to inform design simulation, we developed a textile testing method for highly deformable textiles. The testing method takes its point of departure in the testing procedure MSAJ/M–02–1995 (Fig.35 ), and we define five different stress ratios, 1:1, 2:1, 1:2, 1:0 and 0:1, which are applied consecutively on a cruciform-shaped test piece. The result of this procedure is a stressstrain diagram (Fig.33). From this complete set of test data, ten stress-strain paths can be extracted. Theoretically, samples translate to larger fabrics directly. However, a fabric may not behave homogeneously across its entire width. When under tension, the distortion of the stitch loop varies relative to local conditions at the edge of the fabric as compared to the centre. Furthermore, small variables in machine set-up, slight changes in needle movement and tensioning can all lead to large performative changes across the fabric (10).

CITA Complex Modelling

Piquet Lacoste structure

Loop Parameters

Pique Lacoste Aff

Starts with a Jersey pattern followed by accumulation on the even needles + normal loop on the unpaired ones then switching to normal loop on the even needles and accumulation on the unpaired needles.

Pique Lacoste

Two sets of front loop on the even needles and accumulation on the unpaired ones followed by two sets of accumulation on the even loops and normal loop on the unpaired needles.

DETERMINATION OF MATERIAL PROPERTIES

Ponto Di Roma

Samples Graduation (Density of Knit)

31 37

This structure begins with a double knit (knit the front and back) followed Jersey on the front needle bed and finish with jersey on the rear needle bed.

31 37

Expected Material behaviour

Very soft, low density, low weight, good transparency, High elasticity, very anisotropic elasticity

Very soft, low density, low weight, little loss of transparency, little loss of elasticity

Higher density, low transparency, higher thickness, low elasticity

33 Stress-strain diagram 34 Bitmap files for

producing testing samples

35 Testing procedure of MSAJ/M–02–1995 36 Table of comparison

knitting structures

37 Packed samples of the various knitting structures 38 Manual measurement procedure for the stretch value of the test samples

141

Ponto Di Roma structure 142

HYBRID TOWER

INTEGRATED ANALYSIS

Pattern

Unit Cell

CITA Complex Modelling

Piquet Lacoste structure

Loop Parameters

Pique Lacoste Aff

Pique Lacoste

Two sets of front loop on the even needles and accumulation on the unpaired ones followed by two sets of accumulation on the even loops and normal loop on the unpaired needles.

DETERMINATION OF MATERIAL PROPERTIES

Ponto Di Roma

Samples Graduation (Density of Knit)

31 37

This structure begins with a double knit (knit the front and back) followed Jersey on the front needle bed and finish with jersey on the rear needle bed.

31 37

Expected Material behaviour

Very soft, low density, low weight, good transparency, High elasticity, very anisotropic elasticity

Very soft, low density, low weight, little loss of transparency, little loss of elasticity

Higher density, low transparency, higher thickness, low elasticity

33 Stress-strain diagram 34 Bitmap files for

producing testing samples

35 Testing procedure of MSAJ/M–02–1995 36 Table of comparison

knitting structures

37 Packed samples of the various knitting structures 38 Manual measurement procedure for the stretch value of the test samples

141

Ponto Di Roma structure 142

HYBRID TOWER

INTEGRATED ANALYSIS

Textile sample being produced with the bitmap on the right

CITA Complex Modelling

Close up to the pixel level of the bitmap file Bitmap file

Close up to the pixel level of the bitmap file

40 CNC Knit in Hybrid

CPH: The specification of the different knit patterns takes place in a rectangular shape with all the necessary detailing for the membranes

Tower Guimares: The knit is fully fashioned, meaning ,that besides the definition of knitting pattern and detailing, the code also specifies as well the outer shape of the membrane

39 CNC knit in Hybrid Tower

143

Bitmap file

144

HYBRID TOWER

INTEGRATED ANALYSIS

Textile sample being produced with the bitmap on the right

CITA Complex Modelling

Close up to the pixel level of the bitmap file Bitmap file

Close up to the pixel level of the bitmap file

40 CNC Knit in Hybrid

CPH: The specification of the different knit patterns takes place in a rectangular shape with all the necessary detailing for the membranes

Tower Guimares: The knit is fully fashioned, meaning ,that besides the definition of knitting pattern and detailing, the code also specifies as well the outer shape of the membrane

39 CNC knit in Hybrid Tower

143

Bitmap file

144

2.018

HYBRID TOWER

INTEGRATED ANALYSIS

Hybrid Tower develops a bespoke interface by which to translate the 3D meshes into 2D knitting specifications. Our method takes its point of departure in the elasticity of knit and the Hybrid Tower system, where the curvature of the cone is created through pre-tensioning. In our approach, we first use a weighted relaxation algorithm to transpose the length relations from 3D mesh to a 2D mesh with the same topology. The transposition includes a marking of the different kinds of edges and whether or not they align with the glass fibre reinforced rods. The 2D meshes are then automatically traced and scaled to account for the initial prestress of the membrane, the rectangular shape of the knitted loops and detailing with the placing of channels, reinforcements and tension points parametrically imposed. Finally, these are interpreted into coloured patches from which the knitting code is created. The code is visualised as pixel files in which different colours denote different stitch codes and general machine setup. The pixel files are imported into Shima Seki software, which interprets the file and runs the machine. To support communication between design and fabrication, we developed interfaces that could write the full material specification, including a window with the actual g-code, consisting of lists of A and Y strings referencing the two knitting beds. This allowed us to discuss the fabrication process with the knit technicians and troubleshoot the process.

2.018

CITA Complex Modelling

2.018

FROM 3D MESH TO BITMAP

initial input mesh

details layer

details clustered by pattern type

pixelated CNC knitting file

41 Stages of the CNC-file

generation

42 Line drawing for generating bitmap 43 Bitmap file

0.978

145

yuliyas adjustments final

146

2.018

HYBRID TOWER

INTEGRATED ANALYSIS

2.018

CITA Complex Modelling

2.018

FROM 3D MESH TO BITMAP

initial input mesh

details layer

details clustered by pattern type

pixelated CNC knitting file

41 Stages of the CNC-file

generation

42 Line drawing for generating bitmap 43 Bitmap file

0.978

145

yuliyas adjustments final

146

HYBRID TOWER

INTEGRATED ANALYSIS

initial dimensioning of the pixel file in accordance to the amount of knitting stitches

definiton of all pixels on the canvas

extraction of a+b pixels

extraction of c+d pixels

extraction of h (lace openings) and t (transfer) pixels

extraction of w (waste yarn) pixels

CITA Complex Modelling

r o w 2 6 8

initial dimensioning of the pixel file in accordance to the amount of knitting stitches

147

[a,b,c,d,w,h,t]

definiton of all pixels on the canvas

[a]

[b]

extraction of a+b pixels

[c]

[d]

extraction of c+d pixels

[h]

[t]

extraction of h (lace openings) and t (transfer) pixels

44 Stages of the CNC-file generation

[w]

extraction of w (background yarn) pixels

45 Diagram demonstrating relations between the binary code and the bitmap image

[]

148

HYBRID TOWER

INTEGRATED ANALYSIS

initial dimensioning of the pixel file in accordance to the amount of knitting stitches

definiton of all pixels on the canvas

extraction of a+b pixels

extraction of c+d pixels

extraction of h (lace openings) and t (transfer) pixels

extraction of w (waste yarn) pixels

CITA Complex Modelling

r o w 2 6 8

initial dimensioning of the pixel file in accordance to the amount of knitting stitches

147

[a,b,c,d,w,h,t]

definiton of all pixels on the canvas

[a]

[b]

extraction of a+b pixels

[c]

[d]

extraction of c+d pixels

[h]

[t]

extraction of h (lace openings) and t (transfer) pixels

44 Stages of the CNC-file generation

[w]

extraction of w (background yarn) pixels

45 Diagram demonstrating relations between the binary code and the bitmap image

[]

148

INTEGRATED ANALYSIS

HYBRID TOWER

PROTOTYPE

Isolated Tests (Details, Material) Interface to Machine Assembly Concepts

Knit / Geometry

Detailing

SCALING UP 1:1 PROTOTYPING

Assembly Process

/ 149

The design process is based on continual prototyping by which the results of the simulations are verified. The prototypes are the central means for verifying the interaction of elements and gaining insight into assembly sequence and joint systems. While early prototypes focus on the rod system, creating the high-density polyethylene joints, and use seamed-canvas test membranes, later prototypes test the accuracy of the knitted textiles, techniques, time and force required for the bending of rods and prestressing of membranes.

FE Simulation

46 Diagram, showing the

dependency of all decisions concering the demonstrator on the prototype.

47 Digital representation of the final prototype 48 Assembling the

membrane unrolled

CITA Complex Modelling

150

INTEGRATED ANALYSIS

HYBRID TOWER

PROTOTYPE

Isolated Tests (Details, Material) Interface to Machine Assembly Concepts

Knit / Geometry

Detailing

SCALING UP 1:1 PROTOTYPING

Assembly Process

/ 149

FE Simulation

46 Diagram, showing the

dependency of all decisions concering the demonstrator on the prototype.

47 Digital representation of the final prototype 48 Assembling the

membrane unrolled

CITA Complex Modelling

150

HYBRID TOWER

INTEGRATED ANALYSIS

DISCONTINUITY REINFORCED BY MECHANICAL CONNECTORS

151

49 Interior of Hybrid Tower Guimaraes 50 Deformations around the

joints in Hybrid Tower CPH

51 3d-cnc-milled h-density

polyethylene puzzle joints introduced for Hybrid Tower Guimaraes

CITA Complex Modelling

The connections between the actively bent rods are central to achieving strength in the form-found geometry. In Hybrid Tower CPH, the ambition is to use the knitted membrane as an interface between the bent rods. Instead of using mechanical clamps, we design knitted channels and pockets that hold the end of rods and transfer vertical forces. This tensegrity-like connection makes use of the inherent strength of the high tenacity fibres and the knit structure. In the demonstrator, the knit withstood the emerging forces and was not pierced. However, this textile joint has a necessarily high degree of deformation as its placement coincides with the inflection point of the rod curve. Modelling this kind of joint in finite element analysis is too complex so a fixed connection was simulated instead. In the final Hybrid Tower CPH, we experienced how the emerging forces caused difficulties in assembly, as well as escalating inaccuracies. In Hybrid Tower Guimaraes, the connection is secured with a milled high-density polyethylene puzzle joint to ensure a stiffer connection, a lesser degree of deformation and geometrical precision. The puzzle joint is attached to the rods after they have passed through the textile channels. The two parts slide towards each other and provide a solid connection between the rods. They rest on metal stoppers, which are permanently pre-fixed onto the rod in pre-defined locations and able to withstand vertical loads of up to 50kg.

152

HYBRID TOWER

INTEGRATED ANALYSIS

DISCONTINUITY REINFORCED BY MECHANICAL CONNECTORS

151

49 Interior of Hybrid Tower Guimaraes 50 Deformations around the

joints in Hybrid Tower CPH

51 3d-cnc-milled h-density

polyethylene puzzle joints introduced for Hybrid Tower Guimaraes

CITA Complex Modelling

152

INTEGRATED ANALYSIS

HYBRID TOWER

Type 1

Type 2

Type 3

top joint 2 rods connected with the joint type 3

initial assembly logic of joints

bolt connection enables axial rotation

cross joint 4 rods connected with the joint type 2

CITA Complex Modelling

deployed state of joints

other rod is stopped inside of a joint to be able to have stucking arches

stopper joint 2 rods connected with the joint type 1

closed state of joints

52 Puzzle joint connection detail for the coupling of the rods 53 Diagram of the connector

153

distribution

154

INTEGRATED ANALYSIS

HYBRID TOWER

Type 1

Type 2

Type 3

top joint 2 rods connected with the joint type 3

initial assembly logic of joints

bolt connection enables axial rotation

cross joint 4 rods connected with the joint type 2

CITA Complex Modelling

deployed state of joints

other rod is stopped inside of a joint to be able to have stucking arches

stopper joint 2 rods connected with the joint type 1

closed state of joints

52 Puzzle joint connection detail for the coupling of the rods 53 Diagram of the connector

153

distribution

154

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FABRICATION OF CUSTOM PLASTIC JOINTS

155

54 Puzzle joint parts 55 Custom fabricated highdensity polyethylene joint in puzzle configuration 56 CNC-milling process

The rods weave across the linear patches thereby connecting multiple patches and creating structural coherence. The joint system was developed so that it can be attached after the insertion of the rods in the textile membrane channels. There are two principle joint variants with the first connecting rod crossing points and the second securing end rods.

156

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INTEGRATED ANALYSIS

FABRICATION OF CUSTOM PLASTIC JOINTS

155

54 Puzzle joint parts 55 Custom fabricated highdensity polyethylene joint in puzzle configuration 56 CNC-milling process

156

HYBRID TOWER

INTEGRATED ANALYSIS

CITA Complex Modelling

Hybrid Tower Guimaraes was assembled in four days on the internal square of the Guimaraes CIAJG Museum. Here, we unrolled the textile membranes, inserted the rods and fastened the joints. Each textile patch travels diagonally up the tower and is seamed together with neighbouring patches using a Marline Hitch lacing seam in a small diameter high tenacity rope. For the final seam, the tower is rolled together and the internal tension ropes tightened.

157

57 Stopmotion of the textile

preparation, assembly and tower erection

58 The assembled membrane 59 Detail of the Marline Hitch lacing seam 60 Rolling the tower for the

final seam

61 Transporting Hybrid Tower Guimaraes to the Largo do Toural Square

INSTALLATION SEQUENCE

158

HYBRID TOWER

INTEGRATED ANALYSIS

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157

57 Stopmotion of the textile

preparation, assembly and tower erection

58 The assembled membrane 59 Detail of the Marline Hitch lacing seam 60 Rolling the tower for the

final seam

61 Transporting Hybrid Tower Guimaraes to the Largo do Toural Square

INSTALLATION SEQUENCE

158

HYBRID TOWER

INTEGRATED ANALYSIS

STR U C TU R AL MEMBRA ST RUCT NES 2015URA LBA MEMBRA RCELONA NES- OCT 2015OBER BA RCELONA 2015 - OCT O

EVALUATION

Developed Global Modelling DevelopedMethod: Global Modelling Method:

CONTEXTILE CONFERENCE 2016

• Global geometry from • Global Rhino/GH. geometry from Rhino/GH.

Hybrid Tower was evaluated for two key design criteria: the fidelity of the integrated design simulation and its ability to deform resiliently under wind load and elastically release stored energy to re-find its initial shape. The fidelity of the integrated design simulation was evaluated with respect to both the process of material testing to inform the simulation model and structural performance. The creation of new bi-axial testing methods for highly flexible textiles remains experimental. While the method of creating ‘fictitious’ elastic constants is practical and sufficient in order to predict the overall structural capacity, the finite element simulation is sensitive and difficult to set up within more interactive simulation processes. The final structural performance of the tower is evaluated through overlaying a 3D scan of the final structure onto the simulation. Here, the built Hybrid Tower Guimaraes is slightly narrower and taller than the simulated design, which is a result of an on-site decision to elongate every rod by three centimeters in order to create better prestress of the membrane patches. Finally, the tower is evaluated for deflection. In Hybrid Tower CPH, a weather station was erected on the installation site and data was correlated to two video recordings taken at 90 degrees. The 10 day evaluation measured peak winds of 11m/s which led to local damage and a kink in the shape of the tower. Monitoring showed that the tower has enough flexibility to absorb energy by bending, tensioning and bouncing back. As expected, the biggest deformation occurs at the top. While the simulated model showed deflection in only a small region, the physical demonstrator showed deflection in the entire top.

• Apply pre-tension•(reduce Apply pre-tension stiffness of tension (reducemembers/membrane stiffness of tension mem sha • Apply wind loads.• Apply wind loads. • Analyse deflections. • Analyse deflections.

159

• Superimpose FE results • Superimpose with residual FE results stresseswith fromresidual Rhino/GH. stresses from

62 3D scanning scene of

Hybrid Tower Guimaraes with and without overlay simulation

63 3D scanning scene

Tower CPH

64 Photogrammetry

monitoring of Hybrid Tower CPH

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• Check utilization.• Check utilization.

160

Ramsgaard Thomsen, et. al(2015)Ramsgaard Hybrid Tower, Thomsen, Designing et. al(2015) Soft Structures. Hybrid Tower, In Ramsgaard Designing Thomsen, Soft Structures. M., Tamke, In Ramsga M., Gengnagel, C., Scheurer, F., Faricloth, M., Gengnagel, B.. (Editor) C., Scheurer, Modelling F., Behaviour, Faricloth, B.. Springer, (Editor)Berlin Modelling Heidelberg. Behaviour, Springer, B

HYBRID TOWER

INTEGRATED ANALYSIS

STR U C TU R AL MEMBRA ST RUCT NES 2015URA LBA MEMBRA RCELONA NES- OCT 2015OBER BA RCELONA 2015 - OCT O

EVALUATION

Developed Global Modelling DevelopedMethod: Global Modelling Method:

CONTEXTILE CONFERENCE 2016

• Global geometry from • Global Rhino/GH. geometry from Rhino/GH.

159

• Superimpose FE results • Superimpose with residual FE results stresseswith fromresidual Rhino/GH. stresses from

62 3D scanning scene of

Hybrid Tower Guimaraes with and without overlay simulation

63 3D scanning scene

Tower CPH

64 Photogrammetry

monitoring of Hybrid Tower CPH

CITA Complex Modelling

• Check utilization.• Check utilization.

160

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HYBRID TOWER

INTEGRATED ANALYSIS

161

66 Tower interior. Hybrid Tower Guimaraes

65 Hybrid Tower Guimaraes

162

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INTEGRATED ANALYSIS

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66 Tower interior. Hybrid Tower Guimaraes

65 Hybrid Tower Guimaraes

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INTEGRATED ANALYSIS

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68 Steel base, Hybrid Tower Guimaraes

Hybrid Tower Guimaraes by night

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INTEGRATED ANALYSIS

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68 Steel base, Hybrid Tower Guimaraes

Hybrid Tower Guimaraes by night

164

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HYBRID TOWER

INTEGRATED ANALYSIS

165

70 Cone detail of Hybrid Tower Guimaraes

69 Hybrid Tower Guimaraes during the day

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165

70 Cone detail of Hybrid Tower Guimaraes

69 Hybrid Tower Guimaraes during the day

166

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INTEGRATED ANALYSIS

167

72 Interior space of Hybrid

Tower Guimaraes by night

71 Hybrid Tower Guimaraes by night

168

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HYBRID TOWER

INTEGRATED ANALYSIS

167

72 Interior space of Hybrid

Tower Guimaraes by night

71 Hybrid Tower Guimaraes by night

168

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HYBRID TOWER

INTEGRATED ANALYSIS

74 Cone detail with the

169

tension ropes of Hybrid Tower Guimaraes

73 Hybrid Tower Guimaraes

170

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INTEGRATED ANALYSIS

74 Cone detail with the

169

tension ropes of Hybrid Tower Guimaraes

73 Hybrid Tower Guimaraes

170

INTEGRATED ANALYSIS

HYBRID TOWER

REFERENCES Gengnagel, C. Alpermann, H. Lafuente, E. (2013) “Active Bending in Hybrid Structures”. In FORM—RULE | RULE—FORM. Innsbruck University Press, Innsbruck. pp.12–27

5 Lienhard J., (2014) Bending-Active Structures - Form-finding strategies using elastic deformation in static and kinetic systems and the structural potentials therein. ITKE, University of Stuttgart, Stuttgart, Germany

2 Quinn G., Gengnagel C., Deleuran, A. H. & Tamke M. & Evers H. & Fidjeland A. (2013), Structural Analysis and Optimisation of a Computationally Designed Plywood Gridshell in Transmaterial Aesthetics 2013 in Berlin, Germany

9 Quinn G., Deleuran A.H., Piker D., Brandt-Olsen C., Tamke M., Ramsgaard Thomsen M., Gengnagel C. (2016). Calibrated and Interactive Modelling of Form-Active Hybrid Structures in Proceedings of the 2016 Symposium of the International Association for Shell and Spatial Structures (IASS) in Tokyo, Japan

6 Mele T.V. et al., (2013) Shaping Tension Structures with Actively Bent Linear Elements in International Journal of Space Structures, 28(3), 2013, p. 127–135

10 Kyosev Y., Renkens W., (2010) Modelling and visualization of knitted fabrics. In X. Chen, Woodhead Publishing Series in Textiles, Modelling and Predicting Textile Behaviour, Woodhead Publishing, 2010, Pages 225-262, ISBN 9781845694166, https:// doi.org/10.1533/9781845697211.1.225.

Frei Otto. Thinking in Models Exhibition, ZKM, Karlruhe, Nov 2016 - Sept 2017

Alpermann H. and Gengnagel C., (2013) Restraining actively-bent structures by membranes in Proceedings of International Conference on Textile Composites and Inflatable Structures, 2013

8 Deleuran A.H, Schmeck M., Quinn G., Gengnagel C., Tamke M. Thomsen M., (2015). The Tower: Modelling, Analysis and Construction of Bending Active Tensile Membrane Hybrid Structures in Proceedings of 2015 Symposium of the International Association for Shell and Spatial Structures (IASS) in Amsterdam, The Netherlands

Ahlquist S. and Menges, A. (2013) Frameworks for Computational Design of Textile Micro-Architectures and Material Behavior in Forming Complex Force-Active Structures in Proceedings of the 33rd Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA). p. 281–292

Deleuran A., Schmeck M., Quinn G., Gengnagel C., Tamke M. Thomsen M., (2015). The Tower: Modelling, Analysis and Construction of Bending Active Tensile Membrane Hybrid Structures in Proceedings of 2015 Symposium of the International Association for Shell and Spatial Structures (IASS) in Amsterdam, The Netherlands Gengnagel, C., La Magna, R., Ramsgaard Thomsen, M., & Tamke, M. (2018). Shaping hybrids – Form finding of new material systems. International Journal of Architectural Computing, 16(2), p. 91–103 Marschall M., Schmeck M., Gengnagel C., M Thomsen M.R, Tamke M. (2016), Supporting research projects via student workshops in Proceedings of the 2016 Symposium of the International Association for Shell and Spatial Structures (IASS) in Tokyo, Japan

Ramsgaard Thomsen, M., Tamke, M., Holden Deleuran, A., Friis Tinning, I., Evers, H. L., Gengnagel, C., & Schmeck, M. (2015) Hybrid Tower, Designing Soft Structures In M. R. Thomsen, M. Tamke, C. Gengnagel, B. Faircloth, & F. Scheurer (Eds.) Modelling Behaviour: Design Modelling Symposium 2015, p. 87-99

Ramsgaard Thomsen, M., Tamke, M., Karmon, A., Underwood, J., Gengnagel, C., Stranghöner, N., & Uhlemann, J. (2016). Knit as bespoke material practice for architecture in Proceedings of the 36th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA): Posthuman Frontiers: Data, Designers, and Cognitive Machines. p. 280289

Tamke, M., Holden Deleuran, A., Gengnagel, C., Schmeck, M., Cavalho, R., Fangueiro, R., Ramsgaard Thomsen, M. (2015). Designing CNC Knit for Hybrid Membrane And Bending Active Structures in E. Oñate, K-U. Bletzinger , & B. Kröplin (Eds.), Procedings of VI International Conference on Textile Composites and Inflatable Structures: Structural Membranes 2015, p. 281-295.

Tamke, M., Baranovskaya, Y., Holden Deleuran, A., MBF Monteiro, F., Fangueiro, R., Stranghöhner, N., Ramsgaard Thomsen, M. (2016). Bespoke Materials For Bespoke Textile Architecture In K. Kawaguchi, M. Ohsaki, & T. Takeuchi (Eds.), Proceedings of IASS 2016 Tokyo Symposium: Spatial Structures in the 21st Century IASS

LIST OF PUBLICATIONS /

57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74

Photography by A.Ingvartsen Illustration by CITA Illustration by CITA Illustration by CITA Photography by CITA Photography by CITA Photography by CITA Photography by CITA Photography by CITA Photography by CITA Photography by CITA Photography by CITA Illustration by CITA Illustration by CITA Illustration by CITA Photography by A.Ingvartsen Photography by A.Ingvartsen Photography by A.Ingvartsen Photography by A.Ingvartsen Photography by A.Ingvartsen Photography by A.Ingvartsen Photography by A.Ingvartsen Photography by A.Ingvartsen Photography by A.Ingvartsen Photography by A.Ingvartsen

50 51 52 53 54 55 56

Illustration by CITA Diagram by CITA Photography by CITA Photography by CITA Illustration by CITA Photography by CITA Graph by Essener Labor fuer Leichte Flaechentragwerke, University of Duisburg 34 Diagram by CITA 35 Photography by Essener Labor fuer Leichte Flaechentragwerke, University of Duisburg 36 Diagram by CITA 37 Photography by CITA 38 Photography by CITA 39 Illustration by CITA 40 Illustration by CITA 41 Illustration by CITA 42 Illustration by CITA 43 Illustration by CITA 44 Illustration by CITA 45 Illustration by CITA 46 Diagram by CITA 47 Illustration by CITA 48 Photography by CITA 49 Photography by A.Ingvartsen 27 28 29 30 31 32 33

Photography by A.Ingvartsen Illustration by CITA Photography by N.Melikova Photography by Messala Ciulla Photography by Bernd Seeland Illustration by CITA Photography by CITA 8 Photography by CITA and A.Ingvartsen 9 Photography by A.Ingvartsen 10 Illustration by CITA 11 Illustration by CITA 12 Illustration by CITA 13 Diagram by CITA 14 Diagram by CITA 15 Illustration by CITA 16 Illustration by CITA 17 Illustration by CITA 18 Illustration by CITA 19 Illustration by CITA 20 Illustration by CITA 21 Diagram by CITA 22 Illustration by KET - UdK 23 Illustration by KET - UdK 24 Illustration by KET - UdK 25 Illustration by KET - UdK 26 Diagram by CITA 1 2 3 4 5 6 7

CITA Complex Modelling

IMAGE CREDITS

171

172

INTEGRATED ANALYSIS

HYBRID TOWER

REFERENCES Gengnagel, C. Alpermann, H. Lafuente, E. (2013) “Active Bending in Hybrid Structures”. In FORM—RULE | RULE—FORM. Innsbruck University Press, Innsbruck. pp.12–27

6 Mele T.V. et al., (2013) Shaping Tension Structures with Actively Bent Linear Elements in International Journal of Space Structures, 28(3), 2013, p. 127–135

Frei Otto. Thinking in Models Exhibition, ZKM, Karlruhe, Nov 2016 - Sept 2017

Alpermann H. and Gengnagel C., (2013) Restraining actively-bent structures by membranes in Proceedings of International Conference on Textile Composites and Inflatable Structures, 2013

LIST OF PUBLICATIONS /

57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74

50 51 52 53 54 55 56

CITA Complex Modelling

IMAGE CREDITS

171

172

INTEGRATED ANALYSIS

DATE

VENUE

COLLABORATION

SUPPORT

TEAM

2018

16th Venice Architecture

AFF - A.Ferreira & Filhos, Guimaraes, Portugal

DSM Dyneema B.v, Heerlen, The Netherlands

Mette Ramsgaard Thomsen

Filipa Monteiro

Biennale, FREESPACE

str.ucture GmbH, Stuttgart,Germany

Sika GmbH, Stuttgart, Germany

Martin Tamke

Jorge Vieira

Italy

DSM Dyneema B.V., Geleen,

TopGlass, Osnago, Italy

Yuliya Šinke Baranovskaya

André Correia

The Netherlands

Sofistik AG, Oberschleißheim, Germany

Vasiliki Fragkia

Noel Ferreira

Alurays GmbH, Munich, Germany

WK LED, Utrecht, The Netherlands

Rune Bjørnson-Langen

André Zibell

Sebastian Gatz

Dominic Sacher

Julian Lienhardt

Katrin-Sabina Freier

Riccardo La Magna

ISOROPIA

173

Isoropia is a form active hybrid structure. Designed for the 16th Venice Architecture Biennale, Isoropia expands the Hybrid Tower investigations building a site-specific structure transitioning between multiple structural states. Like a textile vault, Isoropia asks what are the architectural typologies that new material systems suggest and what are the methods for bespoke material specification and fabrication. Isoropia extends our research into knitted hybrid structures by creating a structural continuum transitioning between two different canopy structures on the two outer sides and a vaulted space in the interior. In order to morph between these states, Isoropia shifts from a cablenet system on the exteriors, which pre-stresses and stabilises the structure, to a tensegrity-like structure in the interior in which compression elements pre-stress the knitted membrane. This differentiation poses specific chal-

lenges to the form-finding and analysis process as well as to the specification and fabrication process. Isoropia - meaning balance, equilibrium and stability - is a finely tuned balance of tension and compression. The central design move is the discretisation of the structure into independent bow-like module that act autonomously while tied together into a continual structural system. Each bow-module acts as a spatial beam in which the three-dimensional cones create the depth of the beam. Each module consists of two bent glass fibre reinforced plastic beams inserted into a connecting membrane in turn pre-stressed by a cable net or a set of compression rods. The bow module is variegated across the structure, changing both the shape and width of the textile membrane as well as the length and thickness of the tube-beam thus creating a family of modules all in optima but with

differentiated structural identity, shape and expression. Isoropia occupies a multiscale design space in which performance at high scale is informed by low scale material specification. In order to realise Isoropia, we developed a bespoke customisation method for creating the textile specifications and interface with fabrication. In Hybrid Tower the rotational geometry means that all the knitted membranes are identical. This meant that the material specification interface can be solved by a merge of parametric and explicit drawing processes. In Isoropia we develop an automated process in which the mesh geometry is relaxed, resized and detailing of channels and cone centres are superimposed. Furthermore we create a strategy for functional grading of the membranes by composing patterns of differentiated stitch structures around the centre points allowing the cones to

protrude more and therefor become more three dimensional in turn augmenting the structural performance of the bow-module. Finally, Isoropia is a ultra-light resilient structure. Like Hybrid Tower, the structure is designed to deflect under environmental impact. In order to understand the structural behaviour of this deflection, we introduce a second level of design integrated simulation calculating impact and allowing feedback in the design process.

1 Interior at the Danish

Pavilion

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PROJECT

174

INTEGRATED ANALYSIS

DATE

VENUE

COLLABORATION

SUPPORT

TEAM

2018

16th Venice Architecture

AFF - A.Ferreira & Filhos, Guimaraes, Portugal

DSM Dyneema B.v, Heerlen, The Netherlands

Mette Ramsgaard Thomsen

Filipa Monteiro

Biennale, FREESPACE

str.ucture GmbH, Stuttgart,Germany

Sika GmbH, Stuttgart, Germany

Martin Tamke

Jorge Vieira

Italy

DSM Dyneema B.V., Geleen,

TopGlass, Osnago, Italy

Yuliya Šinke Baranovskaya

André Correia

The Netherlands

Sofistik AG, Oberschleißheim, Germany

Vasiliki Fragkia

Noel Ferreira

Alurays GmbH, Munich, Germany

WK LED, Utrecht, The Netherlands

Rune Bjørnson-Langen

André Zibell

Sebastian Gatz

Dominic Sacher

Julian Lienhardt

Katrin-Sabina Freier

Riccardo La Magna

ISOROPIA

173

1 Interior at the Danish

Pavilion

CITA Complex Modelling

PROJECT

174

INTEGRATED ANALYSIS

ISOROPIA

DESIGN CONCEPT

175

Isoropia is a 35 m long structure made from 41 flexible modules. The structure creates a spatial and structural continuum through the Danish Pavilion, forming differentiated outdoor canopy structures on the two outer sides and a vaulted space in the interior. The southern exterior creates a canopy structure suspended on the façade guiding visitors into the Danish Pavilion. As the structure twists into the interior then membrane is doubled and the cable net replaced by a system of pre-tensioning rods. The low space is close to the body, creating a cocooning and soft interior. Finally, again twisting out to the north façade, the structure hugs the pavilion’s classical colonnade, passing in and out between the columns in a fanlike manner. At night the structure illuminates through its integrated light sources: flexible linear LEDs alight the fibre glass beams and COB LED shine through the plexiglass pre-tensioning rods.

2 Plan drawings of Isoropia 3 Early design sketch

CITA Complex Modelling

A TRASITIONAL STRUCTURAL DESIGN

176

INTEGRATED ANALYSIS

ISOROPIA

DESIGN CONCEPT

175

2 Plan drawings of Isoropia 3 Early design sketch

CITA Complex Modelling

A TRASITIONAL STRUCTURAL DESIGN

176

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ISOROPIA

INTEGRATED ANALYSIS

THE IDEA OF A SOFT VAULT

177

4 Soft vault explorations 5 Lierne Rib Vault Structure

of Bristol Cathedral

Isoropia conceives a soft vault, a textile membrane creating intimacy, wrapping the interior space and enveloping the passer by. The lightweight structure, transparent and multi-layered suggests a new language for hybrid systems. Isoropia remains soft. Soft to the hand, tactile and smooth, itâ&#x20AC;&#x2122;s inherent pliability is accentuated as environmental impact in the form of wind loads vibrate through it. Isoropia asks what is the logic of a soft architecture.

178

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ISOROPIA

INTEGRATED ANALYSIS

THE IDEA OF A SOFT VAULT

177

4 Soft vault explorations 5 Lierne Rib Vault Structure

of Bristol Cathedral

178

ISOROPIA

INTEGRATED ANALYSIS

second skin / 8 membranes / 33.5 sq.m 315 m of Dyneema ropes

first skin / 33 membranes / 127.8 sq.m

32 supports / 64 GFRP rods 301,6m total length

cover area / 79.7 sq.m

The outdoor areas derive their shape from the mutual force interaction between the bent rods, the tensile membrane and the cable net. Support is taken through steel brackets installed on the building faรงade and tied to the colonnade. Each bracket pairs the bow-module beams in varying thickness. The bow-module are held in place by the textile membrane and cantilever outwards. In the process of form finding and structural analysis, the outdoor structure presents particular challenges due to the high nonlinearities deriving from the minimal amount of supports and mechanical constraints in the system. In the interior the bow-modules alternate in direction creating a crossing pattern. The interior is made of bending-active elements, which alternate their direction and create a crossing pattern. Here, the brackets are connected to the interior walls and the ceilings, creating a continuous support condition of the beams. Due to the forgiving boundary conditions, they are less demanding to simulate, however the complex topological arrangement presents particular challenges.

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DESIGN STRATEGY

9 6 Overview of design

strategy

7 Alternating the bow-

modules

8 Bird-viewof design simulations 9 South facade 10 North facade

180

ISOROPIA

INTEGRATED ANALYSIS

second skin / 8 membranes / 33.5 sq.m 315 m of Dyneema ropes

first skin / 33 membranes / 127.8 sq.m

32 supports / 64 GFRP rods 301,6m total length

cover area / 79.7 sq.m

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DESIGN STRATEGY

9 6 Overview of design

strategy

7 Alternating the bow-

modules

8 Bird-viewof design simulations 9 South facade 10 North facade

180

ISOROPIA

INTEGRATED ANALYSIS

DIGITAL DESIGN TOOL

181

Isoropia employs the same computational framework as Hybrid Tower that allows us to predict the interactions between the material systems. Isoropia demonstrates, that this toolset is to generic and can be applied to a structure, which is very different in its composition and performance. The design process moves through eight steps: 1) the position of the beams are defined as vector field considering the maximum fabrication width of the membranes. 2) Beams are generated in determined lengths. 3) Beam positions are defined in section and start-end locations for the textile are defined on the beams generating a membrane outline. 4) The type of membrane is indicated: double or single-sided with or without cable net. 5) Cable nets and tensioning is introduced. 6) The interior membrane is generated and compression rods are introduced and iteratively optimised in order to find an equilibrium position in the textile. 7) External constraints: anchors, external tension ropes, ceiling connections and back tension ropes are introduced. 8) Force values are applied to the goals and the overall shape is found.

11 The eight design steps 12 Plan drawing of form active hybrid structure

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COMPUTATIONAL FRAMEWORK FOR DESIGNING HYBRID KNIT STRUCTURES

182

ISOROPIA

INTEGRATED ANALYSIS

DIGITAL DESIGN TOOL

181

11 The eight design steps 12 Plan drawing of form active hybrid structure

CITA Complex Modelling

COMPUTATIONAL FRAMEWORK FOR DESIGNING HYBRID KNIT STRUCTURES

182

INTEGRATED ANALYSIS 1

ISOROPIA

INTEGRATING SIMULATION

INTERDISCIPLINARY COLLABORATION

/ 183

13 Formfinding, Kangaroo 2 14 Real time structural

feedback, Kiwi3D

15 Finite Element Analysis (wind), Sofistik

CITA Complex Modelling

Isoropia is an ultra-light structure designed to deflect on external impact such as wind loads. This resilient design conserves material by absorbing and releasing energy on impact. In order to understand the structural behaviour of the deflection we extended the digital pipeline creating a new interface to a newly developed intermediate isogeometric analysis tool (1). Here wind loads - 930 mm vertical deformation for wind suction and 640 mm vertical deformation for wind pressure â&#x20AC;&#x201C; are imposed onto the structure which is checked for failure. This workflow allows constant design feedback between design decision reflecting upon spatial intent, material performance or fabrication restraints, and environmental performance. Isogeometric analysis builds finite element analysis on nurb splines and patches. The interface between the mesh based form finding and analysis tool and the isogeometric analysis was facilitated by automating the conversion of discrete lines and surfaces into continuous spline and NURBS patches through interpolation of the nodes (2). The intermediate analysis was verified by a final robust and detailed analysis using more established finite element tools (3). In this way we could extend structural analysis to include long-term behaviour and plasticity. In order to do so, compressive springs were added in the final simulation to take into account the contact between the bending-active rods and the buildingâ&#x20AC;&#x2122;s walls.

184

INTEGRATED ANALYSIS 1

ISOROPIA

INTEGRATING SIMULATION

INTERDISCIPLINARY COLLABORATION

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13 Formfinding, Kangaroo 2 14 Real time structural

feedback, Kiwi3D

15 Finite Element Analysis (wind), Sofistik

CITA Complex Modelling

184

ISOROPIA

INTEGRATED ANALYSIS

c 17

DESIGNING THE BOW MODULE

185

16 Exploration of different bow-module morphologies 17 Diagram of the spatial

extent of the 6m beams

18 Early design

investigation of north faรงade

19 Physical models

examining the design strategy for alternating interior bow modules

CITA Complex Modelling

Learning from the complexity of Hybrid Tower, where all membranes and rods were assembled before erection creating a highly interdependent system, Isoropia develops a more tractable erection system. In Isoropia the structure is discretised in a module-based solution which allows us to complete different sections separately. The bow-module acts as an independent system in equilibrium. This avoids external counterweights that otherwise characterise tensile structures. The module is characterised by the pre-tensioning cones. In order to morph, the bow modules transition from a cablenet system on the exteriors, which pre-stresses and stabilises the structure, to a tensegrity-like structure in the interior in which compression elements pre-stress the knitted membrane. The module acts as a spatial beam in which the depth of the beam affects bending action of the tubes and improves structural performance. During the design process we learnt that the original knit structure used in Hybrid Tower was too tight resulting in a shallowing of the cones. In order to gain more depth within the module, we introduce a patterning of the membranes composing areas of higher structural extendibility around the cone centres. This allows us to tension the textile more and in turn gain more depth.

186

ISOROPIA

INTEGRATED ANALYSIS

c 17

DESIGNING THE BOW MODULE

185

16 Exploration of different bow-module morphologies 17 Diagram of the spatial

extent of the 6m beams

18 Early design

investigation of north faรงade

19 Physical models

examining the design strategy for alternating interior bow modules

CITA Complex Modelling

186

ISOROPIA

INTEGRATED ANALYSIS

DESIGNING THE BOW MODULE

The shape and performance of the bow module is determined by the 6m maximum length of the glass fibre reinforced tubes and the fixed fabrication width of the CNC knitting machine. Early design explorations examine how the detailing and shaping of this narrow strip influences performance. A special interest lies with the double membrane and the possibilities of interweaving the two membranes to find new structural hybrids of textile and compressive elements and articulate spatial depth. In order to do so we developed large scale openings in which the inner membrane passes through the outer pre-tensioned by the tension rod.

187

20 Design possibilities

within the single unit. Exploration of a single or double membrane proposals with the various cablenet layouts and membrane openings

21 Photo of the first attempt

to create a larger scale double layer membrane arch unit

22 Close up of the physical model â&#x20AC;&#x153;Fish boneâ&#x20AC;?, demonstrating a high level of surface articulation and light projections

CITA Complex Modelling

188

ISOROPIA

INTEGRATED ANALYSIS

DESIGNING THE BOW MODULE

187

20 Design possibilities

within the single unit. Exploration of a single or double membrane proposals with the various cablenet layouts and membrane openings

21 Photo of the first attempt

to create a larger scale double layer membrane arch unit

22 Close up of the physical model â&#x20AC;&#x153;Fish boneâ&#x20AC;?, demonstrating a high level of surface articulation and light projections

CITA Complex Modelling

188

INTEGRATED ANALYSIS

ISOROPIA

patch P3, selected for planarisation P3 Exteriour single layer membranes

LP0

BB 2,1751

2,1751

4,6471

Interior double layer membranes

DP15

DP14

DP13

DP12

DP11

DP10

DP9

DP8

P15

P14

P13

P12

P11

P10

C C

4,6471 4,3309

2,1751

4,6471 4,3309

2,1780

4,3309

4,6514 4,3266 1,5560

1,5560

1,5560 1,5607

EE 2D

189

P23

P22

P21

P20

P19

P18

P17

In difference to Hybrid Tower, in which a single patch design is repeated to achieve the rotational geometry, Isoropia works with mass customised patches. As the structure twists through the Danish Pavilion building morphing from canopy to vault and back again, each patch is differentiated both in size and shape as well as in the detailing of openings.

P16

LP1

P30

P29

P28

P27

P26

P25

crop compensation circles

orientation mark

crop compensation circles

orientation mark

1.630

23 Outline drawings of all patches 24 Workflow for producing

fabrication files: from 3d mesh to the planarised bitmap interface for CNC knitting

722 px

P3 P3G-code

G code

P24

4.330

1.936367

FROM THE DIGITAL MESH TO A BITMAP FOR FABRICATION

Exterior single layer membranes

4.587785

DESIGN TO FABRICATION WORKFLOW

4861 px

CITA Complex Modelling

190

INTEGRATED ANALYSIS

ISOROPIA

patch P3, selected for planarisation P3 Exteriour single layer membranes

LP0

BB 2,1751

2,1751

4,6471

Interior double layer membranes

DP15

DP14

DP13

DP12

DP11

DP10

DP9

DP8

P15

P14

P13

P12

P11

P10

C C

4,6471 4,3309

2,1751

4,6471 4,3309

2,1780

4,3309

4,6514 4,3266 1,5560

1,5560

1,5560 1,5607

EE 2D

189

P23

P22

P21

P20

P19

P18

P17

P16

LP1

P30

P29

P28

P27

P26

P25

crop compensation circles

orientation mark

crop compensation circles

orientation mark

1.630

23 Outline drawings of all patches 24 Workflow for producing

fabrication files: from 3d mesh to the planarised bitmap interface for CNC knitting

722 px

P3 P3G-code

G code

P24

4.330

1.936367

FROM THE DIGITAL MESH TO A BITMAP FOR FABRICATION

Exterior single layer membranes

4.587785

DESIGN TO FABRICATION WORKFLOW

4861 px

CITA Complex Modelling

190

INTEGRATED ANALYSIS

Bitmap file in solid fills

ISOROPIA

Bitmap file in differentiated fills PIQUET 1

used for more elastic star/like formation around the cones

PIQUET LACOSTE 2 26

1 used for the background area of a membrane, the most anisotropic performance 2

TUBULAR

CITA Complex Modelling

3 3

used for formation of the double layer channels

INTERLOCK 4

Interior patch P13

191

used for areas of reinforcement, the least stretchy zones

Interior patch P13 G-code 25

In order to fabricate the different patches, an automated system for relaxing, resizing and detailing the patches was developed. Here, the different stitch patterns changes for channels and reinforcement are placed and the details around the cone centres and the openings for securing the corners of the patches are located. The system includes a parametric patterning system in which a fourth looser stitch is used to increase the flexibility of the membranes around the cone centres.

25 Diagram of 4 main knitting structures, used in every patch of Isoropia 26 Detail of the cone 27 Transition between piquet lacost to piquet knit structure

192

INTEGRATED ANALYSIS

Bitmap file in solid fills

ISOROPIA

Bitmap file in differentiated fills PIQUET 1

used for more elastic star/like formation around the cones

PIQUET LACOSTE 2 26

1 used for the background area of a membrane, the most anisotropic performance 2

TUBULAR

CITA Complex Modelling

3 3

used for formation of the double layer channels

INTERLOCK 4

Interior patch P13

191

used for areas of reinforcement, the least stretchy zones

Interior patch P13 G-code 25

25 Diagram of 4 main knitting structures, used in every patch of Isoropia 26 Detail of the cone 27 Transition between piquet lacost to piquet knit structure

192

ISOROPIA

INTEGRATED ANALYSIS

piquet lacoste entrance to the rod channel importance of the “checker board pattern

exit from the rod channel

193

“baked“ linework arranged in layers in predefined particularcolours

28 Details of the pixel file

details

29 Typology of the linedrawings A-D 30 (next page) CNC

Fabrication files

Linedrawer type C

Linedrawer type D

four-pointed stretch zones with two pointed edge stretch zones, all top layer membranes of the interior interfacing with the ceiling

Three-pointed stretch zone, two edge patches that interface with the tension to the building to accomodate structure collapse tension forces

four-pointed stretch zones with the large openings in between, all lower membranes of the interiour

ER_D ER_D

stepping for the curved edge of the membrane

four-pointed stretch zones for the cones, all outdoor patches

ER_C ER_C

linework for the different knit structure zones distribution

The line drawer tool allows us to automate the detailing of patches and translate these into coloured surfaces in turn exported as pixel files for knit fabrication. In this was we interface with the bespoke Shima Seiki APEX3 software in which differentiated pixel colours acts as instructions for the machine. In our workflow we first impose line work placing all details and pattern change areas, then colour them in a vector based workflow and finally export as bmp files. The pixel files are imported in the Shima Seiki software and further detailed. This software is designed for easy selection methods by which colour-identified areas can be selected and automatically replaced with predefined stitch patterns. The complexity of the Isoropia patches require a high degree of freedom in the production machinery. For this a Shima Seiki M183514 14GG flat bed knitting machine was chosen. This machine enables varied down take and tensioning. Knitting with high tenacity fibres is complicated they don’t have usual tolerance of other fibres. Techniques had to be developed in order to absorb or spread tension between structures where needed and also allow a proper knitting flow whenever the knit code changes between different structures.

ER_B ER_B

CITA Complex Modelling

4px link between the “stars“

Linedrawer type B

LINEDRAWER_A LINEDRAWER_A

AUTOMATED MEMBRANE DETAILING

ER_A ER_A

exit channel should always be horizon line

Linedrawer type A

LINEDRAWER_B LINEDRAWER_B

LINE DRAWER TOOL

skip stitch small holes for the ropes

194

ISOROPIA

INTEGRATED ANALYSIS

piquet lacoste entrance to the rod channel importance of the “checker board pattern

exit from the rod channel

193

“baked“ linework arranged in layers in predefined particularcolours

28 Details of the pixel file

details

29 Typology of the linedrawings A-D 30 (next page) CNC

Fabrication files

Linedrawer type C

Linedrawer type D

four-pointed stretch zones with two pointed edge stretch zones, all top layer membranes of the interior interfacing with the ceiling

Three-pointed stretch zone, two edge patches that interface with the tension to the building to accomodate structure collapse tension forces

four-pointed stretch zones with the large openings in between, all lower membranes of the interiour

ER_D ER_D

stepping for the curved edge of the membrane

four-pointed stretch zones for the cones, all outdoor patches

ER_C ER_C

linework for the different knit structure zones distribution

ER_B ER_B

CITA Complex Modelling

4px link between the “stars“

Linedrawer type B

LINEDRAWER_A LINEDRAWER_A

AUTOMATED MEMBRANE DETAILING

ER_A ER_A

exit channel should always be horizon line

Linedrawer type A

LINEDRAWER_B LINEDRAWER_B

LINE DRAWER TOOL

skip stitch small holes for the ropes

194

195 P18 DP8

DP9 DP10 DP11

P11

DP12 DP13

P10

DP14 DP15 P19 P20 P21 P22 P23

P0 P24

P1 P25

P2 P26

P13

P3 P27

P12 P4

P28

P29

P17

Knit Fabrication Package 6

P16 Knit Fabrication Package 4

LP1 Knit Fabrication Package 3

Knit Fabrication Package 2

Knit Fabrication Package 1

ISOROPIA

LP0

Knit Fabrication Package 5

CITA Complex Modelling

INTEGRATED ANALYSIS

P30

P14

P15 P7

196

195 P18 DP8

DP9 DP10 DP11

P11

DP12 DP13

P10

DP14 DP15 P19 P20 P21 P22 P23

P0 P24

P1 P25

P2 P26

P13

P3 P27

P12 P4

P28

P29

P17

Knit Fabrication Package 6

P16 Knit Fabrication Package 4

LP1 Knit Fabrication Package 3

Knit Fabrication Package 2

Knit Fabrication Package 1

ISOROPIA

LP0

Knit Fabrication Package 5

CITA Complex Modelling

INTEGRATED ANALYSIS

P30

P14

P15 P7

196

INTEGRATED ANALYSIS 1300 mm = 662 px

1300 mm = 662 px 1300 mm = 662 px

ISOROPIA

16 1300mm = 662px 1300 mm = 662px

550

750

Fillet R 100

1300 mm = 1824 px

this one os for the "opening up" the double layer edge

1300 mm = 1824 px

Fillet R 100

875

805.30

3000mm = 4210px

875

3000mm = 4210 px

875

3000mm = 4210 px

1300 mm = 662 px

1300 mm = 662 px 40

500

300

Fillet R 100

820.54

boundary for the reinforcement pattern (interlock) Fillet R 100

boundary for the double layer channels (tubular)

1300 mm = 1824 px

1300

boundary for the fill of the membrane (piquet lacoste) G

1000

CITA Complex Modelling

AS A METHOD FOR TESTING AND EVALUATION DIGITAL TOOLS 34

197

PROTOTYPING

The process of form finding relies on the fidelity of the integrated simulation. Where structural performance is verified through finite element analysis using verified methods, the fabrication process fully relies on calibrated projection-based methods. To ensure predictability of design intent, sizing, assembly process and performance, the design to fabrication process for the bow-module typology is tested in a series of prototypes with increasing complexity. The prototypes are evaluated by calibrating the final outcome with the projection based simulation. In a final process, we 3D scan the prototypes and identify areas and reasons for deviations. We also tested for stiffness of the membranes and tautness of the cable nets.

31 Diagram of the initial

prototype

32 Detail of first generation

of pixel files

33 First patch knitted from the files 34 Prototype evaluating the

channel width in order to get a close fit to the GFRP tube

35 Thinner GFRP tubes testing same channel width

boundary for the elastic knit (piquet)

198

INTEGRATED ANALYSIS 1300 mm = 662 px

1300 mm = 662 px 1300 mm = 662 px

ISOROPIA

16 1300mm = 662px 1300 mm = 662px

550

750

Fillet R 100

1300 mm = 1824 px

this one os for the "opening up" the double layer edge

1300 mm = 1824 px

Fillet R 100

875

805.30

3000mm = 4210px

875

3000mm = 4210 px

875

3000mm = 4210 px

1300 mm = 662 px

1300 mm = 662 px 40

500

300

Fillet R 100

820.54

boundary for the reinforcement pattern (interlock) Fillet R 100

boundary for the double layer channels (tubular)

1300 mm = 1824 px

1300

boundary for the fill of the membrane (piquet lacoste) G

1000

CITA Complex Modelling

AS A METHOD FOR TESTING AND EVALUATION DIGITAL TOOLS 34

197

PROTOTYPING

31 Diagram of the initial

prototype

32 Detail of first generation

of pixel files

33 First patch knitted from the files 34 Prototype evaluating the

channel width in order to get a close fit to the GFRP tube

35 Thinner GFRP tubes testing same channel width

boundary for the elastic knit (piquet)

198

ISOROPIA

INTEGRATED ANALYSIS

CITA Complex Modelling

A central part of prototyping is to understand the aggregate behaviour of the assembled structure as well its inherent tolerance. A final test for the overall system was the fabrication and assembly of three bow-modules from one of the corner sections were prototyped to test for shaping and performance fidelity. Testing in 1:1 allowed us to examine critical parts of the bow-module system including the contact point between the glass fibre reinforced rods and the steel brackets. In order to allow for a flexible transition we reinforce the end of the tube by inserting and gluing in a stiffening steel rod. Further tests were undertaken for understanding how to integrate lighting into the installation. Here, soft silicon covered linear LEDs are strapped onto the beams directing light along the surface revealing detail and shape.

P5 P6 P7

199

36 Three single layer

patches are selected from the overall design for 1:1 scale prototyping

37 Erection of the three bow-modules 38 Three bow-modules in context of the Isoropia structure 39 Test of light integration and reflection of the differentiated knit surface

P7 36

ASSEMBLING SINGLE LAYER EXTERIOR BOW-MODULES

200

ISOROPIA

INTEGRATED ANALYSIS

CITA Complex Modelling

P5 P6 P7

199

36 Three single layer

patches are selected from the overall design for 1:1 scale prototyping

37 Erection of the three bow-modules 38 Three bow-modules in context of the Isoropia structure 39 Test of light integration and reflection of the differentiated knit surface

P7 36

ASSEMBLING SINGLE LAYER EXTERIOR BOW-MODULES

200

ISOROPIA

INTEGRATED ANALYSIS

P12

DP12

201

P12 bottomlayer with opening

DP12, top layer to the ceiling

The interior bow-modules have a greater degree of design freedom, as their two sided support to wall and ceilings makes them structurally more robust. However, the complexity of the double membrane needed careful prototyping. Here, especially the size and shape of the edge of openings needed to be determined. The openings were designed as vertical slits with a slight curvature to ensure edge stiffness. The double membrane is assembled using a knit logic. Patches are linked together using the same yarn and the same stitch logic as the patches themselves. This gives a flexible seam that behaves similar to the patch allowing for a predictable performance across the two membranes. Lighting is installed using a custom designed light fixture, which is integrated into the mount of the plexiglass compression rods. Here, COB LEDs light up the sandblasted elements. This solution articulates the depth of the structure. The double layer bow-module was tested in black yarn. The high tenacity polyester yarns can not be coloured as they do not receive die and can only be produced in white and black. However, black was deemed too austere and not well performing in light.

40 Two selected testing

patches for prototyping the double layer interior bow module

41 Erection of the double

layer prototype

42 The bow-module in context of the of Isoropia structure 43 Detail of the double layer cone detail

CITA Complex Modelling

DOUBLE LAYER INTERIOR MODULES

202

ISOROPIA

INTEGRATED ANALYSIS

P12

DP12

201

P12 bottomlayer with opening

DP12, top layer to the ceiling

40 Two selected testing

patches for prototyping the double layer interior bow module

41 Erection of the double

layer prototype

42 The bow-module in context of the of Isoropia structure 43 Detail of the double layer cone detail

CITA Complex Modelling

DOUBLE LAYER INTERIOR MODULES

202

CITA Complex Modelling

ISOROPIA

INTEGRATED ANALYSIS

CONSTRUCTION ON SITE

203

44 Photos from the construction process: preparation of the membranes, insertion of the plastic and metal details, tensioning of the membranes 45 Detail of the graded knit patterns

The on-site installation of Isoropia started with the mounting of the brackets and the preparation of textile membranes. The cone details and all cable nets were tied to the patches and the glass fibre reinforced plastic tubes were inserted on ground before being mounted on to the brackets one by one and tied together. The installation was built in three sections and the corner details connecting the sections tied together at the end.

204

CITA Complex Modelling

ISOROPIA

INTEGRATED ANALYSIS

CONSTRUCTION ON SITE

203

44 Photos from the construction process: preparation of the membranes, insertion of the plastic and metal details, tensioning of the membranes 45 Detail of the graded knit patterns

204

CITA Complex Modelling

ISOROPIA

INTEGRATED ANALYSIS

faรงade

205

47 Interiour of Isoropia at night

46 Detail Isoropia north

206

CITA Complex Modelling

ISOROPIA

INTEGRATED ANALYSIS

faรงade

205

47 Interiour of Isoropia at night

46 Detail Isoropia north

206

CITA Complex Modelling

ISOROPIA

INTEGRATED ANALYSIS

207

49 Isoropia north facade

48 Isoropia south facade

208

CITA Complex Modelling

ISOROPIA

INTEGRATED ANALYSIS

207

49 Isoropia north facade

48 Isoropia south facade

208

CITA Complex Modelling

ISOROPIA

INTEGRATED ANALYSIS

membrane

209

51 Detail of the cones

50 Detail of the double

210

CITA Complex Modelling

ISOROPIA

INTEGRATED ANALYSIS

membrane

209

51 Detail of the cones

50 Detail of the double

210

CITA Complex Modelling

ISOROPIA

INTEGRATED ANALYSIS

53 Detail of cones

52 Transitioning from canopy to vault

211

212

CITA Complex Modelling

ISOROPIA

INTEGRATED ANALYSIS

53 Detail of cones

52 Transitioning from canopy to vault

211

212

ISOROPIA

INTEGRATED ANALYSIS

213

Diagram by CITA Illustration by CITA Diagram by CITA Illustration by CITA Photography by CITA Photography by CITA Photography by CITA Illustration by CITA Photography by CITA Illustration by CITA Photography by CITA Illustration by CITA Photography by CITA Illustration by CITA Photography by CITA Photography by CITA Photography by CITA Photography by A. Ingvartsen Photography by A. Ingvartsen Photography by A. Ingvartsen Photography by A. Ingvartsen Photography by A. Ingvartsen Photography by A. Ingvartsen Photography by A. Ingvartsen Photography by A. Ingvartsen

Bauer A., & Längst P., La Magna, R., Lienhard, J., Piker D., Quinn G., Gengnagel, C., Bletzinger K. U. (2018) Exploring Software Approaches for the Design and Simulation of Bending Active Systems in Proceedings of the IASS Symposium 2018 Creativity in Structural Design MIT, Boston, USA

Lienhard, J., & La Magna, R., Bergmann, C., Runberger J. (2017) A Collaborative Model for the Design and Engineering of a Textile Hybrid Structure in Proceedings of the IASS Annual Symposium 2017 Interfaces: Architecture. Engineering . Science”, Hamburg, Germany

LIST OF PUBLICATIONS Ramsgaard Thomsen, M., Tamke, M., La Magna, R., Noel, R., Lienhard, J., Baranovskaya Y., Fragkia, V. & Längst, P. (2018) Isoropia: an Encompassing Approach for the Design, Analysis and Form-Finding of Bending-Active Textile Hybrids in Proceedings for IASS Symposium 2018: Creativity in Structural Design, Boston, USA

29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53

Photography by A. Ingvartsen Illustration by CITA Illustration by CITA Photography by CITA Photography from blog styleforum.net 6 Illustration by CITA 7 Illustration by CITA 8 Illustration by CITA 9 Illustration by CITA 10 Illustration by CITA 11 Illustration by CITA 12 Illustration by CITA 13 Illustration by CITA 14 Illustration by str.ucture 15 Illustration by str.ucture 16 Photography by CITA 17 Diagram by CITA 18 Illustration by CITA 19 Photography by CITA 20 Illustration by CITA 21 Photography by CITA 22 Photography by CITA 23 Illustration by CITA 24 Diagram by CITA 25 Diagram by CITA 26 Photography by CITA 27 Photography by CITA 28 Illustration by CITA 1 2 3 4 5

REFERENCES

Ramsgaard Thomsen M., Sinke Baranovskaya Y., Monteiro F., Lienhard J., La Magna R., Martin Tamke (2019) Systems for transformative textile structures in CNC knitted fabrics – Isoropia in TensiNet Symposium 2019 Softening the Habitats: Sustainable Innovations in Minimal Mass Structures and Lightweight Architectures, Milan, Italy

CITA Complex Modelling

IMAGE CREDITS

214

ISOROPIA

INTEGRATED ANALYSIS

213

29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53

REFERENCES

CITA Complex Modelling

IMAGE CREDITS

214

MULTI SCALE MODELLING A key interest in Complex Modelling has been to understand multiscale strategies as a framework for networked modelling. While prior chapters have outlined the establishment of modelling networks in which multiple interacting part-models interface and share information, the question remains how to conceptualise inter-model relationships. Multiscale modelling has emerged across a broad spectrum of interdisciplinary applications as a means of modelling phenomena with a high degree of complexity and where important features appear at different scales (1). In these cases, it is not tractable to model and simulate within one unified model or at one unified level of resolution. Multiscale modelling develops coupling and interfacing methods that enable models to be informed and parameterised by models at other scales. In this way, the modelling process benefits from the higher-level abstractions, assumptions and generalisations of macro-scale models, as well as from the detail and accuracy of micro-scale models (2). Complex Modelling links multiscale modelling to architecture at the defined scales of the structure, the element and the material. The modelling framework is

used in highly strategic and tailored ways. Models are often multifarious, meaning that there are multiple models at each level. Each project defines the number and nature of models at each scale, as well as their levels of resolution and accuracy. Networks of models can be arranged sequentially or in parallel with feedback travelling up or down stream through the scales of design agency. What is arrived at is a design practice defined by fundamental bi-directional dependencies in which behaviour steers design and design steers behaviour. A central enquiry is the concept of handshakes. Handshakes are the interfaces for information transfer between models. In Complex Modelling, we examine the role of geometry as a communicative substrate to support handshaking and information transfer. Here, we employ mesh-based methods. We investigate both nested strategies, in which fine discretizations are uniformly correlated with coarse discretizations, as well as adaptive strategies that support more tactical and non-uniform discretizations. These adaptive strategies combine different resolutions within a single mesh so that areas of high complexity are associated with

locally refined discretizations. Complex Modelling creates dynamic processes for refining and coarsening meshes, and thereby information, enabling direct interfaces between design agency at different scales (2). The paradigm of multiscale modelling breaks down the traditional architectural modelling boundaries, allowing us to expand concern into the actual design and fabrication of materials. In Stressed Skin, multiscale modelling is used to create a bridge between macro-structural analysis, the generation of rigidisation patterns and the prediction of material properties. In PCM Faรงade, the thermodynamic focus on structure, element and material is expanded to include the scales of site, as well as micro- and macroclimate.

MULTI SCALE MODELLING

DATE

LOCATION

COLLABORATION

SUPPORT

TEAM

2015

Design Museum

DTU Mechanik

The Danish Council for Independent Research

Paul Nicholas

Zelina Asya Ilgun

David Stasiuk

Giselle Bouron

Esben Clausen Nørgaard

Katre Laura

Niels Bay (DTU)

Ana Goidea

Chris Hutchinson (Monash

Rafael Koelmel

Materials Science)

Magdalena Haslinger

Denmark, København

Clemens Preisinger, Rober Verlinger

STRESSED SKINS

225

Stressed Skins is an asymmetric tunnel structure installed at the Danish Design Museum in May 2015. The structure is made of 186 unique planar, pentagonal panels arranged into an inner and outer skin, and cantilevers at one end. The project explores the architectural and structural potentials of thin skin metallic structures - how very thin, easily bent metal sheet can become strong through geometric and material manipulation. We develop modelling and robotic fabrication workflows to support customised design and fabrication of a stressed skin structure. Stressed skins are a structural hybrid - an intermediate between a monocoque and a rigid frame - that utilize the capacity of a thin skin to transmit tensile, compressive and shear loads. This structural activation of the skin makes stressed skin structures strong and light weight compared to conventional framed construction approaches. This

project finds inspiration in the development of stressed skins within aviation, the geometric strategies for increasing rigidity implemented in Junkers’ early experimental wing structures and aeroplane bodies, as well as the trajectories of architectural and structural opportunity initialized by Prouve’s folded sheet metal construction, LeRicolais’ structural elements and Junkers’ experimental metal housing. Stressed Skins places particular focus on predicting and incorporating material properties into design development. The project explores how an initially standardized and homogenous sheet of thin metal can gain strength and be made heterogeneous as a result of working and out of plane rigidisation. The geometry of rigidisation patterns, as well as other details, is generated computationally and fabricated through a Robotic process which allows the forming of locally customised geome-

tries beyond those achievable via conventional rolling or stamping approaches. As the steel is formed, there is an increase in surface area, and a corresponding local thinning of the material. From a forming perspective, it is important to calculate this change in geometric thickness so that the material does not tear or buckle as the thickness approaches zero. The process of forming also activates work hardening, with the effect of locally raising the yield strength of the steel. At an extreme, the yield strength can be almost doubled, while material thickness can reduce to zero. These small scale operations can have significant impact on large scale behavior. To incorporate the implications of fabrication-based material transformation into the design phase, StressSkins develops an inter-scale modelling approach with three defined scales of structure, panel and ma-

terial. An adaptive mesh-based approach is used to communicate information between these scales. There are two established mesh-based methods for adapting resolution where required to capture complex dynamics, small scale geometry and scale sensitive calculations: the nesting of structured grids (multiple contiguous domains) and the adaptation of a non-structured grid (a single continuous domain). This project develops the second of these strategies and deploys a single, continuous-domain multi-scale mesh to negotiate form-finding, analysis, fabrication and representation.

1 Stressed Skin at the Danish

Design Museum, 2015

CITA Complex Modelling

PROJECT

226

MULTI SCALE MODELLING

DATE

LOCATION

COLLABORATION

SUPPORT

TEAM

2015

Design Museum

DTU Mechanik

The Danish Council for Independent Research

Paul Nicholas

Zelina Asya Ilgun

David Stasiuk

Giselle Bouron

Esben Clausen Nørgaard

Katre Laura

Niels Bay (DTU)

Ana Goidea

Chris Hutchinson (Monash

Rafael Koelmel

Materials Science)

Magdalena Haslinger

Denmark, København

Clemens Preisinger, Rober Verlinger

STRESSED SKINS

225

1 Stressed Skin at the Danish

Design Museum, 2015

CITA Complex Modelling

PROJECT

226

STRESSED SKINS

MULTI SCALE MODELLING

time `= 1.23402E * 01 fringes of shell thickness min = 5.568E-01 in element 27870 max = 9.913E-01 in element 41139 integration point * 1

fringes levels 7.500E - 01 7.670E - 01

7.840E - 01 8.010E - 01 8.180E - 01 8.350E - 01 8.520E - 01 7

8.690E - 01 8.860E - 01 9.030E - 01

ROBOTIC INCREMENTAL SHEET FORMING

227

2 Interdum et malesuada

fames ac ante ipsum

3 Interdum et malesuada

fames ac ante ipsum

STATE OF THE ART

4 Interdum et malesuada fames ac ante ipsum elit

The project uses a Robotic Incremental Sheet Forming (RSIF) process to fabricate and rigidise an architectural stressed skin structure. A manipulative process for imparting 3D form onto thin metal sheet through highly localised plastic deformation, RISF differs from deep drawing and other common sheet metal forming techniques in that the final shape of the piece is fully determined by the movement of a simple tool moving continuously over the surface of the sheet (2). RISF extends the flexible Incremental Sheet Forming (ISF) manufacturing process first developed in Japan in the 1980s and 1990s (1).

5 Interdum et malesuada

fames ac ante ipsum elit

6 Interdum et malesuada

fames ac ante ipsum elit

7 Interdum et malesuada

fames ac ante ipsum elit

8 Tin can regidised rib structure 9 Interdum et malesuada fames ac ante ipsum elit 10 Interdum et malesuada fames ac ante ipsum elit

CITA Complex Modelling

228

STRESSED SKINS

MULTI SCALE MODELLING

time `= 1.23402E * 01 fringes of shell thickness min = 5.568E-01 in element 27870 max = 9.913E-01 in element 41139 integration point * 1

fringes levels 7.500E - 01 7.670E - 01

7.840E - 01 8.010E - 01 8.180E - 01 8.350E - 01 8.520E - 01 7

8.690E - 01 8.860E - 01 9.030E - 01

ROBOTIC INCREMENTAL SHEET FORMING

227

2 Interdum et malesuada

fames ac ante ipsum

3 Interdum et malesuada

fames ac ante ipsum

STATE OF THE ART

4 Interdum et malesuada fames ac ante ipsum elit

5 Interdum et malesuada

fames ac ante ipsum elit

6 Interdum et malesuada

fames ac ante ipsum elit

7 Interdum et malesuada

fames ac ante ipsum elit

8 Tin can regidised rib structure 9 Interdum et malesuada fames ac ante ipsum elit 10 Interdum et malesuada fames ac ante ipsum elit

CITA Complex Modelling

228

MULTI SCALE MODELLING

Low strength steels (<180 MPa)

STRESSED SKINS

Ultra-high-strength steels ( > 550 MPa)

High-strength steels

Elongation ( % )

Conventional high-strength steels

Mild

Advanced highstrength steels

IS BH

CMn

20 10

TRIP HSL

DP ,C

MART

0 0

200

400

600 Yield Strength (MPa)

1300 12

FORAYS INTO FORMING

EXPERIMENTS AT DTU MECHANIK

Initial experiments investigate two alternative metal forming methods. The first uses a pneumatic hammering tool, where force and deformation is generated via the stroke of the tool tip. The second method, a single-point pressing approach that utilizes the robot armâ&#x20AC;&#x2122;s capacity to impart force, was developed through access to and experience of the ISF-designated CNC setup at DTU Mekanik. Distinctly different surface qualities are associated with each approach and emerge from varying the speed of the tool and the spacing of the toolpaths.

229

1000

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CITA Complex Modelling

800

230

MULTI SCALE MODELLING

Low strength steels (<180 MPa)

STRESSED SKINS

Ultra-high-strength steels ( > 550 MPa)

High-strength steels

Elongation ( % )

Conventional high-strength steels

Mild

Advanced highstrength steels

IS BH

CMn

20 10

TRIP HSL

DP ,C

MART

0 0

200

400

600 Yield Strength (MPa)

1300 12

FORAYS INTO FORMING

EXPERIMENTS AT DTU MECHANIK

229

1000

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CITA Complex Modelling

800

230

MULTI SCALE MODELLING

partial model

STRESSED SKINS

partial model

MACRO Global Configuration

INTERSCALAR RELATIONS NUNC AT MAXIMUS NISI, VITAE

231

One of the main problems in the design of stressed skin structures is to ensure rigidity against buckling of the parts which have to carry compressive load. The modelling approach is developed from the need to address buckling at each of these scales: buckling of the structure, buckling within panel elements, and buckling and tearing that can occur during the sheet forming process itself. In addition, the macro scale incorporates the resolution of global design goals, overall geometric configurations, a full-scale understanding of structural performance and discretization, and is informed by the available scale of production. The meso scale considers the project at an assembly and sub-assembly level, and is concerned with material behaviors tied to geometric transformation, detailing and compoÂŹnent-level tectonic expression. The micro scale is concerned with relevant material characteristics at the most discretized level. In connecting these scales together, the modelling framework is able to consider macro, meso and micro scales as markers along a continuum describing variable, interdependent functionalities within the design system.

MESO Tectonics Assembly & Detail

MICRO Local Material Behaviours & Properties 15 Interdum et malesuada fames ac ante ipsum elit 16 Interdum et malesuada fames ac ante ipsum elit 17 Interdum et malesuada

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CITA Complex Modelling

partial model

232

MULTI SCALE MODELLING

partial model

STRESSED SKINS

partial model

MACRO Global Configuration

INTERSCALAR RELATIONS NUNC AT MAXIMUS NISI, VITAE

231

MESO Tectonics Assembly & Detail

MICRO Local Material Behaviours & Properties 15 Interdum et malesuada fames ac ante ipsum elit 16 Interdum et malesuada fames ac ante ipsum elit 17 Interdum et malesuada

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CITA Complex Modelling

partial model

232

STRESSED SKINS

MULTI SCALE MODELLING

Additional resolution where complex dynamics are occuring

HALF-EDGE MESH APPROACH NUNC AT MAXIMUS NISI, VITAE

233

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CITA Complex Modelling

A central investigation in the project is to use a mesh as a substrate for enacting and communicating various types of analysis across multiple scales, to support geometric specification, structural simulation and production of fabrication data. The basis of the approach is a half-edge (or directed-edge) mesh data structure. The half-edge mesh data structure is particularly well suited for geometry development and model traversal. Half-edge mesh data structures allow for the efficient topological reading and transformation of mesh objects, and the remeshing processes that are central to a multi-scalar modelling approach. The sequential increase in resolution is shown in Figure 7. Initial increases in resolution are achieved through node insertions related to specific geometries, and later refinements by Loop subdivision (3). The refinement of the mesh maintains anchored nodes, seams and creases as they are established at different levels of resolution.

234

STRESSED SKINS

MULTI SCALE MODELLING

Additional resolution where complex dynamics are occuring

HALF-EDGE MESH APPROACH NUNC AT MAXIMUS NISI, VITAE

233

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CITA Complex Modelling

234

CITA Complex Modelling

STRESSED SKINS

MULTI SCALE MODELLING

FORMING EXPERIMENTS LOREM IPSUM DOLOR SIT AMET

235

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236

CITA Complex Modelling

STRESSED SKINS

MULTI SCALE MODELLING

FORMING EXPERIMENTS LOREM IPSUM DOLOR SIT AMET

235

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STRESSED SKINS

MULTI SCALE MODELLING

26 29

237

SUBTITLE 27

128

The meshing strategy focusses on incrementally refining subdivisions so that one mesh can support understandings of coarser topological relationships between individual panels, granular understandings of local material behaviors, and refined geometries for defining digital fabrication drivers and toolpaths. Half-edge meshes enable the deployment of N-gon faces (rather than more standard triangulated or quadrilatÂŹeral faces). This opens up the possibility for designing with more complex topologies, and for sequential increases in resolution across the design process. Initial modelling investigations test the combination of half-edge meshing approaches with tools for form finding. These experiments revealed that half-edge meshes enable data from the form-finding solver and the mesh topology to be coordinated as a unified data structure.

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CITA Complex Modelling

MESHING EXPERIMENTS

238

STRESSED SKINS

MULTI SCALE MODELLING

26 29

237

SUBTITLE 27

128

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CITA Complex Modelling

MESHING EXPERIMENTS

238

STRESSED SKINS

MULTI SCALE MODELLING

GENERATIVE MODEL Open double-skin half edge mesh REACTION DIFFUSION PATTERNING Open single-skin half-edge mesh face memory & feature retainment

MODELLING PROCESS

INITIAL FE Probe connectors between skins REFINED FE Final connectors between skins

CITA Complex Modelling

SUBTITLE

239 J

The modelling process begins with the definition of a target surface, designed in response to the spatial opportunities and constraints of the installation site. A generative model grows two panelised skins off this surface through the sequential addition of pentagonal panels spiraling outward from a seed tile. The shape and configuration of panels are defined through a recursive form-finding process that includes edge length and angle goals, goals that pull towards the target mesh, vertex repelling goals between panel seams on the upper and lower skins and goals that neither skin collide with the other. As each new panel is located in the assembly, the solver reconciles these geometrically competing interests into a configuration that retains the topology of the tiling strategy but minimally adapts its emerging form to approximate the target surface. After the target surfaces are fully tiled, a planarising goal is applied to the panels.

DEPTH MODULATION PANELISATION MODEL 32 Interdum et malesuada

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Iso-cut along reaction diffusion & final interskin connectors split at panelborders

Iso-cut along reaction diffusion & final interskin connectors split at panelborders pattern depth adjusted according to locally recursive processing of utilisation

INTERIOR SKIN FABRICATION MODEL Utilisation-driven dimpling subdivision refinement

EXTERIOR SKIN FABRICATION MODEL Utilisation-driven dimpling subdivision refinement

QUAD REMESHING Locally adaptive subdivision geometric strain calculations

MICROSCOPY READINGS Assignment of hardening from material observations

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Direct Topology Scalar Transformation â&#x20AC;&#x153;Handshakeâ&#x20AC;&#x153; driven Scalar Transformation

PANELISATION MODEL Open double-skin half edge mesh interstitial faces between panels

240

STRESSED SKINS

MULTI SCALE MODELLING

GENERATIVE MODEL Open double-skin half edge mesh REACTION DIFFUSION PATTERNING Open single-skin half-edge mesh face memory & feature retainment

MODELLING PROCESS

INITIAL FE Probe connectors between skins REFINED FE Final connectors between skins

CITA Complex Modelling

SUBTITLE

239 J

DEPTH MODULATION PANELISATION MODEL 32 Interdum et malesuada

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Iso-cut along reaction diffusion & final interskin connectors split at panelborders

Iso-cut along reaction diffusion & final interskin connectors split at panelborders pattern depth adjusted according to locally recursive processing of utilisation

INTERIOR SKIN FABRICATION MODEL Utilisation-driven dimpling subdivision refinement

EXTERIOR SKIN FABRICATION MODEL Utilisation-driven dimpling subdivision refinement

QUAD REMESHING Locally adaptive subdivision geometric strain calculations

MICROSCOPY READINGS Assignment of hardening from material observations

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Direct Topology Scalar Transformation â&#x20AC;&#x153;Handshakeâ&#x20AC;&#x153; driven Scalar Transformation

PANELISATION MODEL Open double-skin half edge mesh interstitial faces between panels

240

STRESSED SKINS

MULTI SCALE MODELLING

maximum deviation: 0.565 m average deviation: 0.123 m utilisation of possible connection locations: 0 %

maximum deviation: 0.232 m average deviation: 0.028 m utilisation of possible connection locations: 20 %

SUBTITLE maximum deviation: 0.165 m average deviation: 0.021 m utilisation of possible connection locations: 40 %

maximum deviation: 0.078 m average deviation: 0.016 m utilisation of possible connection locations: 80 %

241

maximum deviation: 0.095m average deviation: 0.017 m utilisation of possible connection locations: 60 %

Connectivity is established through a panelisation process. The pentagonal mesh is hybridised to incorporate panel offsets and new connective faces introduced to define the connection detail between panels on the same skin. “Shared territories” are identified between proximate panels on the lower and upper skins, and “feelers” distributed within each shared territory identify proximate feelers from panels on the opposite skin. The most central, or average, connection point in each territory is established as a single “probe connection”, with each panel - where possible - having at least three and up to five connections. New connective faces integrate connections into the mesh as coarse conical geometries, supporting a structural analysis to determine nodal translations, rotations, utilization of bending forces and also readings of shear forces at each connection point.

maximum deviation: 0.073 m average deviation: 0.014 m utilisation of possible connection locations: 100 %

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CITA Complex Modelling

STRUCTURAL CONNECTIVITY

242

STRESSED SKINS

MULTI SCALE MODELLING

maximum deviation: 0.565 m average deviation: 0.123 m utilisation of possible connection locations: 0 %

maximum deviation: 0.232 m average deviation: 0.028 m utilisation of possible connection locations: 20 %

SUBTITLE maximum deviation: 0.165 m average deviation: 0.021 m utilisation of possible connection locations: 40 %

maximum deviation: 0.078 m average deviation: 0.016 m utilisation of possible connection locations: 80 %

241

maximum deviation: 0.095m average deviation: 0.017 m utilisation of possible connection locations: 60 %

maximum deviation: 0.073 m average deviation: 0.014 m utilisation of possible connection locations: 100 %

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CITA Complex Modelling

STRUCTURAL CONNECTIVITY

242

STRESSED SKINS

MULTI SCALE MODELLING

Multi-scale Adaptive Quad Mesh

Strain Hardening Material Parametrisation

RIGIDISATION PATTERN

FEA

Connection / Rotation / Translation

Pattern Transformation

Local Utilisation

Accumulation of Incremental Pattern Depth from Baseline

Baseline Connection Geometry Iter 1 - 3

REACTION DIFFUSION FOR STABILITY

After Iter 3 Iter 4 - 14

After Iter 14

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0.16 0.15

0.00023

0.00016 0.00010

0.14 0.13 0.12

243

Panel Performance by iteration

0.17

0.00005 39

0.18

10mm Total Bending Energy (nKm)

0mm

Average Utilisation

CITA Complex Modelling

Localised rigidisation â&#x20AC;&#x201C; the creation of a three dimensional pattern - gives thin metal sheet greater bending stiffness. The patterning strategy on the upper skin is achieved using a Gray-Scott reaction-diffusion algorithm. This is executed on a higher-resolution, topologically persistent triangulated subdivision of the original generative pentagonal tile mesh, and informed with fixed vertex locations for connection elements that later enable the instantiation of precise connection geometries. The subdivision technique allows for newly introduced features to inherit key data elements during both decimation and subdivision. The mesh was then further discretised according to a surface-level iso cut, which split faces along edges according to the reaction-diffusion U and V ingredient parameters at each vertex. The areas inside the iso surface were considered formable. The goal here is to produce a pattern on the upper surface whose isotropic nature assists in stiffening panels without favouring any particular directionality, and which takes advantage of geometries not achievable via rolling and stamping.

244

STRESSED SKINS

MULTI SCALE MODELLING

Multi-scale Adaptive Quad Mesh

Strain Hardening Material Parametrisation

RIGIDISATION PATTERN

FEA

Connection / Rotation / Translation

Pattern Transformation

Local Utilisation

Accumulation of Incremental Pattern Depth from Baseline

Baseline Connection Geometry Iter 1 - 3

REACTION DIFFUSION FOR STABILITY

After Iter 3 Iter 4 - 14

After Iter 14

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0.16 0.15

0.00023

0.00016 0.00010

0.14 0.13 0.12

243

Panel Performance by iteration

0.17

0.00005 39

0.18

10mm Total Bending Energy (nKm)

0mm

Average Utilisation

CITA Complex Modelling

244

STRESSED SKINS

MULTI SCALE MODELLING

MODELLING STRAINS CIRCLE PROJECTION METHOD FOR PREDICTING STRAINS

245

After deformation

Before deformation ( 4;1 )

( 1;1 )

4 ( 0;0 )

3 2 ( 4; -1 )

y ( 5; 0 )

( 0;0 )

( 2;0 )

2 ( 1; -1 )

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CITA Complex Modelling

At the smallest scale, a circle projection method is used to predict strains and material thinning. A circle is inscribed into an initial mesh face on a flat, un-deformed sheet, and then projected onto a corresponding deformed sheet. The vertices for each quad face are projected to the target geometry, and the face is tested for planarity. If the face is within a set tolerance, it remains at its current resolution. If it is not, it subdivides into four faces. This test is recursively applied to the mesh such that it locally adapts its resolution to relevant geometric features. After several iterations, each quad can be understood both in its initial unformed square state on the starting plane, and in its strained quad state resulting from geometric forming. A circle inscribed in the initial square is then projected onto the deformed quad, resulting in an ellipse whose primary and secondary axes produce both direction and lengths of strains resulting from the forming process.

246

STRESSED SKINS

MULTI SCALE MODELLING

MODELLING STRAINS CIRCLE PROJECTION METHOD FOR PREDICTING STRAINS

245

After deformation

Before deformation ( 4;1 )

( 1;1 )

4 ( 0;0 )

3 2 ( 4; -1 )

y ( 5; 0 )

( 0;0 )

( 2;0 )

2 ( 1; -1 )

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CITA Complex Modelling

246

MULTI SCALE MODELLING B

STRESSED SKINS

200 MPa

247

350 MPa

SUBTITLE Given a geometry to be formed, the predictive model calculates the strains that will be induced by the forming process. These strains are then combined with a material model gained from empirical testing (Vickers hardness testing and optical microscopy to predict resultant material thickness and yield strength. To determine this model, a series of samples using different materials and thicknesses are produced using the same rig as for final production. Empirical tests systematically vary tool speed, feature angle, and step size between tool targets. The tool speed and angle determine the strain-rate of the deformation process, which is known to directly correspond to the strain hardening of metal.

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500 MPa

CITA Complex Modelling

CALIBRATING THE MODEL

248

MULTI SCALE MODELLING B

STRESSED SKINS

200 MPa

247

350 MPa

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500 MPa

CITA Complex Modelling

CALIBRATING THE MODEL

248

MULTI SCALE MODELLING

(a) Sample position.

STRESSED SKINS

technique: pressing

sample1 1 Sample

(b) Adjust the focus of the optical lens.

sample22 Sample

sample33 Sample

Figure 1: Experiment setup before hardness test.

S20 S20 S20 After the the S20 real-time image is in focus, onto the sample sur <50 <5050 the diamond indenter is slowly lowered 50 pressed into the surface shape indent on the surfac S40 S65 S40 S40 with a load of 0.1kN (Figure S65 2a), leaving a diamond S40 <35 35 diagonals of<35 the diamond are then measured (in µm, Figure 2b) and the Vickers hardness is calculate <3535 35 S65 S65 S65 S65 formula below (F is in kN and d1 , d2 are in mm). <1515 <15 15 1.8544 × F F ≈ HV = d1 d2 A 48

technique: hammering

sample 4

sample 5 S30 S20 45

S: speed angle

(a) Indenter is lowered onto the sample.

Figure 2: Experiment setup during and after indentation.

MICROSCOPY

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Location 1 10x ps

Location 1 20x ps

Location 2 10x ps

Location 2 20x ps

Location 3 10x ps

Location 3 20x ps

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OPTICAL MICROGRAPHS OF THE INCREMENTALLY FORMED METAL SHEETS The local increase in flow strength that results from the tooling process is measured using Vickers hardness tests with a 5kg load measured along the cross sectional thickness of the formed sheet. Flow strength is the yield strength of the metal as a function of strain, and describes the point at which the material enters plastic deformation. Visual monitoring of the grains at the same points is achieved using optical microscopy. The resulting hardnesses are converted to predicted flow stresses and correlated with the local strains. The conversion between hardness and flow stress is stress (MPa)~3xVHN (where VHN is the Vickers hardness number). The low carbon mild steel used for StressedSkins recorded reductions in sectional thickness from 0.5mm to 0.15mm, and increases in strength from 220 to 410 MPa.

(b) Measurement of the diagonal lengths.

250

MULTI SCALE MODELLING

(a) Sample position.

STRESSED SKINS

technique: pressing

sample1 1 Sample

(b) Adjust the focus of the optical lens.

sample22 Sample

sample33 Sample

Figure 1: Experiment setup before hardness test.

technique: hammering

sample 4

sample 5 S30 S20 45

S: speed angle

(a) Indenter is lowered onto the sample.

Figure 2: Experiment setup during and after indentation.

MICROSCOPY

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Location 1 10x ps

Location 1 20x ps

Location 2 10x ps

Location 2 20x ps

Location 3 10x ps

Location 3 20x ps

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(b) Measurement of the diagonal lengths.

250

STRESSED SKINS

MULTI SCALE MODELLING

DEPTH MODULATION

251

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CITA Complex Modelling

The depth of the rigidisation pattern is established locally from the synthesis of information from several scales within the modelling system. The process begins by discretising each panel from the reaction diffusion model, applying the geometry of the connection elements, and leaving the rest of the panel “unformed”. Each panel is further subdivided into individual, triangulated elements, each of which is capable of having unique material properties assigned to it in the Karamba finite element modelling environment. An analysis is performed on each face, with extracted local strains from the adaptive quad remeshing technique. Resulting yield strengths for each face are specified by the measured relationship between strain and yield strength. Using Karamba’s prescribed displacements enables the process of subjecting this locally informed mesh to corresponding nodal rotations and translations along its connection points, as extracted from the refined FE model. The patterning emerges as a tectonic response to utilisation and bending energies introduced by the global structural conditions.

252

STRESSED SKINS

MULTI SCALE MODELLING

DEPTH MODULATION

251

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252

253 53 54

CITA Complex Modelling STRESSED SKINS

MULTI SCALE MODELLING

254

253 53 54

CITA Complex Modelling STRESSED SKINS

MULTI SCALE MODELLING

254

STRESSED SKINS

MULTI SCALE MODELLING

FABRICATION

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SUBTITLE Stressed Skins is fabricated using a multi-purpose industrial robot. The working area for the final panels is approximately 50x100cm. To improve control over tooling time and surface quality, we develop a toolpathing algorithm based on the established method of a spiral descent (Jeswiet et al. 2005). This algorithm integrates the grouping of features, the position of features, toolpath length and tooling speed in relation to wall angle. The algorithm is also informed by knowledge gained directly through prototyping: this includes the observation of forming limits, optimal working areas, and tooling speed. Lastly, the algorithm incorporates three different jig positions, so that forming takes place in those areas in which the robot is best able to exert force.

Tooling speep in relation to wall angle

Seperated by spiral length

255

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Seperated in features

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CITA Complex Modelling

Reoriented in relation to position

256

STRESSED SKINS

MULTI SCALE MODELLING

FABRICATION

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Tooling speep in relation to wall angle

Seperated by spiral length

255

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Seperated in features

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CITA Complex Modelling

Reoriented in relation to position

256

CITA Complex Modelling

STRESSED SKINS

MULTI SCALE MODELLING

60 Several panels layout for

metal lasercutting

257

61 Close up to one of the panels with the assembly labelling

258

CITA Complex Modelling

STRESSED SKINS

MULTI SCALE MODELLING

60 Several panels layout for

metal lasercutting

257

61 Close up to one of the panels with the assembly labelling

258

STRESSED SKINS

MULTI SCALE MODELLING

1.50 kN

Robot (Model etc.)

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Panel

Grid for ....

259

out of reach

SINGLE ROBOT FABRICATION SET UP

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CITA Complex Modelling

0.90 kN

260

STRESSED SKINS

MULTI SCALE MODELLING

1.50 kN

Robot (Model etc.)

Panel

Grid for ....

259

out of reach

SINGLE ROBOT FABRICATION SET UP

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CITA Complex Modelling

0.90 kN

260

STRESSED SKINS

MULTI SCALE MODELLING

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Integer lobortis accumsan nisl eu venenatis. Morbi felis lectus, viverra et pulvinar eu, vestibulum sed massa. In a sollicitudin risus. Duis sodales, nisi nec eleifend tempor, massa nibh molestie diam, vitae hendrerit mi ligula cursus dui. Proin placerat, arcu vitae suscipit tincidunt, metus magna maximus purus, egestas congue velit neque in mauris. Aliquam et pulvinar augue. Duis elementum metus dolor, vel convallis ante auctor sed. Ut eu leo nec eros hendrerit mollis. Vivamus ac metus eleifend, dignissim est vitae, pulvinar neque. Pellentesque in tellus vulputate, vestibulum orci at, sagittis justo. Sed eget augue eu dui cursus rutrum sit amet et.

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DEVIATION BETWEEN THE DIGITAL AND PHYSICAL Quisque suscipit tellus quam, sed posuere quam vehicula malesuada. Cras nec bibendum nibh. Pellentesque venenatis ultricies elit ut blandit. Integer vitae gravida lectus. Nunc eu imperdiet turpis. Aliquam consectetur tellus orci, non imperdiet ante posuere vel. Aliquam eu rhoncus magna. Praesent dapibus vel felis at pharetra. Nullam laoreet nisi ut turpis consequat ornare. Ut ipsum lectus, elementum lobortis elit ac, placerat fermentum tellus. Fusce ac libero metus. Nunc at nunc vel turpis vehicula lacinia. Suspendisse commodo nibh nec sapien finibus dignissim. Sed lectus felis, posuere eget porttitor id, volutpat vitae magna. Sed vitae mauris ac erat aliquet bibendum. Morbi congue.

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REFERENCES Emmens, W. C., Sebastiani, G., & van den Boogaard, A. H. (2010). The technology of Incremental Sheet Forming¿A brief review of the history. Journal of materials processing technology, 210(8), 981-997. https://doi.org/10.1016/j.jmatprotec.2010.02.014

2 Jeswiet, Jack & Geiger, Manuel & Engel, Ulf & Kleiner, Matthias & Schikorra, M & Duflou, Joost & Neugebauer, R & Bariani, P & Bruschi, S. (2008). Metal forming progress since 2000. CIRP Journal of Manufacturing Science and Technology. 1. 2–17. 10.1016/j.cirpj.2008.06.005. 3 Loop C.T. (1987) Master´s Thesis. Smooth Subdivision Surfaces Based on Triangles. University of Utah, Department of Mathematics.

Photography by A. Ingvartsen Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Photography by CITA Photography CITA Photography CITA Illustration by CITA Illustration by CITA Photography by A. Ingvartsen Illustration by CITA Illustration by CITA Photography by A. Ingvartsen Photography by A. Ingvartsen Photography by A. Ingvartsen Photography by A. Ingvartsen Photography by A. Ingvartsen Photography by A. Ingvartsen

Nicholas, P. (2018). Fabrication for Differentiation: Towards an Adaptive Material Practice. In M.Daas (ed) Towards a Robotic Architecture (s. 76-87), ORO Editions, Nicholas, P., Zwierzycki, M., Stasiuk, D., Nørgaard, E. C., Leinweber, S. & Ramsgaard Thomsen, M., (2016) Adaptive Meshing for Bi-directional Information Flows: A Multi-Scale Approach to Integrating Feedback between Design, Simulation, and Fabrication in Adriaenssens, S., Gramazio, F., Kohler, M., Menges, A. & Pauly, M. (eds.) Advances in Architectural Geometry 2016. 1 ed. Zürich: vdf Hochschulverlag AG an der ETH Zürich, p. 260-273 14 p. Nicholas, P., Stasiuk, D., Nørgaard, E. C., Hutchinson, C. & Ramsgaard Thomsen, M., (2016) An Integrated Modelling and Toolpathing Approach for a Frameless Stressed Skin Structure, Fabricated Using Robotic Incremental Sheet Forming in Reinhardt, D., Saunders, R. & Burry, J. (eds.) Robotic Fabrication in Architecture, Art and Design. 1 ed. Cham: Springer, Vol. 2016. p. 62-77 16 p.

Nicholas, P., Zwierzycki, M., Stasiuk, D. & Ramsgaard Thomsen, M. (2016) Concepts and Methodologies for Multi-scale Modelling: a Mesh-based Approach for Bi-directional Information Flows in Proceedings of the 36th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA): Posthuman Frontiers: Data, Designers, and Cognitive Machines. The Association for Computer-Aided Design in Architecture, p. 308-317 10 p. Nicholas, P., Stasiuk, D., Nørgaard, E., Hutchinson, C. & Ramsgaard Thomsen, M. (2015) A Multiscale Adaptive Mesh Refinement Approach to Architectured Steel Specification in the Design of a Frameless Stressed Skin Structure in Proceedings of Design Modelling Symposium 2015: Modelling Behaviour: Ramsgaard Thomsen, M., Tamke, M., Gengnagel, C., Faircloth, B. & Scheurer, F. (eds.). Cham: Springer, p. 17-34 17 p.

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2018

Sydney, Australia

Transformative Technologies &

Paul Nicholas

Alexander Moss

Data Poetics Group at University

Tim Schork

Zhusong Mei

of Technology Sydney

Dane Voorderhake

Xuan Huy Nguyen

Craft Metals, Australia

Peter Booth

Hoang-Nguyen

Nitika Duggal

Nguyen-Phan

Toan Dinh

Liang Peng

David Ge

Ivana Seizova

Carmelo Leuzzi Anthony Mollica

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Copper Clad explores how the digital design and robotic fabrication methods developed in Stressed Skins and A Bridge Too Far can be integrated into current industry approaches to facade detailing. The project develops a novel faรงade system that incorporates standing seam panel connection detailing, and whose non-standard geometry is interfaced back to a standardised structural sub-frame. The project works with copper sheet, an expensive however particularly sustainable choice of metal for faรงade design. Copper requires no further treatment once installed, is highly formable and expressive, and will last for hundreds of years. In a facade application, vibration caused by wind prevents is a driver for material thickness and panel size. Applying robotic incremental sheet forming methods to increase the structural performance of thin copper sheet results in stiffer, thinner and lighter

panels that use less material, are better able to resist vibration, and decrease the dead-loads carried by underlying structural systems. The project occurred as a 10 day workshop with students at University of Technology Sydney and industrial partner Craft Metals. The prototyping process included exploration and evaluation of different standing seam details and panelisation designs, and fabrication and assembly of a 1:1 copper facade demonstrator. The workshop focussed on gaining direct experience of material and production parameters through hands on experimentation. These investigations tested how digital and physical fabrication variables affected material outcomes, and to familiarize students with process, material and tools. To establish awareness of critical factors influencing material performance and the design space, 300x300mm copper

test squares were set into a reusable forming frame and teams were supplied with a digital fabrication pipeline capable of producing robotic instruction code. Emphasis was placed upon testing geometric, tool and workcell specific limits. Physical limits tested included formed wall angle, global depth of depression, proximity to frame, step down and step over, tool size and length, feed, speed, and whether a supporting profile was used below. Standing seam details were investigated in parallel to forming tests. The standing seam has advantages over other sheet metal details in that by standing perpendicular to the sheet plane it acts as a stiffener. A basic detail was chosen that could be bent to shape using industry standard hand tools, and CNC engraving was tested along fold lines in order to increase accuracy of the edge and reduce tolerances.

The modelling and simulation workflow used in Copper Clad utilises the predictive and multi-scale methods developed on A Bridge Too Far, but extends design consideration to industry standards for the detailing of copper cladding with standing seam connections. Parameters related to dimensioning, seaming and folding lines, connection to sub frame and structural performance, as well as material and fabrication parameters are addressed across three different scales. The global shape is extracted from a sphere to enable consistent ranges of intersection angle between panels. A mesh walking algorithm sub divides the global shape into strips of variably sized triangular panels. The size of each strip is limited to match standard stock and installation requirements. The orientation and subdivision of each strip is optimized to ensure

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Paul Nicholas

Alexander Moss

Data Poetics Group at University

Tim Schork

Zhusong Mei

of Technology Sydney

Dane Voorderhake

Xuan Huy Nguyen

Craft Metals, Australia

Peter Booth

Hoang-Nguyen

Nitika Duggal

Nguyen-Phan

Toan Dinh

Liang Peng

David Ge

Ivana Seizova

Carmelo Leuzzi Anthony Mollica

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the bulk of standing seams run near parallel to local bending forces, making most effective use of the geometric stiffening effect of this detail. To generate the bespoke out of plane deformations that occur on each panel, a reaction-diffusion algorithm is seeded using measures of bending energy from a structural analysis of the restrained, panelised geometry. Indentations locally push further out of plane as more stiffening is required to counteract higher bending forces. The algorithm incorporates awareness of inter-panel edges and internal face to face seam connections, and interpolates between full and zero deformation to allow for the bending required to make seams. Lastly, a thinning analysis using methods developed on Stressed Skins is used to confirm that material forming parameters are not exceeded.

The research develops as part of an ongoing investigation into robotic sheet metal forming at CITA. The underlying drivers of this research trajectory are to investigate how digital design and fabrication tools support new material practices, to develop new methods that support designing across scales of resolution, and to establish design integrated modelling methods. This workshop made use of a KUKA KR120 R2700 HA on a linear Axis, as well as a 3-axis CNC mill. After milling each panel to shape from flat sheet copper, panel seams were pre-bent to a 90 degree angle and screwed into wooden blocks that were then affixed onto a wooden supporting panel. This folded copper flange on all sides stiffened panel edges, counteracting the forces of RISF which resulted in more accurate incremental deformations, reduced stretching of seam tabs and supported highly accurate standing seams. The size of the KUKA ro-

botic arm used had a significant impact on the toolpath feed rate and subsequent production speed as compared to Stressed Skin and A Bridge Too Far. With a 120kg payload the KR120HA achieved straight line feed rates of 1m/s [with the potential for further increases utilising full-automatic mode]. This enabled all 20 copper strips to be formed over a 3 day period. Built demonstrator The faรงade prototype demonstrates that the digital modelling and RISF methods can be integrated into existing industry practice for metal cladding, where it is able to add value by supporting the addition of customised, optimised geometries that increase material stiffness. A principal limit was found to be the restrictions upon the location and continuity of incrementally formed geometries implied by the folding lines required within and at the

edges of each strip. While some of these restrictions are removed in the case on 2D surfaces - the majority of typical wall and roof conditions - further work aims to explore how the need for folding lines might be removed to better achieve complex 3D surface applications.

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Photography by Brett Boardman Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Photography by Brett Boardman Photography by Brett Boardman Illustration by CITA Illustration by CITA Photography by Brett Boardman Photography by Brett Boardman Photography by Brett Boardman Photography by Brett Boardman Photography by Brett Boardman Photography by Brett Boardman

LIST OF PUBLICATIONS Nicholas, P., Schork, T., & Voorderhake, D. (2018). Full-scale Prototype of a Lightweight and Robotic Incrementally Formed Copper Facade System with Standing Seam Connections. In Proceedings of the IASS Symposium 2018: Creativity in Structural Design https://doi.org/10453/126840

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ISOROPIA

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A key insight in Complex Modelling is that the integration of machine learning in the networked model enables adaptive parameterisation and breaks the reductionism inherent to parametric modelling. As our models are able to intersect with information drawn from the world around us through the sensing and simulation of environment, and structural and material behaviour, we encounter the dilemma of the information-rich but data-heavy design model. Complex Modelling exposes the nature and sheer volume of the information of future modelling paradigms that seek to design for performance and optimise material deployment. These processes introduce radically new scales and types of data into design modelling. Complex Modelling examines the idea of information-rich design through a focus on machine learning. By employing machine learning across the networked model, we combine analytical methods for evaluation and classification with creative methods for design generation and evolution. Machine learning is different from parametric strategies in that models are not explicitly defined but rather trained on data sets. This means that the information-rich design environment acts

as a source of training data. Data can be brought in as a predefined data set or generated continually, and their associated models can be trained either discretely or continuously. Here, models exist in multiples, in thousands of models, which are spawned by the generative system to then be analysed by the learning system. Models are no longer singular endpoints, where finding the optimum represents the end of the modelling process. Instead, models learn from other models. They belong to processes of expansion, increasing in number and in complexity at each step of evolution (1). Machine learning presents new practices for architecture. In Complex Modelling, we examine three central emergent practices (2). Firstly, we investigate new modes of mapping and characterising solution spaces in non-explicit ways. Secondly, by intersecting machine learning with simulation, we develop alternate strategies for performance prediction, which avoids brute-force calculation. And thirdly, we extend the adaptability of design information by applying machine learning onto sense data gathered from the fabrication process.

In Learning to be a Vault, unsupervised machine learning is used to map solution spaces and categorise outputs into observable classifications thereby letting the designer navigate these high-order design spaces more easily (3). In Lace Wall, neural networks are interfaced with simulation in order to optimise structural morphology and enhance performance. Here, machine learning is interfaced with multiscale simulation strategies. At the scale of the element, a genetic algorithm is used to optimise the topology of the cable network for both performance and fabrication requirements, and at the scale of the structure, an artificial neural network trained with backpropagation is used to bypass structural simulation. Finally, in Bridge Too Far, fabrication processes are informed by sense data. Here, we employ machine learning algorithms to create strategies of continual adaptation (3). Sensors observe the robotic fabrication process to continually register material deformation. The data they produce trains a machine learning algorithm that adapts the forming process to local material conditions.

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DATE

VENUE

COLLABORATION

SUPPORT

TEAM

2016

Meldahls Smedie KADK

HAL Robotics, SICK Sensor

The Danish Council for Independent Research

Paul Nicholas

Complex Modelling

Intelligence Denmark,

Esben Clausen Nørgaard

Exhibition

KET Konstruktives Entwerfen

Mateusz Zwierzycki

Copenhagen, Denmark

und Tragwerken UdK Berlin,

Scott Leinweber

Bollinger+Grohmann

Riccardo La Magna Christoph Hutchinson

A BRIDGE TOO FAR

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A Bridge Too Far uses a process of robotic metal forming to create a light, strong bridge from very thin metal sheets. This project extends the research territories of Robotic Incremental Sheet Forming (RISF) and Inter-scale Modelling initialised in the project Stressed Skins. The key enquiry is to explore the use of nested meshes and a hierarchy tree to connect distinct models associated with different scales, as opposed to the adaptive meshing strategy implemented in Stressed Skins. The project additionally extends upon Stressed Skins in three aspects: 1) a shift to dual point robotic forming, 2) exploration of machine learning as a means to improve forming accuracy, and 3) consideration of stronger materials and live structural loads. The project both develops production and simulation methods. The robotic incremental sheet forming (RISF) method im-

parts 3D form onto a 2D sheet by moving a ball-headed tool over the surface of a sheet to cause localised plastic deformation. The dual sided approach implemented in this project enables forming out of plane in opposing directions, and removes the need for any supporting jig. This allows for greater freedom and complexity in the formed geometry, including features that it would be difficult or impossible to create supports for. In A Bridge Too Far, we further the state of the art by applying this technique to architectural fabrication, expanding the vocabulary of elements formed, and by developing methods for linking the material implications of forming to design modeling. The complex material behaviours associated with this forming process raise key questions regarding the prediction of material and structural implications, and how to incorporate this information within the design process across

different scales of resolution. A Bridge Too Far focuses on the exchange of information between material, generative and structural models with different resolutions. The modelling approach decomposes the bridge design into distinct but interdependent models associated with macro, meso and micro scales. These models parameterize one another. A key concern is therefore those techniques which enable the information generated within each of these models to flow to others. The project develops a highly efficient tree traversal method to support both upstream and downstream propagation of information about material and structural performance between different models, using various methods of numerical propagation and coarsening. This supports a search process that integrates fitness criteria from across multiple models and scales of resolution.

Structurally, A Bridge Too Far relies on several hundred point connections being made precisely between upper and lower skins. As the manipulative forming process is affected by spring-back behavior too complicated to simulate and solve within the modelling process, the project explores the need for a back and forth between fabrication, analysis and modeling. A central contribution of the project is to develop two adaptive strategies - an online sensor-based strategy and an offline strategy based on 3D scanning and neural networks – to manage, predict and correct for spring-back. These material models - capable of registration, learning and decision making – increase forming accuracy through the adaption of design information during the fabrication process, inverting the usual relationship between modeling and fabrication.

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DATE

VENUE

COLLABORATION

SUPPORT

TEAM

2016

Meldahls Smedie KADK

HAL Robotics, SICK Sensor

The Danish Council for Independent Research

Paul Nicholas

Complex Modelling

Intelligence Denmark,

Esben Clausen Nørgaard

Exhibition

KET Konstruktives Entwerfen

Mateusz Zwierzycki

Copenhagen, Denmark

und Tragwerken UdK Berlin,

Scott Leinweber

Bollinger+Grohmann

Riccardo La Magna Christoph Hutchinson

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A Bridge Too Far explores the architectural potentials of robotic incremental sheet forming. The research develops integrated design, simulation and fabrication workflows that connect material and geometric change at multiple geometric scales. Within the modelling process, panelisation, rigidisation geometries and connection points are generated and optimised for their specific location within the bridge structure. This process of customization enables a very thin and light material - 0.5mm aluminium sheet â&#x20AC;&#x201C; to become strong enough to carry the weight of a person over a span of 4m. A Bridge Too Far extends prior research in the Complex Modelling project Stressed Skins (refs) at CITA, experiments into incremental forming at Michigan(), and the use of metal forming for architectural structures at RWTH Aachen ()

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INTRODUCTION

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MAKING THIN SHEETS STRONG

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House Frame by Jean Prouve, 1954

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Thin panelized metallic skins play an important role in contemporary architecture, often as a non-structural cladding system. Strategically increasing the structural capacity - particularly the rigidity - of this cladding layer could offer significant efficiencies as well as savings for secondary and primary structural systems. Traditional techniques for rigidizing a thin sheet include stamping or rolling the sheet to increase its structural depth. Where Junkers, LeRicolais and Prouve initiated the architectural exploration of rigidized lightweight metallic architectures and structural elements, this research aims to explore further potential architectural applications that exist in customised load-adapted architectural designs. Because loads vary over a building system, the requirements for structural rigidity and rigidisation vary. Responsive local adaption of morphology - not possible or feasible using more standardised rolling and stamping methods - opens opportunities to integrate expression, form and structural behaviour.

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House Frame by Jean Prouve, 1954

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sample11 Sample

For most fabrication process a relative constancy of properties during fabrication can be assumed. However, the RISF process has effects that are both geometrically and materially transformative. As materials are stretched out of plane, there is a corresponding change in local properties - thinning as the surface area increases, as well as cold working which effects the hardness and yield strength of the metal. The design process for A Bridge Too Far began with the production of identical sample geometries of different metals, including titanium, magnesium (hot formed), steel, zink, aluminium, as well as thermoplastics, to determine the behaviour of each material during fabrication.

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These forming experiments with metals and plastics informed the decision to use a pre-hardened 0.5mm Aluminium 5005H14. This metal provides a good balance between formability, initial thickness and initial hardness. In comparison with steel, the higher formability of thin aluminium sheet allows higher forming speeds and faster production without risking a significantly higher amount of material failures. This material choice also impacted the design, where the average wall angle of the rigidisation pattern and other geometries could be increased from previous prototypes.

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CURABITUR VITAEGORO CONGUE

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The hardness test for the Al-1mm and Lexan-1.8mm samples were performed with the Duramin A300 Vickers Hardness Tester using a load of 0.1kN and a dwell time of 10 seconds. Here is a simple step-by-step demonstration on how the tests were performed. The sample tested in the presented pictures is Lexan-1.8mm.

INFORMATION RICH DESIGN PRACTICES

A BRIDGE TOO FAR

The first step is to place the sample on the stage where we can accurately control the positioning using the micrometer (Figure 1a) . Then the optical lens is swiveled in to get the image on the real-time image in focus (Figure 1b).

(a) Sample position.

(b) Adjust the focus of the optical lens.

Figure 1: Experiment setup before hardness test. After the the real-time image is in focus, the diamond indenter is slowly lowered onto the sample surface and is pressed into the surface with a load of 0.1kN (Figure 2a), leaving a diamond shape indent on the surface. The two diagonals of the diamond are then measured (in µm, Figure 2b) and the Vickers hardness is calculated with the formula below (F is in kN and d1 , d2 are in mm). HV = (a) Sample position (a) Sample position.

1.8544 × F F ≈ d1 d2 A

(b) Adjust focuslens of the optical lens. (b) Adjust the focus of thethe optical

(b) of Measurement of lengths the diagonal lengths. (b) Measurement the diagonal

(a)isIndenter lowered onto the sample. (a) Indenter lowered isonto the sample

CITA Complex Modelling

Figure 2: Experiment setup during and after indentation.

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aluminium magnesium (b) Measurement of the diagonal lengths. zink mild steel

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Hardness tests were performed on each sample with the Duramin A300 Vickers Hardness Tester using a load of 0.1kN and a dwell time of 10 seconds. Visual monitoring of the grains and measurement of thickness at the same points was achieved using optical microscopy. A material behaviour model was derived from this data by fitting a logarithmic curve to the observed data points. The final choice of material - AL5005-H14 was a negotiation between formability and yield strength to ensure a stable structure but not exceed the force capability our robotics setup. An additional point of interest was that because AL5005-H14 is pre-hardened, forming at low wall angles softens the metal, while higher wall angles hardens it.

Figure 2: Experiment setup during and after indentation. 0%

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(a) Sample position.

(b) Adjust the focus of the optical lens.

1.8544 × F F ≈ d1 d2 A

(b) Adjust focuslens of the optical lens. (b) Adjust the focus of thethe optical

(b) of Measurement of lengths the diagonal lengths. (b) Measurement the diagonal

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CITA Complex Modelling

Figure 2: Experiment setup during and after indentation.

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relative thickness

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Figure 2: Experiment setup during and after indentation. 0%

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Initialise: Make Hierarchy Tree

Set Values: Set values for a particular level of the hierarchy

Set propagation method: 0 - none, 1 - copy, 2 - split, 3 average

Propagate: 0 - level to proagate from 1 - direction: up or down

MULTI-SCALE MODELLING

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A central problem addressed in this project is the transfer of information from one model to another. The HNode (Hierarchy Node) Class is developed to support continuity of information between different geometry resolutions and models. This class is a type of tree data structure which can be traversed efficiently via a query method for parent and child nodes. As with tree structures, all of the data is stored in the root level node. In our case, the root represents the complete demonstrator structure composed of multiple panels, which are stored separately as the second level of the tree. The third level represents the initial low resolution mesh, where each node keeps information for each mesh face. To keep track of different resolutions, the subdivision algorithm introduces new layers to the tree: for each subdivided face, multiple children are added (2-4 for adaptive Loop Subdivision), and to keep the tree easy to read and manipulate, the nodes of the faces which are not subdivided are given a singular child.

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Average strain

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Initialise: Make Hierarchy Tree

Set Values: Set values for a particular level of the hierarchy

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Base Surface

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INFORMATION PROPAGATION

Initial Mesh with Ceases

Mesh after Subdivision

Strain Values

Strain on Initial Mesh

Additional to storing information about its children, an HNode collection can store and/ or convey any other information just like a binary tree. Contrary to that kind of structure, the values are decoupled from the topology of the tree (in our case the topology is derived from the subdivision process) and come from structural analysis at various levels. As the analysis can be done for any of the levels of the tree at any time, various upstream and downstream methods of propagation have been implemented. One example of upstream data propagation is the minimal wall thickness information gained from strains calculation. This process happens at the lowest level of the tree, and to visually inspect the results it is easiest to recursively query each top-level parent to get the lowest value of each of its children. At this highest level, this results in an easy to verify visualization.

Max Strain per Panel

Clustering

Common Areas Calculation

Rigidization Pattern Generation High Resolution

Planarization

Thickness Interpolation

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Evaluate Fitness

Structural Analysis Med Resolution

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Base Surface

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INFORMATION PROPAGATION

Initial Mesh with Ceases

Mesh after Subdivision

Strain Values

Strain on Initial Mesh

Max Strain per Panel

Clustering

Common Areas Calculation

Rigidization Pattern Generation High Resolution

Planarization

Thickness Interpolation

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Loading: karamba “mesh load“ 3kn/m2 applied within the dotted area + gravity load maximum deflection: 4 mm

Surface without rigidisation

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MODELLING EXPERIMENTS

property calculation

A series of modelling experiments are made to establish the representation of geometry for structural analysis, to identify an analysis approach, and to identify appropriate output values. The first of these experiments shows that including rigidisation geometries within the simulation model effects the calculated structural behavior, but also reveals that modelling these geometries at different resolutions produces very different predictions. To determine the ‘right’ resolution to model these geometries – one that accurately simulates structural behavior using lower geometric resolution – deflections simulated using models with stepped decrease in resolution were compared to those of a baseline high resolution model, until an unacceptable deviation was reached. The integrated FE tool Karamba is used to predict behavior and deflections of the entire structure. This design-integrated simulation is validated against simulation using Sofistik as well as empirical load testing of prototypes. Tests of different load cases defined an approach that tested 6 load cases – the full weight of a person on each of the 6 central panels – to find the maximum deformation and measure the elastic deformation energy per panel.

Loading: karamba “mesh load“ 3kn/m2 applied within the dotted area + gravity load maximum deflection: 17mm

Surface without rigidisation

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Load Area (red) and deformation in LC 2

Load Area (red) and deformation in LC 6

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design geometry

Deflections

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Loading: karamba “mesh load“ 3kn/m2 applied within the dotted area + gravity load maximum deflection: 4 mm

Surface without rigidisation

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MODELLING EXPERIMENTS

property calculation

Loading: karamba “mesh load“ 3kn/m2 applied within the dotted area + gravity load maximum deflection: 17mm

Surface without rigidisation

Deflections

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Load Area (red) and deformation in LC 2

Load Area (red) and deformation in LC 6

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A A parametric surface is defined on the basis of four boundary curves and a centerline

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C Points are grouped into panels using K means clustering

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D The outline of each panel is extracted and simplified to a straight line

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A A parametric surface is defined on the basis of four boundary curves and a centerline

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A k-means clustering algorithm is used to determine panel outlines, a low fidelity representation that supports evaluation of the coincidence of seams on upper and lower surfaces. An interference model generates high fidelity rigidisation geometries, from which a precise calculation of material properties is made using circle projection.

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( 4;1 )

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Depending on the geometric transformation, the effects of the material transformation are locally introduced into the material to different degrees according to the depth and angle attained. Given a geometry to be formed, the predictive material model calculates the strains that will be induced by the forming process. Correlation of the predicted strains with data gained from empirical testing (Vickers hardness testing and optical microscopy) enables prediction of the resultant material thickness and yield strength. A circle projection method is used to predict strains: A circle is inscribed into an initial mesh face on a flat, un-deformed sheet and then projected along the normal onto a corresponding deformed sheet. This results in an ellipse whose primary and secondary axes produce both direction and magnitude of strains resulting from the forming process.

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INTER-SCALE SEARCH & OPTIMISATION

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Panels are fabricated using two coordinated industrial robots and a Dual Point Incremental Forming process. The fabrication setup incorporates two ABB industrial robots working on each side of a moment frame that allows for a working area of approximately 1,500 x 1,000mm. Working with DPIF requires a precise positioning of two tools, one that works as a forming tool and one as the local support. The supporting tool can be positioned in two different ways, following the top perimeter of the feature or following the forming tool down the geometry (Paniti, 2014). Early investigation of both methods showed that, for our setup, moving the supporting tool only along the feature perimeter quickly led to tearing of the metal due to the repeated tooling. Feedback from laser distance sensing is used during the fabrication process to manage forming tolerances, with decisions made by one robot communicated to the other.

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Forming affected by: - depth of feature - proximity of frame - proximity to previously formed features - irregularities of the material - calibration of workObj

WITHIN THE FORMING PROCESS While RISF removes the need for complex moulding, the geometric accuracy of forming is affected by spring-back and is lower compared to other approaches. Testing of formed geometries via 3D scanning, photogrammetry, and the measurement of reaction forces during forming, points to a complex interdependency of material behaviour and processing parameters, including the forming velocity, tool path, forming depth, sheet size and distance to points of restraint. This complexity makes it extremely difficult to develop a mechanistic predictive model for spring-back, and motivated a search for alternate strategies for improving forming accuracy.

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training output

prediction

difference fabrication geometry & measured deviation

input mesh

3d scan

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input mesh

input mesh prediction

std deviation 2.180 mm

SENSOR FEEDBACK FOR ADAPTIVE CONTROL To ensure forming accuracy at connection points, the project develops a sensor-based adaptive control approach. This automated process involves 1) positional measurement of each connection centre-point using a single point laser distance measure mounted to the robot arm, 2) calculation of any measured deviation away from the 3D model, and 3) selection of an appropriate toolpath (depth and radius) for a cone that corrects the measured deviation to make a precise connection. Scanning occurs several times during the forming of each cone. During this process, a spring-back model is gradually developed and improved. The specification of cone toolpaths includes an â&#x20AC;&#x2DC;over-formingâ&#x20AC;&#x2122; parameter. This parameter is defined through a linear regression that captures the relationship between target depth and actual forming depth: after each cone is formed, the resultant depth is scanned and the data added to the curve fitting model. This approach allows a continued improvement in accuracy across the course of fabrication.

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mesh correction routine

output

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0 - 15 mm

3d scan

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hidden

input

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ACHIEVING STRENGTH AND LIGHTNESS FINAL DEMONSTRATOR

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The central span of A Bridge Too Far is 3.5m, unframed, and can support live loads of greater than 100kg. This structural capability is the product of locally formed deformations within, and connections between, the upper and lower panels. Bolts at hundreds of points connect the upper and lower panels together, allowing transfer of all tensile, compressive and shear loads. Connections between the upper and lower panels are located in large valley areas within each panel: these areas are zones locally strong enough to walk on, while rigidisation patterns are formed outside the valleys.

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66 Bridge Too Far at the Final Complex Modelling Exhibition 2016

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REFERENCES Paniti I. (2014). Adaptation of Incremental Sheet Forming into cloud manufacturing. CIRP Journal of Manufacturing Science and Technology. 7. 185–190. 10.1016/j. cirpj.2014.04.003.

3 Kalo, Ammar & Newsum, Jake. (2014). An Investigation of Robotic Incremental Sheet Metal Forming as a Method for Prototyping Parametric Architectural Skins. In Robotic Fabrication in Architecture, Art and Design 2014, DOI 10.1007/978-3-319-04663-1_3.

2 Nicholas, P., Zwierzycki, M. & Ramsgaard Thomsen, M., (2017) Localised and Learnt Applications of Machine Learning for Robotic Incremental Sheet Forming in Proceedings of Design Modelling Symposium Paris 2017: Humanizing Digital Reality: Springer, p. 373382 10 p.

Bailly, D., Bambach, M., Hirt, G., Pofahl T., Puppa Della G., Trautz M., (2015). Flexible Manufacturing of Double-Curved Sheet Metal Panels for the Realization of Self-Supporting Freeform Structures. In Key Engineering Materials 639: 41–48. doi:10.4028/www. scientific.net/KEM.639.41.

5 Sulzer, P., 2008. Jean Prouve Complete Works Volume 3: 1944-1954. Germany: Birkhauser.

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Illustration by CITA Illustration by CITA Photography by CITA Photography by CITA Photography by CITA Photography by CITA Illustration by CITA Illustration by CITA Illustration by CITA Photography by CITA Diagram by CITA Illustration by CITA Illustration by CITA Diagram by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Photography by A. Ingvartsen Photography by A. Ingvartsen Photography by A. Ingvartsen Photography by A. Ingvartsen

Nicholas, P., Zwierzycki, M., Clausen Nørgaard, E., Leinweber, S., Stasiuk, D., Ramsgaard Thomsen, M. & Hutchinson, C. (2017) Adaptive Robotic Fabrication for Conditions of Material Inconsistency: Increasing the Geometric Accuracy of Incrementally Formed Metal Panels in A. Menges, B. Shiel & M. Skavara (eds.) Fabricate 2017. UCL Press, p. 114-121 8 p. Nicholas, P., Zwierzycki, M. & Ramsgaard Thomsen, M., (2017) Localised and Learnt Applications of Machine Learning for Robotic Incremental Sheet Forming in Proceedings of Design Modelling Symposium Paris 2017: Humanizing Digital Reality: Springer, p. 373-382 10 p.

Nicholas, P., Zwierzycki, M., Stasiuk, D., Nørgaard, E. C., Leinweber, S. & Ramsgaard Thomsen, M., (2016) Adaptive Meshing for Bi-directional Information Flows: A MultiScale Approach to Integrating Feedback between Design, Simulation, and Fabrication in Adriaenssens, S., Gramazio, F., Kohler, M., Menges, A. & Pauly, M. (eds.) Advances in Architectural Geometry 2016. 1 ed. Zürich: vdf Hochschulverlag AG an der ETH Zürich, p. 260273 14 p.

Photography by CITA Illustration by C. Hutchinson Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Diagram by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Diagram by CITA Illustration by CITA Illustration by CITA Diagram by CITA Illustration by CITA

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Illustration by CITA Photography by A. Ingvartsen Photography by A. Ingvartsen Photography by A. Ingvartsen Scanned image by CITA from J. Prouve Complete Works Volume 3 6 Photography by CITA 7 Photography by Archiv Bernd Junkers 8 -------------------------------9 Retrieved from https:// media.ford.com/content/fordmedia/feu/en/permalink.html?VideoId=5852356387001 10 Photography by CITA 11 Photography by CITA 12 Photography by CITA 13 Photography by CITA 14 Diagram by CITA 15 Illustration by CITA 16 Illustration by CITA 17 Photography by CITA 18 Illustration by CITA 19 Illustration by C. Hutchinson 20 Diagram by CITA 1 2 3 4 5

LIST OF PUBLICATIONS

IMAGE CREDITS

356

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A BRIDGE TOO FAR

REFERENCES Paniti I. (2014). Adaptation of Incremental Sheet Forming into cloud manufacturing. CIRP Journal of Manufacturing Science and Technology. 7. 185–190. 10.1016/j. cirpj.2014.04.003.

5 Sulzer, P., 2008. Jean Prouve Complete Works Volume 3: 1944-1954. Germany: Birkhauser.

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LIST OF PUBLICATIONS

IMAGE CREDITS

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INFORMATION RICH DESIGN PRACTICES

DATE

VENUE

SUPPORT

TEAM

2016

Meldahls Smedie KADK

The Danish Council for Independent Research

Mette Ramsgaard Thomsen

Complex Modelling

Martin Tamke

Exhibition

Anders Holden Deleuran

Copenhagen, Denmark

Mateusz Zwierzycki Ida Friis Tinning Yuliya Ĺ inke Baranovskaya Danica Pistekova

LACE WALL

357

Lace Wall explores form-active hybrid structures that combine elements in tension and compression in a pre-calculated balance. Here two elements of low structural capacity - slender fibreglass beams and textile cable networks â&#x20AC;&#x201C; are combined in interdependent relationships to create one whole of higher stiffness. Lace Wall examines the design methods necessary to design and develop such structures. By learning from prior research into hybrid structures, our aim is to formalise and extend an otherwise mainly empirical methodology of handson testing, by developing digital design methods that incorporate the simulation of interacting material systems. The aim is to enable structural variation, local optimisation by bridging to fabrication. Lace Wall is a 12 meter long and 5 meter high wall constructed out of 80 form-active units, each made of bent rods and a

constraining cable net. Lace Wall follows a textile logic of cells and arrays and is a generic and modular space frame-like system. In this instance a wall, the system can be extended in a spatial array to construct large enclosures such as walls, roofs, domes and more complex macro shapes. While the dimension and topology of the GFRP units are identical, the cable networks are differentiated so as to allow the single units to withstand different local strains in the structure, and to constrain each unit with cable nets into bespoke geometries that allow them to fit into a desired overall macro shape. In order to design and build Lace Wall new material, computational and engineering methods to design with bending active systems had to be developed. We developed a design integrated tool, which allows for real-time interaction with form active hybrid structures (FAHS) This tool provides

immediate feedback about the formation of the material system with realistic material behaviour. This tool does not restrain design to iteration within a given topology, but allows for free topological exploration as well as the use of parametric and other generative modelling strategies. The tool generates physically correct structural feedback regarding internal forces and deformations in realtime on the scale of units and small assemblies. The complexity of the large Lace Wall aggregates demands however still considerable time, which prevents a reasonable speed in design interaction and optimisation. In order to assess the structural capacity of Lace wall and specify the local cells and cable net constraints we developed a structural optimisation technique with machine learning. This develops through a few simulation runs on the macro and meso level of Lace wall an intuition about the structural

behaviour of the design. Comparative test with conventional optimization strategies using Finite Element Analysis, show, that our approach generates structural sound solutions, while being way faster. We finally developed new material techniques for assembly and joining of thousands of bending active elements.

1 Lace Wall installation in

the Exhibition Space, KADK Complex Modelling Exhibition, 2016

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PROJECT

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DATE

VENUE

SUPPORT

TEAM

2016

Meldahls Smedie KADK

The Danish Council for Independent Research

Mette Ramsgaard Thomsen

Complex Modelling

Martin Tamke

Exhibition

Anders Holden Deleuran

Copenhagen, Denmark

Mateusz Zwierzycki Ida Friis Tinning Yuliya Ĺ inke Baranovskaya Danica Pistekova

LACE WALL

357

1 Lace Wall installation in

the Exhibition Space, KADK Complex Modelling Exhibition, 2016

CITA Complex Modelling

PROJECT

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STATE OF THE ART INVESTIGATING THE INTERACTION OF FORCES IN HYBRID STRUCTURES

359

2 Close up to the Lace

Wall Structure, Complex Modelling Exhibition 2016

3 Bat Wing Sail, R Off, 2007 4 Membrane Restrained Column, Udk Berlin, 2012 5 Membrane Restrained

Column, Udk Berlin, 2012

6 ICD/ITKE Textile Hybrid

Installation La Tour de lâ&#x20AC;&#x2122;Architecte, 2012

CITA Complex Modelling

Form-active hybrid structures (FAHS) are defined by the principle of constructing a stiff and resilient whole using an inventory of lightweight and deforming structural elements which restrain each other in a reciprocal manner. Structures of this type typically combine bending-active slender beams acting in compression, textile membranes acting in tension, and cables acting in tension. These locally different material behaviours are combined to generate a global form-active hybrid behaviour. FAHS present a promising approach for designing efficient and elegant structural skins. When intelligently combined, these structures have the potential to offer high load-bearing capacity at a fraction of the weight of traditional building elements and can improve the performance of buildings in terms of efficiency of material usage. Beyond pure structural efficiency, they provide a rich visual language, which directly expresses the force flow and equilibrium state of the structure. At present, a significant impediment to the design of form-active hybrid structures is the lack of appropriate design tools. Recent interest has resulted in new methods for shaping and form-finding form-active hybrid structures including finite element modelling (1), spring-based modelling (2) and force-density methods (3). However, these methods focus on validation of structures and omit the initial processes of defining assemblies of elements and supports (4).

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STATE OF THE ART INVESTIGATING THE INTERACTION OF FORCES IN HYBRID STRUCTURES

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2 Close up to the Lace

Wall Structure, Complex Modelling Exhibition 2016

3 Bat Wing Sail, R Off, 2007 4 Membrane Restrained Column, Udk Berlin, 2012 5 Membrane Restrained

Column, Udk Berlin, 2012

6 ICD/ITKE Textile Hybrid

Installation La Tour de lâ&#x20AC;&#x2122;Architecte, 2012

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SYSTEMS IN BALANCE SPATIAL HYBRID SURFACES: FROM TEXTILE TO NETS

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7 â&#x20AC;&#x153;Deep form-active hybrid

skinâ&#x20AC;? developed during the Tower project

8 Model of the membrane restrained pringle 9 Model of the cable-net restrained pringle

CITA Complex Modelling

Lace Wall is part of a larger investigation into the design and fabrication of form-active hybrid structures. It builds on prior work in the Complex Modelling project Tower, in which we developed an interested in expanding the vocabulary of FAHS into modular approaches with distributed cell-based structural systems. However the conception and making of these systems of interacting arrays of bending sticks and restraining three dimensional textiles is complex. Inspired by the simulation models of FAHS, in which membrane surfaces are abstracted as networks of linear element, we replace the full textile membranes with a strategic network of tensile cables. In this way we reduce our FAHS inventory to consist exclusively of linear elements (beams and cables). This reduction affords a high degree of combinatorial options using the same geometrical representation, aligns the description and behaviour of the physical and computational modelling and reduces efforts for making physical models.

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SYSTEMS IN BALANCE SPATIAL HYBRID SURFACES: FROM TEXTILE TO NETS

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7 â&#x20AC;&#x153;Deep form-active hybrid

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8 Model of the membrane restrained pringle 9 Model of the cable-net restrained pringle

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TOPOLOGICAL EXPLORATION UNDERSTANDING THE DESIGN INVENTORY

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11 10 Single tail models of the

units for the future systems of interconnected elements

will perform my bigger bending resistance

11 Digital sketches of the

scaling opportunities within a single cell

12 Models of a single unit type cells restrained with the cablenet

1. very important the proportion between the circumference of the loop in the relation to the line to line self overlap 2. the cable attached in all examples in the same pattern location: middle of loop to the end of line-line self overlap 3. self overlap in all examples is till the middle of tail

CITA Complex Modelling

The project investigates the design space for FAHS on a fundamental level. While other projects in the field of FAHS concentrate on the simulation and making of found topologies, we extend these concerns to include investigation of the initial process of inventing assemblies of elements and supports. The aim is to find novel topologies for FAHS and methods, which enable us to use computation to generate, analyse and improve novel FAHS topologies. As a first step we investigate the topological strategies in the formation of FAHS. We find, that in our minimal inventory of two types (cables and beams) a huge topological richness emerges through simple changes on only three levels: the topological setup - how and where elements are connected, the dimension of these elements - the length these elements have - and which type of elements are connected. By working through physical prototyping the fundamental material behaviour of the units were understood and an intuition for their variation was built. Prototypes were built in scaled models using 1.5mm glass fibre rod and waxed thread.The prototype investigation was documented in a catalogue of â&#x20AC;&#x153;primitivesâ&#x20AC;? that supported further topology exploration of the primitive, the array and field.

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11 10 Single tail models of the

units for the future systems of interconnected elements

will perform my bigger bending resistance

11 Digital sketches of the

scaling opportunities within a single cell

12 Models of a single unit type cells restrained with the cablenet

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NonPeriodic Connection is achived using developing CVs

Self, Point, End-end, Periodic

Self, Point, End-end, NonPeriodic

Self, Point, Inside-Inside A

Overlapping edges

CITA Complex Modelling

Non-Periodic connection achieved using acute angle

Self, Point, End-end, NonPeriodic

Self, Overlap, End-Inside

Overlapping edges

Self, Overlap, End-End, NonPeriodic

Self, Point, End-Inside

INTERACTIVE DESIGN TOOLS In contrast to current tools for design and simulation of FAHS we aim for a tool which allows for interactive modelling. A crucial step in Lace Wall was therefore the development of methods to construct the geometrical representation of elements, for discretizing this geometry and for dynamically coupling the Rhino document and the Grasshopper definition. In our digital workflow beams and cables are represented as polylines, piecewise linear curves which approximate continuous shapes. These are drawn by the designer as easy to understand coarse polylines describing assembly topology and initial dimensions. Implementing a layer naming convention, these are automatically piped to Grasshopper if anything changes on the Rhino document beam/cable layers. Here they are discretized by subdividing their edges into a user defined sub-edge length. To enable the designer snapping to the discretized geometry, all its vertices are automatically captured and sent back to the Rhino document as a locked point cloud. This modelling loop affords immediate and precise definition of assemblies and provides the designer with an intuitive interface, where complex changes can be executed with ease and results on the designs material behaviour are feedback almost in real time.

Overlapping edges

Self, Overlap, End-Inside

Overlapping edges

Self, Overlap, Inside-Inside

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Self, Point Inside-Inside & Self Point, End-End, Periodic

Self, Overlap, End-Inside

13 Catalog of self-connecting beams. The rules for a nonperiodic end-end connection is to draw overlapping vertices at the connection, or, to have the incoming edges meet below a user specified angle

14 Digital explorations of

the influence of cable net typologies in resulting shape of bending active loop

15 Interactively defining topology and shaping an FAHS assembly with real-time shaping and downstream bending analysis using our modelling pipeline on the case of a pringle

16 Design variation of a loop element with different cable nets

Self, Overlap, End-end, Periodic

DIGITAL PROTOTYPING

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INFORMATION RICH DESIGN PRACTICES

LACE WALL

NonPeriodic Connection is achived using developing CVs

Self, Point, End-end, Periodic

Self, Point, End-end, NonPeriodic

Self, Point, Inside-Inside A

Overlapping edges

CITA Complex Modelling

Non-Periodic connection achieved using acute angle

Self, Point, End-end, NonPeriodic

Self, Overlap, End-Inside

Overlapping edges

Self, Overlap, End-End, NonPeriodic

Self, Point, End-Inside

Overlapping edges

Self, Overlap, End-Inside

Overlapping edges

Self, Overlap, Inside-Inside

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Self, Point Inside-Inside & Self Point, End-End, Periodic

Self, Overlap, End-Inside

13 Catalog of self-connecting beams. The rules for a nonperiodic end-end connection is to draw overlapping vertices at the connection, or, to have the incoming edges meet below a user specified angle

14 Digital explorations of

the influence of cable net typologies in resulting shape of bending active loop

15 Interactively defining topology and shaping an FAHS assembly with real-time shaping and downstream bending analysis using our modelling pipeline on the case of a pringle

16 Design variation of a loop element with different cable nets

Self, Overlap, End-end, Periodic

DIGITAL PROTOTYPING

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INFORMATION RICH DESIGN PRACTICES

CUSTOM GOALS AND K2 ENGINEERING TOWARDS MECHANICALLY ACCURATE BEHAVIOUR

reactions

The Grasshopper plugin Kangaroo popularised the design of force equilibrium structures in parametric design workflows. While extremely successful in the computational architectural community, it was hard to calibrate the original Kangaroo particle spring solver to real world forces. The latest release of Kangaroo (K2), whose development took place during and in collaboration with the Complex Modelling project, featured the implementation of a projection based dynamic relaxation technique and an improved damping scheme. This facilitates simulation of mechanically accurate structural behaviour with remarkable stability and speed. We utilised the newly added API and custom goals in K2 to create a structurally calibrated extension called K2 Engineering. The main purpose of this plugin is to offer a direct output of meaningful structural values that can be used to evaluate the performance. The plugin currently contains a bar, cable, rod and support goal from which the axial forces, reactions, shear and bending moments can be extracted. In Lace Wall K2 and K2 Engineering are completely integrated: K2 is used for the interactive design with hybrid structures in realtime and designers can at any moment switch to K2 Engineering in order to determine the impact of real world forces on shape and overall stability on element and macro level.

bending

shear

17 Visualisation of forces in

K2 Engineering

18 Gregory Quinn at the SmartGeometry 2016 Workshops giving a lecture about Form-Active Structures. Gothenburg, Sweden

axial

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CUSTOM GOALS AND K2 ENGINEERING TOWARDS MECHANICALLY ACCURATE BEHAVIOUR

reactions

bending

shear

17 Visualisation of forces in

K2 Engineering

18 Gregory Quinn at the SmartGeometry 2016 Workshops giving a lecture about Form-Active Structures. Gothenburg, Sweden

axial

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EARLY ATTEMPTS a OF GEOMETRICAL a a ORGANISATION LOGICS a a DEVELOPMENT a a The interest in the primitive, the balanced a a figure of bend rods and restraining cable neta a work, is spawned by the interest to aggregate them into larger systems. a Two strategies are investigated: Independent unit organisation through tiling with topological closed elements, connected along their edges Interdependent unit organization through textile logics - open ended elements are interwoven with neighbors To understand the inherent ability for the primitive to aggregate, a series of parallel digital and physical prototypes were designed exploring connectivity and variation.

AGGREGATING PRIMITIVES

a a

a a+

19 Digital explorations into

the tiling of primitives

20 Relation of a single

primitive in an array using textile strategies

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AGGREGATING PRIMITIVES

a a

a a+

19 Digital explorations into

the tiling of primitives

20 Relation of a single

primitive in an array using textile strategies

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INFORMATION RICH DESIGN PRACTICES

LACE WALL

Simulation of one unit from gh (60% scaled the same image as on the previous page)

01.

Simulation of one unit from gh (60% scaled the same image as on the previous page)

Field image top (simulation)

a b Simulation of one unit from gh (60% scaled the same image as on the previous page)

Field image top (simulation)

Simulation of one unit from gh (60% scaled the same image as on the previous page)

Field image top (simulation)

TRANSFORMATION OPERATIONS RULES FOR AGGREGATION

Field image perspective (simulation)

Simulation of one unit from gh (60% scaled the same image as on the previous page)

Field image perspective (simulation)

CITA Complex Modelling

Simulation of one unit from gh (60% scaled the same image as on the previous page)

Field image perspective (simulation)

Simulation of one unit from gh (60% scaled the same image as on the previous page)

Field image perspective (simulation)

Simulation of one unit from gh (60% scaled the same image as on the previous page)

Field image perspective (simulation)

Simulation of one unit from gh (60% scaled the same image as on the previous page) Simulation of one unit from gh (60% scaled the same image as on the previous page)

01. 01. 01.

TILING PRIMITIVES

Field image top (simulation)

By building an understanding of the inherent asymmetries of the primitives it is interesting how macro behaviour emerges from the base design of the unit structures. By looking at the arraying, pairing and mirroring of primitives various geometrical behaviours can be observed. Depending on the angle of rotation and the translation vector it is possible to achieve a variety of geometrical macro behaviours. The final unit design is made from a mirrored pair of bent rods with varying cable network optimised for its particular position in the assembly. For beams a key structural concern is the local bending stress, as too much complicates assembly and eventually snaps the GFRP rods. The bending stress, utilisation and reserve of the beam in isolation of other load cases can however be derived from the local radii along the polylines of the digital model. We measure the local radii, defined here as the radius of the circle constructed through a polyline vertex and its two neighbours. This property is visualised in the viewport as coloured/scaled vectors that also provide a visual representation of the bending orientation providing instant feedback within the design process.

02.

02. 02. 02. 03. a

a b

03. 03. 03. 04.

21 Digital explorations of the

different pringle arrays

22 Translation

transformation for forming a linear array of elements

Field image perspective (simulation)

371 Field image perspective (simulation)

Field image perspective (simulation)

04. 04. 04.

Simulation of one unit from gh (60% scaled the same image as on the previous page)

372

INFORMATION RICH DESIGN PRACTICES

LACE WALL

Simulation of one unit from gh (60% scaled the same image as on the previous page)

01.

Simulation of one unit from gh (60% scaled the same image as on the previous page)

Field image top (simulation)

a b Simulation of one unit from gh (60% scaled the same image as on the previous page)

Field image top (simulation)

Simulation of one unit from gh (60% scaled the same image as on the previous page)

Field image top (simulation)

TRANSFORMATION OPERATIONS RULES FOR AGGREGATION

Field image perspective (simulation)

Simulation of one unit from gh (60% scaled the same image as on the previous page)

Field image perspective (simulation)

CITA Complex Modelling

Simulation of one unit from gh (60% scaled the same image as on the previous page)

Field image perspective (simulation)

Simulation of one unit from gh (60% scaled the same image as on the previous page)

Field image perspective (simulation)

Simulation of one unit from gh (60% scaled the same image as on the previous page)

Field image perspective (simulation)

Simulation of one unit from gh (60% scaled the same image as on the previous page) Simulation of one unit from gh (60% scaled the same image as on the previous page)

01. 01. 01.

TILING PRIMITIVES

Field image top (simulation)

02.

02. 02. 02. 03. a

a b

03. 03. 03. 04.

21 Digital explorations of the

different pringle arrays

22 Translation

transformation for forming a linear array of elements

Field image perspective (simulation)

371 Field image perspective (simulation)

Field image perspective (simulation)

04. 04. 04.

Simulation of one unit from gh (60% scaled the same image as on the previous page)

372

INFORMATION RICH DESIGN PRACTICES Initial parameters: -translation vector -rotation angle

mirrored internal cable net

internal cable net

LACE WALL

internal cable net

translation vector causes the shift of the base unit to create an array

extended external cable net

external cable net

translation vector causes the shift of the base unit to create an array translation angle translation angle 40 Â°

translation vector causes the shift of the base unit to create an array translation angle 40 Â°

anchor points

SPATIAL ARRAYS

anchor points

373

step 01

step 02

half circular arrangement without constraining cables, hinge freedom

half circular arrangement cables are only withon the unit, hinge freedom remains

The intended structural function for the tiled elements in the Lace Wall is to withstand compression and tension forces though cable nets, which brace and constrain. However these work under tension only and the insertion of large cable nets into the assembled system is challenging. Through digital probes we investigate different degrees of interconnectivity between the cable nets and the modular system of GFRP elements in regards to the ability to create macro shapes, the structural performance and the effort needed for assembly. Full cable nets, which span between several discrete GFRP elements perform best in terms of structural strength, but are challenging in terms of assembly logic and sequence. In conclusion the function of the cable nets should be to constrain the individual units, while the connection between the units take place through contact between GFRP rods.

step 03 half circular arrangement, cables are within the units as well as in between units

step 04 23 Digital modelling of the

circular arranged units. Steps 1-3

half circular arrangement, with expanded network of cables

24 Digital modelling of the

circular arranged units. Step 4

CITA Complex Modelling

INTRODUCING CABLE NETS IN TILING PRIMITIVES

374

INFORMATION RICH DESIGN PRACTICES Initial parameters: -translation vector -rotation angle

mirrored internal cable net

internal cable net

LACE WALL

internal cable net

translation vector causes the shift of the base unit to create an array

extended external cable net

external cable net

translation vector causes the shift of the base unit to create an array translation angle translation angle 40 Â°

translation vector causes the shift of the base unit to create an array translation angle 40 Â°

anchor points

SPATIAL ARRAYS

anchor points

373

step 01

step 02

half circular arrangement without constraining cables, hinge freedom

half circular arrangement cables are only withon the unit, hinge freedom remains

step 03 half circular arrangement, cables are within the units as well as in between units

step 04 23 Digital modelling of the

circular arranged units. Steps 1-3

half circular arrangement, with expanded network of cables

24 Digital modelling of the

circular arranged units. Step 4

CITA Complex Modelling

INTRODUCING CABLE NETS IN TILING PRIMITIVES

374

2016-02-18T18:21:47 INFORMATION RICH DESIGN PRACTICES

LACE WALL

Line/line overlap connections could be overlap connections could be reduced to leave more Line/Line freedom to the system reduced to leave more freedome to the system Applies only for non-planar target (curved Applies mostly for nongeometries planar targer geometries (curvedwall, wall, etc)etc)

“Open“ part of the component: opportunity "Open" partdimension of the component, to vary the opportunity to vary the dimension of cables and affect the of cable and affect the geometry target geometry.

“Open“ part of the component: opportunity to vary the dimension of cables and affect the "Open" part of the component, target geometry. opportunity to vary the dimension of cable and affect the geometry

LocalLocal plane deformations planes deformations by cable tension by cable tensioning

a initial element, loop with tail

Set up with minimal Minimal amount of cables for self support amount of cables

a+ mirrored bottom causes the change of the neck angle

-a mirrored in two planes

-a+ initial a mirrored in 4 planes

If the cluster has elements that are mirrored in 4 planes, theoretically it means that it will stabilize itself and not perform and directional performance (e.g. twisting in one direction, etc.) This one will be suitable for:

TEXTILE LOGICS FOR LACE WALL

PLANAR SOLUTIONS WITH LOCAL DEFORMATIONS (texture) TARGET GEOMETRIES WITH THE ENCLOSED EDGE (cylinder)

DEPENDENT UNIT AGGREGATION

Our investigation into the interdependent aggregation of units is informed by a deep interest in textile logics and the ability for textiles systems to be transferred into architectural scale structures informs. In textile systems such as knit and lace, base stitches make up the units of the structure. However, these structures are friction based as the fibres are continuous through the material system. In Lace Wall we investigate whether similar material strategies can be devised on a macro scale. Here the units are open ended through eg. long tails, allowing them to interweave with neighbours and create a dense structural web.

375

25 Effectiveness of the different cable net on the same beam structure 26 Physical model of a

dependent cablenet systems. Model 1

27 Physical model of a interdependent cablenet systems. Model 2

CITA Complex Modelling

376

2016-02-18T18:21:47 INFORMATION RICH DESIGN PRACTICES

LACE WALL

LocalLocal plane deformations planes deformations by cable tension by cable tensioning

a initial element, loop with tail

Set up with minimal Minimal amount of cables for self support amount of cables

a+ mirrored bottom causes the change of the neck angle

-a mirrored in two planes

-a+ initial a mirrored in 4 planes

TEXTILE LOGICS FOR LACE WALL

PLANAR SOLUTIONS WITH LOCAL DEFORMATIONS (texture) TARGET GEOMETRIES WITH THE ENCLOSED EDGE (cylinder)

DEPENDENT UNIT AGGREGATION

375

25 Effectiveness of the different cable net on the same beam structure 26 Physical model of a

dependent cablenet systems. Model 1

27 Physical model of a interdependent cablenet systems. Model 2

CITA Complex Modelling

376

INFORMATION RICH DESIGN PRACTICES

LOGIC RESPONSIBLE CABLES INTERDEPENDENT ASSEMBLY

2016-02-03T15:49:51

LACE WALL

LOGICCABLES RESPONSIBLE CABLES LOGIC RESPONSIBLE INTERDEPENDENT ASSEMBLY INTERDEPENDENT ASSEMBLY

2016-02-09T14:51

LOGIC RESPONSIBLE CABLES INTERDEPENDENT ASSEMBLY a

bab -+

ab +

ab -+

bab++

ab++

LOGIC RESPONSIBLE CABLES INTERDEPENDENT ASSEMBLY

LOGIC RESPONSIBLE CABLES a+ INTERDEPENDENT ASSEMBLY 2016-02-03T12:04:54

ab +

a 2016-02-09T14 a+

2016-0

a + ***next step is to build a claster***next step is ittoworks build aand claster components "b+" and "b-" workcomponents together in a"b+" pairand "b-" work together in a pair ans see how out the gaps between grid ofa "a" components see if there is any material to fill out the gaps betweena gridtooffill"a" components aa redundancy - see if there is any material redu a+

a +a -

additional element additional (3) element brings a(3) gives stability to stability to the element 2. element 2. material behaviour: whole material behavior: leaning to the side, structure is leaning to the side, need an need an opposite counter tension

a- b+

ba+- b + a+ a

assembly tiling

ASSEMBLY INSTRUCTIONS

by mirroring the pair type, the counter tension is pair type mirrored, achieved sois both pair are holding each other in balance both pairs are counter

balancing each other

totoreduce redundancy the second reduce redundancy in theinsecong row, row, twocomponents components areare replaces with one thatone two replaced with is having two simmetrical offsprings offsprings that is having two simmetrical

a a

b +a

three of them to "close the

ba -

b +a

When working with textile logics, the order of bending and combining the single units informs the structural performance and shape of the overall assembly. We represent the steps towards the formation of complex textile aggregates with a digital notation system which we developed for the digital design workflow. The use of this system allows us to simultaneously communicate formation process and simulate the geometrical outcome of these.

are corner co

three of them are needed

opposite counter tension

link between pairs

growth in the to X direction a + and a b the edge" "close

DEPENDENT UNIT AGGREGATION

377

a + and a are corner a - condition comp

a a

component a (two tails) cana be component (twoused tails) can be the structure to grow in U a for the structure for to grow in U and V directio

28 Growth direction in the

interdependent unit based system

29 Sequence in the interdependent unit based systems

growth in both X and Y direction

In the process of working with the highly interdependent systems it was observed the nessesity to have several unit types in order toachieve tilable connection.

CITA Complex Modelling

without third component and without a third component and cable the cable network is not stable network the pair is not stable by itself.

puzzling logic a+

growt

explosion diagram for the tiling principle

growth of the field

378

INFORMATION RICH DESIGN PRACTICES

LOGIC RESPONSIBLE CABLES INTERDEPENDENT ASSEMBLY

2016-02-03T15:49:51

LACE WALL

LOGICCABLES RESPONSIBLE CABLES LOGIC RESPONSIBLE INTERDEPENDENT ASSEMBLY INTERDEPENDENT ASSEMBLY

2016-02-09T14:51

LOGIC RESPONSIBLE CABLES INTERDEPENDENT ASSEMBLY a

bab -+

ab +

ab -+

bab++

ab++

LOGIC RESPONSIBLE CABLES INTERDEPENDENT ASSEMBLY

LOGIC RESPONSIBLE CABLES a+ INTERDEPENDENT ASSEMBLY 2016-02-03T12:04:54

ab +

a 2016-02-09T14 a+

2016-0

a +a -

a- b+

ba+- b + a+ a

assembly tiling

ASSEMBLY INSTRUCTIONS

by mirroring the pair type, the counter tension is pair type mirrored, achieved sois both pair are holding each other in balance both pairs are counter

balancing each other

a a

b +a

three of them to "close the

ba -

b +a

are corner co

three of them are needed

opposite counter tension

link between pairs

growth in the to X direction a + and a b the edge" "close

DEPENDENT UNIT AGGREGATION

377

a + and a are corner a - condition comp

a a

component a (two tails) cana be component (twoused tails) can be the structure to grow in U a for the structure for to grow in U and V directio

28 Growth direction in the

interdependent unit based system

29 Sequence in the interdependent unit based systems

growth in both X and Y direction

In the process of working with the highly interdependent systems it was observed the nessesity to have several unit types in order toachieve tilable connection.

CITA Complex Modelling

without third component and without a third component and cable the cable network is not stable network the pair is not stable by itself.

puzzling logic a+

growt

explosion diagram for the tiling principle

growth of the field

378

top view top view top view top view

top view top view

LACE WALL

top view top view

INFORMATION RICH DESIGN PRACTICES

2016-02-16T11:16:21 perspective view 2016-02-16T11:16:21 2016-02-16T11:16:21 2016-02-16T11:16:21 2016-02-16T11:16:21 2016-02-16T11:16:21 perspective view 2016-02-16T11:16:21 perspective viewview perspective perspective view view perspective 2016-02-16T11:16:21

2016-02-17T16:04:39 2016-02-17T16:

2016-02-17T16:04:0

a a+

Excercise 1: pair configuration A and A+ with cable net configuration 01

perspective view

top view

perspective view perspective view

single interdependent unit, without being fixed to surface is having a trouble to keep in shape

C: CLenF: 0.83, CStr:C:300 CLenF: 0.83, CStr: 300 B: SpStr: 5000, BStr:190.49, B: SpStr:BAng: 5000,1.0 BStr:190.49, BAng: 1.0

2016-02-17T16:0

Excercise 2: pair configuration A and A+ with cable net configuration 02

2016-02-17T16:05:53 2016-02-17T16:05

a row of interdependent units, performing a curling of the surface based on the modification of cable net configuration

379

2d array of interdependent units, which gain stability from being â&#x20AC;&#x153;intewovenâ&#x20AC;? one to another

- a +- a

-a+

2016-02-17T16:05:53

a a +CStr: 266 C: CLenF: 0.84, C: CLenF: 0.84, CStr: 266 group B: SpStr: 5000, BStr:190.49, B: SpStr: BAng: 5000, 1.0BStr:190.49, BAng: 1.0 -a -a+

*PHYSICAL *PHYSICAL PROTOTYPE PROTOTYPE AS A REFERENCE AS A REFERENCE

C: CLenF: 0.83, CStr: 300 B: SpStr: 5000, BStr:190.49, BAng: 1.0

C: CLenF: 0.84, CStr: 266 B: SpStr: 5000, BStr:190.49, BAng: 1.0

30 Sequence of the unit aggregation 31 Variations of the arrays

Excercise 3: configuration A and A+ (double pair)

2016-02-17T16:06:12 2016-02-17T16

Excercise 4: array build up from above pair configurations

CITA Complex Modelling

a row of interdependent units, performing a better stability than a single element

a +a

-a

2016-02-17T16:06:12

The design integrated simulation tool allows for rapid investigation of the effect that changes on unit level have on the macro shape of larger assemblies. We find that even small changes on the quantity and position of connections, the assemblies underlying tiling patterns or operations such as mirroring the topologies of the FAHS units or cable nets have large effects on the shape and performance across many units. Working with design integrated simulation of material behaviour allows us to speed up digital design iterations. More interestingly the tools allows us to design on a conceptual meta level with material behaviour. Instead of taming small deviations in material and connections, as in physical FAHS assemblies, we are able to observe whether and how hybrid structures find an equilibrium on macro scale. The parallel design inquiry in digital and physical models allows us to speculate and to evaluate across different forms of representation. In the end of our initial explorative design phase we conclude that dependent unit aggregations are too laborious, in terms of design and assembly, and challenging, in terms of computational representation and communication to the assembly team. We decide therefore to build Lace Wall from a system of discrete units with beam based connection details.

*PHYSICAL PROTOTYPE AS A REFERENCE

DISCRETIZING ASSEMBLIES

380

top view top view top view top view

top view top view

LACE WALL

top view top view

INFORMATION RICH DESIGN PRACTICES

2016-02-17T16:04:39 2016-02-17T16:

2016-02-17T16:04:0

a a+

Excercise 1: pair configuration A and A+ with cable net configuration 01

perspective view

top view

perspective view perspective view

single interdependent unit, without being fixed to surface is having a trouble to keep in shape

C: CLenF: 0.83, CStr:C:300 CLenF: 0.83, CStr: 300 B: SpStr: 5000, BStr:190.49, B: SpStr:BAng: 5000,1.0 BStr:190.49, BAng: 1.0

2016-02-17T16:0

Excercise 2: pair configuration A and A+ with cable net configuration 02

2016-02-17T16:05:53 2016-02-17T16:05

a row of interdependent units, performing a curling of the surface based on the modification of cable net configuration

379

2d array of interdependent units, which gain stability from being â&#x20AC;&#x153;intewovenâ&#x20AC;? one to another

- a +- a

-a+

2016-02-17T16:05:53

a a +CStr: 266 C: CLenF: 0.84, C: CLenF: 0.84, CStr: 266 group B: SpStr: 5000, BStr:190.49, B: SpStr: BAng: 5000, 1.0BStr:190.49, BAng: 1.0 -a -a+

*PHYSICAL *PHYSICAL PROTOTYPE PROTOTYPE AS A REFERENCE AS A REFERENCE

C: CLenF: 0.83, CStr: 300 B: SpStr: 5000, BStr:190.49, BAng: 1.0

C: CLenF: 0.84, CStr: 266 B: SpStr: 5000, BStr:190.49, BAng: 1.0

30 Sequence of the unit aggregation 31 Variations of the arrays

Excercise 3: configuration A and A+ (double pair)

2016-02-17T16:06:12 2016-02-17T16

Excercise 4: array build up from above pair configurations

CITA Complex Modelling

a row of interdependent units, performing a better stability than a single element

a +a

-a

2016-02-17T16:06:12

*PHYSICAL PROTOTYPE AS A REFERENCE

DISCRETIZING ASSEMBLIES

380

LACE WALL

INFORMATION RICH DESIGN PRACTICES

tile

box

unit

Empty rectangles between units A+ A+ A+ A+

Empty rectangles between piar rows A+ A+ A+ A+ Distribution of elements in 3D

DESIGNING COMPLEX ARRAYS PREREQUISITES In order to understand and design the arrays of the beam units with complex topologies a simplification into box-like geometry was undertaken. This representation introduced a metalevel, which enabled the exploration of fundamental tiling principles and positions of joints. In order to have a common and explicit language we introduced a terminology for our approach with the following definitions: • A tile: the tile is the highest of the hierarchical relations and is understood as a two dimensional rhomboid shape that easily packs into a packing system • A box: the box is a volumetric representation of the unit that fits around the rhomboid while giving it spatial depth • A unit: the units is the actual polyline beam configuration

Empty rectangles between pairs and rows A+ A- A+ A-

381

Puzzling of the volumetric rombo units

Shift of the vertical rows A+ A+ A+ A+

32 Tiling principles on the

level of a tile, box and unit

33 Process of building up the array

CITA Complex Modelling

Empty rectangles between double pairs A+ A- A+ A-

382

LACE WALL

INFORMATION RICH DESIGN PRACTICES

tile

box

unit

Empty rectangles between units A+ A+ A+ A+

Empty rectangles between piar rows A+ A+ A+ A+ Distribution of elements in 3D

Empty rectangles between pairs and rows A+ A- A+ A-

381

Puzzling of the volumetric rombo units

Shift of the vertical rows A+ A+ A+ A+

32 Tiling principles on the

level of a tile, box and unit

33 Process of building up the array

CITA Complex Modelling

Empty rectangles between double pairs A+ A- A+ A-

382

INFORMATION RICH DESIGN PRACTICES

process

LACE WALL

6 process

process

process 1

data

process 5

data

process

data

defining assembly topology

process

defining assembly dimensions

process data

MODELLING PIPELINE

shaped geometry

The digital model in Lace Wall has to integrate feedback from multiple sources and serve multiple purposes in the areas of design, analysis and fabrication. In order to achieve this we introduce a new modelling paradigm: Rather than storing geometry of the elements we encode the properties and relationships between the objects in our system. For this we use a graph based data structure, which serves as the base for different model outputs: A polygon representation is used to add, delete and alter the relationships interactively Fast and close to physically correct shapes with analysis of geometrical properties (curvature, simple bending forces) are determined on the fly through the implementation of the Kangaroo2 (K2) dynamic relaxation solver. Physically correct form finding and structural analysis takes place through K2E Graph representation for Topology analysis Specification of fabrication information for rods and cable nets Data level - allows for coding for generation of new topologies, optimisation and interaction with Machine Learning

K2 forces visualisation

0C 245 0 > 180

1C 180 0 > 180

0 > 181

8C 369

0 > 235

0 > 181

0 > 3159

0 > 1084

9C 284

11C 235

284 > 181

0 > 3159

0 > 4676

13B 5528

12C 369

180 > 235

10C 181

0 > 3888

0 > 4799

0 > 4676

0 > 235

0 > 284

284 > 181

180 > 369

4C 180

7C 235

6C 181

245 > 369

0 > 180

180 > 235

5C 284

2C 180

0 > 369

180 > 369

3C 180 0 > 284

245 > 180

2910-3159 > 5528-5278 0-239 > 2755-2515

0 > 1084

0 > 3888

0 > 4799

4613-4862 > 4862-4613 1703-1943 > 811-1051 811-1051 > 1703-1943

14B 5528

which are derived from the underlying graph data structure

35 Modelling pipeline diagram 36 Detailed fabrication data

is extracted from the graphs

2910-3159 > 5528-5278 0-239 > 2755-2515

160824_0953_GenGenome8_WedgeAngle5p01_ID10

/ 383

34 Range of visualisation,

assembly graph

cable net fabrication labeling

CITA Complex Modelling

DESIGNING AND REPRESENTING BEHAVIOUR IN MATERIAL SYSTEMS

384

INFORMATION RICH DESIGN PRACTICES

process

LACE WALL

6 process

process

process 1

data

process 5

data

process

data

defining assembly topology

process

defining assembly dimensions

process data

MODELLING PIPELINE

shaped geometry

K2 forces visualisation

0C 245 0 > 180

1C 180 0 > 180

0 > 181

8C 369

0 > 235

0 > 181

0 > 3159

0 > 1084

9C 284

11C 235

284 > 181

0 > 3159

0 > 4676

13B 5528

12C 369

180 > 235

10C 181

0 > 3888

0 > 4799

0 > 4676

0 > 235

0 > 284

284 > 181

180 > 369

4C 180

7C 235

6C 181

245 > 369

0 > 180

180 > 235

5C 284

2C 180

0 > 369

180 > 369

3C 180 0 > 284

245 > 180

2910-3159 > 5528-5278 0-239 > 2755-2515

0 > 1084

0 > 3888

0 > 4799

4613-4862 > 4862-4613 1703-1943 > 811-1051 811-1051 > 1703-1943

14B 5528

which are derived from the underlying graph data structure

35 Modelling pipeline diagram 36 Detailed fabrication data

is extracted from the graphs

2910-3159 > 5528-5278 0-239 > 2755-2515

160824_0953_GenGenome8_WedgeAngle5p01_ID10

/ 383

34 Range of visualisation,

assembly graph

cable net fabrication labeling

CITA Complex Modelling

DESIGNING AND REPRESENTING BEHAVIOUR IN MATERIAL SYSTEMS

384

0 > 300

293 > 300 INFORMATION RICH DESIGN PRACTICES

3C 248

11C 156

LACE WALL

> 185

0 > 329

0 > 174

1C 300

248 > 329

0C 293

0 > 174

0 > 290

3C 248

12C 290

0 > 156

7C 241

0 > 159

241 > 156

9C 159

0 > 2169

> 185

0>290 0 > 290

6C 174 0 > 241

0 > 329

0>4067

8C 241 0 > 156

0 > 4067 0 > 5231

241 > 156

0>2415 0 > 2415

0 > 5231

0>0

17C 156

0 > 6442

0>6442

0>2169 0 > 2169

0 > 6442

21B 7366

0 > 15690>967 0>0 0 > 967

0 > 290 0 > 6442

13C 329 17C

0 > 967

0-258 > 3545-3286 3964-4192 > 7366-7138

2169-2708 > 967-1506 6202-6681 > 6681-6202 967-1506 > 2169-2708

156

16C 185

8C 241 18C

0 > 6442

0 > 1213

0 > 4067

0 > 185

15C 159

0>1569 0 > 1569

16C 185

0-258 > 3545-3286 3964-4192 > 7366-7138

0 > 6442

174 > 290

0-258 > 3545-3286 3964-4192 > 7366-7138

0 > 967

0 > 156

12C 290

21B 7366

0 > 967

0-258 > 3545-3286 3964-4192 > 7366-7138

0 > 1213

0 > 2415

0 > 6442

0 > 6442 0 > 5231

159 > 185

black node: beam. 21 - the item number in the list, B - beam. 7366 - the length of the element in mm.

0 > 241

0 > 967

0 > 2415

0 > 2169

22B 7366

0>4067

0>5231 0 > 5231

241 > 156

CableNetwork_FormFound_ID21

0 > 2169

16C 185

0 > 159

15C 159

21B 7366 0 > 6442

17C 18C 156 290

19C 329

159 > 185

0>6442

2C 300

0 > 1569

2169-2708 > 967-1506 6202-6681 > 6681-6202 967-1506 > 2169-2708

CableNetwork_FormFound_ID21 0-258 > 3545-3286 3964-4192 > 7366-7138

0 > 156

300 > 567

BEYOND GEOMETRIES 0 > 1213 GRAPH REPRESENTATION OF DATA

4C 248

For the development of Lace Wall it was important to analyse and evaluate the topologies of the elements. However visually analysing assembly topology is difficult and provides 0 > 2415 no objective data by which to differentiate assemblies and steer design space search. As we 0 > a174 248 > 329 use graph based data structure we are able 0 > 4067 to represent topologies in a non-geometric format. In discrete mathematics, a graph is an abstract construct consisting of nodes, where some 0 > 2169 pairs of these are connected by edges. Nodes describe the objects of a network and their 0 > 290 properties, edges describe how nodes connect and the properties of these connections. In our assembly graphs, nodes represent structural elements and edges their physical connections. Nodes have two properties (element type and length) and edges have two (where along the elements the connection occurs). The> 290 directed graph class of the NetworkX 0 > 241 174 Python module is implemented as the base representation. This enables us to analyse assemblies for graph theoretical measures such as size, connectedness, node degree, centrality and cycles and to arbitrarily add properties to nodes/edges 0-258 > 3545-3286 3964-4192 > 7366-7138 In order to visualise the relationships within and between elements our data structures are translated to DOT graph language notation can be compiled to an image using GraphViz which is rendered in the Rhino viewport. This occurs automatically and enables the designer to visualise the topology using different graph layout algorithms (hierarchical, force-directed 0 > 159 etc).

22B 8C 7366 241

2169-2708 > 967-1506 6202-6681 > 6681-6202 967-1506 > 2169-2708

241 > 156

0 > 5231

6C 174

0 > 2169

22B 07366 > 4067

293 > 567

159 > 185

290

0 > 185

0 > 4067

0 > 248

174 > 290 174>290

248 > 329

14C 567 174 > 290

19C 329

20C 567

0 > 241 0>241

248 > 329 10C 185

0 > 290 300 > 567

0 > 159

0>156 0>0 0 > 1569

293 > 567

0 > 329

0 > 290

0 > 156

0>5231

15C 159

0 > 185

0 > 567

0>159

0>156

0 > 4067

11C 6442156

0 > 174

5C 174

13C 329

12C 290

0 > 156

4C 248

0 > 174

174 > 290

159 > 185

0 > 1213

0 > 2415

300 > 567

14C 567

248 > 329

241 > 156

0 > 185

0>1213

0 > 967

0 > 241

300>567

241 > 156

248 > 329

293>567

0 > 248

248>329

0 > 174

5C 174

0>0

300 > 567

0 > 329

0 > 6442

6C300 174

0 > 567

0 3C > 248 0>329 248

0>174

174 > 290

11C 156

0>248

0 > 329

293 > 300

0>567

0 > 1569

0 > 248

white node: cable. 3 - the item number in the list, C - cable. 248 - the length of the element in mm.

0 > 2415

7C 241

1C 300

13C 329

20C 567

293>300

0 > 300

5C 174

4C 248

arrow: connection data between elements. 0>240 means that element 6C is connecting to element 8C at 0 > 5231 th 0 point of 6C and at 241 point of 8C

0>300

0 > 241

CITA Complex Modelling

14C 567

18C 290

0 > 1569 0 > 329

20C 567

0.0-1.5 0.0-10.5 3.0-22.5

3.0-1.5

0.0-4.5 0.0-10.5 3.0-16.5 3.0-22.5 0.0-4.5 0.0-10.5 3.0-16.5 3.0-22.5

19C 329

0.0-3.2

0.0-1.1

2.1-1.5 2.1-1.5 0.0-7.5 0.0-1.5 3.0-1.5 4.2 - 1.5 2.4-19.5 0.0-7.5 3.0-1.5 0.0-1.5 4.2 - 1.5

37 GraphViz visualisation

for a complex assemply

38 Graph representation of one of the final units

2.4-19.5

0.0-4.5 0.0-10.5 3.0 - 16.5 3.0 - 1.5 0.0-10.5 3.0 - 1.5

39 Evolution of graph complexity

0.0-4.5 3.0 - 16.5

/ 385

CableNetwork_FormFound_ID21 386

11C

0 > 5231

241 > 156

0 > 185

15C

0 > 4067

0 > 300

293 > 300 INFORMATION RICH DESIGN PRACTICES

3C 248

11C 156

LACE WALL

> 185

0 > 329

0 > 174

1C 300

248 > 329

0C 293

0 > 174

0 > 290

3C 248

12C 290

0 > 156

7C 241

0 > 159

241 > 156

9C 159

0 > 2169

> 185

0>290 0 > 290

6C 174 0 > 241

0 > 329

0>4067

8C 241 0 > 156

0 > 4067 0 > 5231

241 > 156

0>2415 0 > 2415

0 > 5231

0>0

17C 156

0 > 6442

0>6442

0>2169 0 > 2169

0 > 6442

21B 7366

0 > 15690>967 0>0 0 > 967

0 > 290 0 > 6442

13C 329 17C

0 > 967

0-258 > 3545-3286 3964-4192 > 7366-7138

2169-2708 > 967-1506 6202-6681 > 6681-6202 967-1506 > 2169-2708

156

16C 185

8C 241 18C

0 > 6442

0 > 1213

0 > 4067

0 > 185

15C 159

0>1569 0 > 1569

16C 185

0-258 > 3545-3286 3964-4192 > 7366-7138

0 > 6442

174 > 290

0-258 > 3545-3286 3964-4192 > 7366-7138

0 > 967

0 > 156

12C 290

21B 7366

0 > 967

0-258 > 3545-3286 3964-4192 > 7366-7138

0 > 1213

0 > 2415

0 > 6442

0 > 6442 0 > 5231

159 > 185

black node: beam. 21 - the item number in the list, B - beam. 7366 - the length of the element in mm.

0 > 241

0 > 967

0 > 2415

0 > 2169

22B 7366

0>4067

0>5231 0 > 5231

241 > 156

CableNetwork_FormFound_ID21

0 > 2169

16C 185

0 > 159

15C 159

21B 7366 0 > 6442

17C 18C 156 290

19C 329

159 > 185

0>6442

2C 300

0 > 1569

2169-2708 > 967-1506 6202-6681 > 6681-6202 967-1506 > 2169-2708

CableNetwork_FormFound_ID21 0-258 > 3545-3286 3964-4192 > 7366-7138

0 > 156

300 > 567

BEYOND GEOMETRIES 0 > 1213 GRAPH REPRESENTATION OF DATA

4C 248

22B 8C 7366 241

2169-2708 > 967-1506 6202-6681 > 6681-6202 967-1506 > 2169-2708

241 > 156

0 > 5231

6C 174

0 > 2169

22B 07366 > 4067

293 > 567

159 > 185

290

0 > 185

0 > 4067

0 > 248

174 > 290 174>290

248 > 329

14C 567 174 > 290

19C 329

20C 567

0 > 241 0>241

248 > 329 10C 185

0 > 290 300 > 567

0 > 159

0>156 0>0 0 > 1569

293 > 567

0 > 329

0 > 290

0 > 156

0>5231

15C 159

0 > 185

0 > 567

0>159

0>156

0 > 4067

11C 6442156

0 > 174

5C 174

13C 329

12C 290

0 > 156

4C 248

0 > 174

174 > 290

159 > 185

0 > 1213

0 > 2415

300 > 567

14C 567

248 > 329

241 > 156

0 > 185

0>1213

0 > 967

0 > 241

300>567

241 > 156

248 > 329

293>567

0 > 248

248>329

0 > 174

5C 174

0>0

300 > 567

0 > 329

0 > 6442

6C300 174

0 > 567

0 3C > 248 0>329 248

0>174

174 > 290

11C 156

0>248

0 > 329

293 > 300

0>567

0 > 1569

0 > 248

white node: cable. 3 - the item number in the list, C - cable. 248 - the length of the element in mm.

0 > 2415

7C 241

1C 300

13C 329

20C 567

293>300

0 > 300

5C 174

4C 248

arrow: connection data between elements. 0>240 means that element 6C is connecting to element 8C at 0 > 5231 th 0 point of 6C and at 241 point of 8C

0>300

0 > 241

CITA Complex Modelling

14C 567

18C 290

0 > 1569 0 > 329

20C 567

0.0-1.5 0.0-10.5 3.0-22.5

3.0-1.5

0.0-4.5 0.0-10.5 3.0-16.5 3.0-22.5 0.0-4.5 0.0-10.5 3.0-16.5 3.0-22.5

19C 329

0.0-3.2

0.0-1.1

2.1-1.5 2.1-1.5 0.0-7.5 0.0-1.5 3.0-1.5 4.2 - 1.5 2.4-19.5 0.0-7.5 3.0-1.5 0.0-1.5 4.2 - 1.5

37 GraphViz visualisation

for a complex assemply

38 Graph representation of one of the final units

2.4-19.5

0.0-4.5 0.0-10.5 3.0 - 16.5 3.0 - 1.5 0.0-10.5 3.0 - 1.5

39 Evolution of graph complexity

0.0-4.5 3.0 - 16.5

/ 385

CableNetwork_FormFound_ID21 386

11C

0 > 5231

241 > 156

0 > 185

15C

0 > 4067

INFORMATION RICH DESIGN PRACTICES physical model

LACE WALL

initial digital shaping model

Tag of the point where cables and beams meet

baked geo from pipeline, zombi solver

pointcloud from the scan

points from 3D scan

points from 3D scan with assigned tags

overlayed digital model input with physical scan output

COMPARISON OF A DIGITAL AND PHYSICALLY BUILD UNIT

input polyline geo + scanned points

CITA Complex Modelling

Galapagos solver

initial poly with default genepool parameters

shaped 3D cables vs. 3D scanned points

387

Key in the development of Lace Wall was the synchronisation and calibration of the digital and physical models. We constantly aimed to find a good compromise between precision and speed in the simulation and dismissed e.g. designs, which could not be modelled sufficiently enough for digital simulation. However in systems like Lace Wall, there will always be a difference between the behaviour of the physical model and the simulated on. In order to identify deviations and calibrate the digital models with the built units we developed 3D scanning methods in. In these we align the 3D scanned point cloud roughly with the 3D model of the simulated unit. The challenge in this comparison is the lack of a ground truth, as both physical and digital model are form found. We use the topology of the cablenet as the common denominator between the models. Especially as the cables and their branching points can be quite well identified. These points are labelled in both models with a corresponding order. Afterwards the Galapagos Search Engine is used in order to align the models and finally extract the deviations between the points, which was e.g. in the range of 1-2 cm for a 100cm large unit. The ascertained deviation is then used to calibrate the digital simulation.

initial poly shaped into cables mathing state with target genepool parameters

average position between shaped end cable points and 3D scanned ones

new cable net is drawn inbetween fitnessed points and a new set of parameteres is generated

resulting genenom can be plugged back in a feedback loop to the shaping in order to shape again through the pipeline the model which is now closer to the real physical model 40

Cable network traced from the scan

3D scan of the unit with overlayed tags

40 3D scanning excercise 41 Exploded diagram of a

3D-scanned model

42 Physically build component compared to digital target model

input polyline geometry

3D SCANNING AS A TOOL EVALUATION

388

INFORMATION RICH DESIGN PRACTICES physical model

LACE WALL

initial digital shaping model

Tag of the point where cables and beams meet

baked geo from pipeline, zombi solver

pointcloud from the scan

points from 3D scan

points from 3D scan with assigned tags

overlayed digital model input with physical scan output

COMPARISON OF A DIGITAL AND PHYSICALLY BUILD UNIT

input polyline geo + scanned points

CITA Complex Modelling

Galapagos solver

initial poly with default genepool parameters

shaped 3D cables vs. 3D scanned points

387

initial poly shaped into cables mathing state with target genepool parameters

average position between shaped end cable points and 3D scanned ones

new cable net is drawn inbetween fitnessed points and a new set of parameteres is generated

resulting genenom can be plugged back in a feedback loop to the shaping in order to shape again through the pipeline the model which is now closer to the real physical model 40

Cable network traced from the scan

3D scan of the unit with overlayed tags

40 3D scanning excercise 41 Exploded diagram of a

3D-scanned model

42 Physically build component compared to digital target model

input polyline geometry

3D SCANNING AS A TOOL EVALUATION

388

CITA Complex Modelling

LACE WALL

INFORMATION RICH DESIGN PRACTICES

43 Manual assembly of the single unit from 6mm GFRP rod and polyester prefabricated cable nets

389

44 Plan and perspective view of the digitally designed spatial unit

390

CITA Complex Modelling

LACE WALL

INFORMATION RICH DESIGN PRACTICES

43 Manual assembly of the single unit from 6mm GFRP rod and polyester prefabricated cable nets

389

44 Plan and perspective view of the digitally designed spatial unit

390

LACE WALL

INFORMATION RICH DESIGN PRACTICES

Rope wire cutter tool

Nylon Rings

Ultra Sonic Welder

BUILDING TECTONICS CITA Complex Modelling

FOR HYBRID STRUCTURES 46

Woven polyester belts

391

45 Instruments necessary for fabrication of a cablenet 46 Beam to Beam

connectors, cnc-milled from HDPE plastic

47 Cable-to-Beam connectors, cnc-milled from HDPE plastic

The development of details that connect and hold the rods and cablenet precisely, while also being fast to produce and easy to assemble, played an important role in the project. Details are milled from HDPE (High Density PolyEthylene) which allows us to use that materials inherent flexibility and strength. All details follow a snap-fit logic in which material bending allows the locking of connections on to the fibreglass beams and tightening of the cable net. Details were explored through a series of iterations in which the connection logic, snap fitting and its local tensioning were optimised. The details are divided into three categories: • Beam-to-beam connectors • Cable-to-beam connectors • Cable-to-cable connectors. The development of the details were undertaken in an iterative cycle of design manufacture and load testing.

392

LACE WALL

INFORMATION RICH DESIGN PRACTICES

Rope wire cutter tool

Nylon Rings

Ultra Sonic Welder

BUILDING TECTONICS CITA Complex Modelling

FOR HYBRID STRUCTURES 46

Woven polyester belts

391

45 Instruments necessary for fabrication of a cablenet 46 Beam to Beam

connectors, cnc-milled from HDPE plastic

47 Cable-to-Beam connectors, cnc-milled from HDPE plastic

392

LACE WALL

INFORMATION RICH DESIGN PRACTICES

S-shape clamp with a single pin lock

S-shape clamp with a double pin lock

BEAM-TO-BEAM CONNECTORS An key detail in Lace Wall is the connection of two parallel rods. This detail is prevalent at several places in each discrete element and in the connection of these elements into the macro structure. There are multiple challenges: the general slipperiness of the GFRP rods, which hampers friction based joints; the sheer amount of joints, which impedes glued joints; and the brittleness of the GFRP, which would be fractured when screw or bolts would be used as fasteners. Further design requirements are quick assembly and manufacture with as little material use as possible. Though difficult to achieve friction based joints seemed the most promising path. Several design iterations explored possible snap fit and puzzle joints. However all of these showed, that the forces needed to create a friction based ´connection could not be established through the springback of the plastic. This was especially true, as the model assumption of “parallel rods” hardly emerged in reality. The forces in the rods would rather induce a twisting rotation and forces, which would pull joints apart. In conclusion additional fastening was required, which led to the development of a U-shape joint that could be tightened through battery driven screw drivers.

8-Shape single piece clamp

S-Shape clamp with smoother design

Horse-shoe clamp with the screw solution

393

48 Development of the

beam-to-beam connectors

49 Beam-to-beam connectors within the same beam - in the loop formation 50 Photos of the beam-to-

beam connectors prototypes

CITA Complex Modelling

Two part Puzzle solution

394

LACE WALL

INFORMATION RICH DESIGN PRACTICES

S-shape clamp with a single pin lock

S-shape clamp with a double pin lock

8-Shape single piece clamp

S-Shape clamp with smoother design

Horse-shoe clamp with the screw solution

393

48 Development of the

beam-to-beam connectors

49 Beam-to-beam connectors within the same beam - in the loop formation 50 Photos of the beam-to-

beam connectors prototypes

CITA Complex Modelling

Two part Puzzle solution

394

LACE WALL

INFORMATION RICH DESIGN PRACTICES

395

Cable to beam and cable to cable connections provide answers to situations where only tension forces occur and no moment forces need to be transmitted. Tests showed, that the cablenets had generally a very good fit and would self adjust in terms of the inner angles between cables and in regards to the location of their connection to the beams. In some cases an adjustment of the terminal cables length was necessary though. A snap-fit hook was chosen in order to facilitate easy on-site assembly and support the challenge of sequencing assembly in a rational way. To organise the connection between cables, a closed nylon ring was sufficient for stability and strength in the highly tensioned cable networks.

51 Development of the

cable-to-beam connections

52 Deassambalable ring variations 53 Plexi-glass details for

early stage cable nets

CITA Complex Modelling

CABLE-TO-BEAM AND BEAM-TO-BEAM CONNECTORS

396

LACE WALL

INFORMATION RICH DESIGN PRACTICES

395

51 Development of the

cable-to-beam connections

52 Deassambalable ring variations 53 Plexi-glass details for

early stage cable nets

CITA Complex Modelling

CABLE-TO-BEAM AND BEAM-TO-BEAM CONNECTORS

396

CITA Complex Modelling

LACE WALL

INFORMATION RICH DESIGN PRACTICES

S-shape clamp for beam to beam connection with the screw connection

Hook for cable to beam connections

Two-component puzzle clamp for beam to beam connection

Horse-shoe clamp for beam to beam connection

8-shape clamp for beam to beam self connection (to form a loop)

3D AXIS CNC MILLING OF CONNECTION DETAILS

397

All the details were prototyped and fabricated in house at the CITA Fabrication Lab on two 3 axis milling machines. The milling strategy was developed in accordance to the large amount of details and the complexity and detail of the designs.

S shape clamp for beam to beam connection

54 Milling path of the

prorotyped details for Lace Wall

55 Nested details on the sheet 56 Milling process

Horse-shoe clamp for beam to base connection (attach to the base metal rim)

398

CITA Complex Modelling

LACE WALL

INFORMATION RICH DESIGN PRACTICES

S-shape clamp for beam to beam connection with the screw connection

Hook for cable to beam connections

Two-component puzzle clamp for beam to beam connection

Horse-shoe clamp for beam to beam connection

8-shape clamp for beam to beam self connection (to form a loop)

3D AXIS CNC MILLING OF CONNECTION DETAILS

397

S shape clamp for beam to beam connection

54 Milling path of the

prorotyped details for Lace Wall

55 Nested details on the sheet 56 Milling process

Horse-shoe clamp for beam to base connection (attach to the base metal rim)

398

SYSTEM 1 Single unit based system

Cable net 3d

LACE WALL

Cable net 3d

3 1

0.085316

0.08083

6 0.085

0.080

0.08083

0.077582

0.085316

0.077 5

0.095 0.08393 0.095287

0.189

0.189 0.100

0.069

0.138789

11 0.074468

0.112519 0.119226 5 11 0.189252 0.074468

0.100662

0.138789

10 8

0.111316

0.207508

0.112519

0.069 0.119226 0.189252

Attach the open cable from previous unit in the middle over here

0.098315 0.13354

10 0.083535 0.111316 8 0.117624 0.057589

0.100 0.112519 0.207

0.069

Attach the open cable from previous

anchored row Anchorslast for the last row to support Anchors for the last row to support Duethe to inderdependency of units Due to inderdependency of units due to interdependency condition

0.119

0.207

0.074 11 To the next unit

0.207508

10 0.083535 8 0.117624 0.057589

0.111

0.118

0.057 Cable net unrolled flat with the target beam locations and length

0.098

0.124685 4

0.133

0.118

0.057 0.117 0.098

0.124

0.117 0.083 0.133

7 0.256231

0.132578

total len: 2.938074

Cable net unrolled flat with the target beam locations total len: 2.938074 and length

0.256231

0.256

0.132578

0.256

0.132578

Cable Cable cables, Represented by nylon polyester Represented by nylon polyester 12mm nylon textile band 12 mm textile band 12 mm polyester band

0.083

0.124 10

beams, Beam Beam GFRPRepresented 4mm by GFRP rod 4mm Represented by GFRP rod 4mm

To the next unit

0.118884

0.098315 0.13354

0.124685 4

0.083

0.069

0.074 unit11in the middle over here

Cable net unrolled flat with the target beam locations and length

0.118884 10

0.095 0.119

0.083 0.095287

0.100662

0.112519

0.085

0.080

0.077

0.077582

0.08393

INFORMATION RICH DESIGN PRACTICES

Cable net unrolled flat Cable net unrolled flat with the target beam locations with the target beam locations and length and length

0.132578

Single unit based system

Single unit based system Array 5*4 Single unit based system Form found geometry Shaped output Array 5*4 Top view

SYSTEM 1 SYSTEM 1 92 Single unit based systemArray 5*49unit based system Single Polyline input geometry Polyline Polyline input geometry input Array 5*4 Array 5*4

Top view

Single unit based system Form found geometry Array 5*4

3 0

0.029474

0.029474 0.454825

11 7

0.085 0.215177

0.080 0.454825

11 3

0.242955 0.215177

0.077

0.242955 0.273641

6 0.165487 0.273641

65 0.249899 0.165487

8 0.096634

0.249899 0.115132

4 5

8 0.096634

0.115132

0.647193

10 0.447658

0.447658

0.095

CITA Complex Modelling

0.083 10

0.189

0.119 0.100

0.069

Unrolled beam with the points Unrolled where cables beam with are to thebepoints attached where cables are to be attached 0.112519 attach the open cable from the Attach the open cable from previous previous unitunitinin the middle over the middle over here here

0.069

0.207 0.074 11

to the unit To thenext next unit

0.118884

083535 8 0.117624 0.057589

0.111

cable net unrolled flat with the target beams location tagsflatand Cable net unrolled with the target beam locations length and length

0.118

0.057 0.117 0.098

685

0.133

0.083

0.124

10 7 0.256231

0.256

57 Fabrication drawing

0.132578

58 Digital representation of the lace wall unit arrays

Single unit based system Array 5*4 Polyline input

demonstrating planarized cablenet

SYSTEM 1 Single unit based system

400

399

SYSTEM 1 Single unit based system

Cable net 3d

LACE WALL

Cable net 3d

3 1

0.085316

0.08083

6 0.085

0.080

0.08083

0.077582

0.085316

0.077 5

0.095 0.08393 0.095287

0.189

0.189 0.100

0.069

0.138789

11 0.074468

0.112519 0.119226 5 11 0.189252 0.074468

0.100662

0.138789

10 8

0.111316

0.207508

0.112519

0.069 0.119226 0.189252

Attach the open cable from previous unit in the middle over here

0.098315 0.13354

10 0.083535 0.111316 8 0.117624 0.057589

0.100 0.112519 0.207

0.069

Attach the open cable from previous

anchored row Anchorslast for the last row to support Anchors for the last row to support Duethe to inderdependency of units Due to inderdependency of units due to interdependency condition

0.119

0.207

0.074 11 To the next unit

0.207508

10 0.083535 8 0.117624 0.057589

0.111

0.118

0.057 Cable net unrolled flat with the target beam locations and length

0.098

0.124685 4

0.133

0.118

0.057 0.117 0.098

0.124

0.117 0.083 0.133

7 0.256231

0.132578

total len: 2.938074

Cable net unrolled flat with the target beam locations total len: 2.938074 and length

0.256231

0.256

0.132578

0.256

0.132578

Cable Cable cables, Represented by nylon polyester Represented by nylon polyester 12mm nylon textile band 12 mm textile band 12 mm polyester band

0.083

0.124 10

beams, Beam Beam GFRPRepresented 4mm by GFRP rod 4mm Represented by GFRP rod 4mm

To the next unit

0.118884

0.098315 0.13354

0.124685 4

0.083

0.069

0.074 unit11in the middle over here

Cable net unrolled flat with the target beam locations and length

0.118884 10

0.095 0.119

0.083 0.095287

0.100662

0.112519

0.085

0.080

0.077

0.077582

0.08393

INFORMATION RICH DESIGN PRACTICES

Cable net unrolled flat Cable net unrolled flat with the target beam locations with the target beam locations and length and length

0.132578

Single unit based system

Single unit based system Array 5*4 Single unit based system Form found geometry Shaped output Array 5*4 Top view

SYSTEM 1 SYSTEM 1 92 Single unit based systemArray 5*49unit based system Single Polyline input geometry Polyline Polyline input geometry input Array 5*4 Array 5*4

Top view

Single unit based system Form found geometry Array 5*4

3 0

0.029474

0.029474 0.454825

11 7

0.085 0.215177

0.080 0.454825

11 3

0.242955 0.215177

0.077

0.242955 0.273641

6 0.165487 0.273641

65 0.249899 0.165487

8 0.096634

0.249899 0.115132

4 5

8 0.096634

0.115132

0.647193

10 0.447658

0.447658

0.095

CITA Complex Modelling

0.083 10

0.189

0.119 0.100

0.069

0.207 0.074 11

to the unit To thenext next unit

0.118884

083535 8 0.117624 0.057589

0.111

cable net unrolled flat with the target beams location tagsflatand Cable net unrolled with the target beam locations length and length

0.118

0.057 0.117 0.098

685

0.133

0.083

0.124

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58 Digital representation of the lace wall unit arrays

Single unit based system Array 5*4 Polyline input

demonstrating planarized cablenet

SYSTEM 1 Single unit based system

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WORKSHOP

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Throughout the project period, CITA invited students from CITA Studio to participate in the development phases through small workshops. In one of these students were involved in evaluating how well the automatically generated fabrication instructions for building units worked. The workshop tested different strategies and ways to combine elements. The result was that the hugging unit was considered the most diverse and promising solution and was selected for further development. Throughout the project, student involvement through workshops supported very successful exchanges. The project team received fast and useful input on fabrication data optimisation as well as on the cable net design. In turn, students got experience in designing for and with active bending and with relevant fabrication methods.

59 Built prototype, 4mm GFRP rods 60 Built prototype, 4mm

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61 Photo from the student workshop 62 Photo from the student

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59 Built prototype, 4mm GFRP rods 60 Built prototype, 4mm

GFRP rods

61 Photo from the student workshop 62 Photo from the student

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CM 6

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GENERATIVE CABLENETS COMPUTATIONAL METHODS FOR AUTOMATED DESIGN AND SEARCH

relaxed network

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topological centrality

65 Branching methods for cable networks 66 General methods for collapcing cablenet edges 67 Implementation of K2

Engineering

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initial point cloud

The role of the cablenets in Lace Wall is to brace and force the bending active rods into the form found balanced hybrid. However to achieve a designed shape there might be many different cablenet topologies to do so. We developed computational methods to generate and analyse and eventually find the best fitting cablenet for each position in the meta structure. In this we had to overcome several challenges, in terms of missing algorithms and methods for design and evaluation of cablenets and the sheer amount of nets to calculate. The computational design of cable networks is informed by the typologies produced during interactive and physical modelling. Here a general tendency towards minimal trivalent networks was observed. This means three cables meeting in one internal node, as this are networks which have few members (i.e. cables), yet are efficient at restraining a beam unit. These trivalent properties are similar to the class of graph networks known as Steiner trees. However no fast algorithm for generating these is known. We developed therefore a pseudo Steiner tree algorithm that generates a minimal valence 3 network. This algorithm is fast and does not require the state of the art approach, which uses lengthy optimization loops. Our algorithm follows a logic, where we find iteratively the closest node pair from a set of points (in Lace Wall points distributed on the bend rods), connect these nodes with an edge (i.e. a line/cable), remove the nodes from the set and add the midpoint of the edge to the node set. The resulting network is subsequently relaxed once it is fully connected.

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GENERATIVE CABLENETS COMPUTATIONAL METHODS FOR AUTOMATED DESIGN AND SEARCH

relaxed network

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topological centrality

65 Branching methods for cable networks 66 General methods for collapcing cablenet edges 67 Implementation of K2

Engineering

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Genome: 0.519 0.14 0.258 0.634 0.865 0.157

Entries: 5 Iterations: 106 Genome Size: 6 MaxFitness: 0.7 MaxSimilarity: 1.0

68 Novelty search for cable networks 69 Close up view on the genome generation for the novelty search engine

CITA Complex Modelling

The generative design strategy for cable nets aims to generate large sets of well performing cable networks looking for diversity both in terms of network size and topology. For every investigated beam unit our design space search generated a large amount of diverse cable networks. Each of these was than evaluated in terms of performance. The result of this fitness analysis was displayed to the designer and a new or refined search could start. Several methods of analysis were implemented to define fitness to use with the meta-heuristic search and optimization processes. These can described as being either binary or continuous. To be considered a candidate, an assembly has to pass both geometric analysis (do all cables connect to beams at acceptable angles? Does any cable connect at too many overlapping beams?), dynamic analysis (is the solution stable? Which can evaluated by whether or not it reached an equilibrium within N iterations), structural analysis (are all cables taut? are all cables evenly taut?). Once it passes these tests, it is evaluated against how well it will tile with its neighbours, which provides the primary fitness score.

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Genome: 0.519 0.14 0.258 0.634 0.865 0.157

Entries: 5 Iterations: 106 Genome Size: 6 MaxFitness: 0.7 MaxSimilarity: 1.0

68 Novelty search for cable networks 69 Close up view on the genome generation for the novelty search engine

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ASSESSING FITNESS IN COMPLEX SEARCH SPACES

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70 Fitness criteria for the tiling value 0.6856. 0 is a perfect match 71 One of the cablenet iterations with the maximum low fitness criteria

CITA Complex Modelling

Searching and analysing the large space of possible cablenets solutions is neither an easy nor a straightforward task. Most of the solutions, which are found through the iteration over possible combinations of parameters are actually not stable and provide hence void solutions. As result the phase space of the search problem is not continuous, but very patchy and the implementation of generic optimization solvers would therefore not guaranteed to find any global minima. Instead we use generative search as a method of generating a pool of many good solutions from which we pick candidates. This is managed by recording all good fit candidates over several rounds of search; at each run the genome size is increased to generate larger networks. Each round lasts two hours and yields about 50-100 candidates. To ensure that we do not simply record the same or very similar candidates during a run, candidates are only recorded if they are sufficiently different (measured by comparing genomes) from the already recorded candidates in the pool. If a new candidate is fitter than a similar candidate in the recorded pool, it replaces the old one.

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70 Fitness criteria for the tiling value 0.6856. 0 is a perfect match 71 One of the cablenet iterations with the maximum low fitness criteria

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Pipeline provides information about the orientation of planes as well as all the angles between the elements which helps to visualise the model with the materil thicknesses

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72 Growth direction for the

cable nets

73 Units with the detailed cable nets

Colour demonstrates the hierarchy in the cable network - more red - the most centric cable it is, more blue - the most outer cable it is

The cable net algorithm generates a large diversity of cable networks based on the input of a polyline beam geometry and the direction of the future cable net growth (â&#x20AC;&#x153;spineâ&#x20AC;&#x153;), as well as the amount of cables and outer nodes. In order to narrow down the cable net outcomes the search range was also minimised by defining the angle between cables in the node and the angle by which the cable meets the beam. These angles were predefined through empirical testing of the system. The cable networks with uneven distribution of angles in the nodes were deselected as were the those with steep angles between beam and cable.

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Pipeline provides information about the orientation of planes as well as all the angles between the elements which helps to visualise the model with the materil thicknesses

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72 Growth direction for the

cable nets

73 Units with the detailed cable nets

Colour demonstrates the hierarchy in the cable network - more red - the most centric cable it is, more blue - the most outer cable it is

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74 Design outcomes of the

search cablenet engine

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75 Overlay of the cablenet search solutions

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74 Design outcomes of the

search cablenet engine

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75 Overlay of the cablenet search solutions

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slack cables: 0 evently taut: 28.95

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STRESSES AND TENSION IN THE CABLE NETWORKS The shaping and form finding process implements the mechanically accurate K2 Engineering elements of bar, rod and cable for representing the beams and cables. This means that we can evaluate the structural performance of a FAHS unit in terms of stresses and forces at any point during solving. Specifically we evaluate: 1) The axial stresses in the discretized bar/cable elements along the beams and cable to determine how much tension (blue) or compression (red) they are under. 2) The rod elements along the beams to determine local bending stresses (red-yellow-green-blue gradient). 3) The reaction forces at anchored nodes and point loads. The axial stresses in the cable element are used downstream to evaluate for slack and unevenly taut cables in the network.

76 Tension forces in the cablenets 77 Slack cables analysis 78 Forces visualisation from K2 Solver component

slack cables: 0 evently taut: 31.15

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slack cables: 0 evently taut: 28.95

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76 Tension forces in the cablenets 77 Slack cables analysis 78 Forces visualisation from K2 Solver component

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80 Tension forces visualised only on the level of cables

79 Tension forces distributed on the Lace Wall design

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80 Tension forces visualised only on the level of cables

79 Tension forces distributed on the Lace Wall design

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MACHINE LEARNING FOR CABLE NET GENERATION SUPERVISED LEARNING In order to build Lace Wall we need we need to develop knowledge or at least an intuition about the relationship between the single unit and the macro behaviour of the structure. So far, to find a suitable cable net we have been using an evolutionary solver which was searching the solution space for the design meeting all of the buildability/performance criteria. While we can optimize a small sample of the wall in that way, applying the same method for the overall assembly is futile - the amount of solutions to evaluate grows exponentially with each parameter introduced into the system. And while we can run simulations on large arrays of units, we cannot run these in speeds an evolutionary solver would require.

81 Computation of stresses 82 Unit classification based

stresses

83 Output values for each of the units during the learning process

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81 Computation of stresses 82 Unit classification based

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Initialization Initialization

Initial Initial Design Design

Structural Analysis Data Analysis Data

Naive Naive Pick Pick Initialization Initialization

Classification Loop Classification Loop Optimization Optimisation (Evolutionary Solver) (Evolutionary Solver)

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Data Classification Data Classification (Neural (NeuralNetwork) Network)

Comparison

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Was Improved Improved?? Was Yes / NoNo Yes

Final Final Design Design

To overcome this limitation we use a simple heuristic - we look for a single unit which performs the worst, optimize it and reintroduce it into the wall with changed cable layout repeating this process multiple times greatly improves the overall performance of the wall. The challenge in the execution of this method is the lack of a proper metric which could indicate the worst performing unit. Rather than inventing this metric directly, we employ a supervised machine learning method - backpropagation neural network. This kind of neural network is used commonly for pattern recognition, and it is known for its flexibility and robustness in classification. We train the network with load distribution data of the units for which we know the optimal cable net solution. We ask the network about each of the units in the wall, and it indicates the one which it is least familiar with this is what we interpret as the worst performing unit, which is then optimized and the whole process repeats.

Smallest Output Smallest Output Value Value Case Case

84 Optimisation diagram 85 Visualisation of the

Networkâ&#x20AC;&#x2122;s learning process

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Database Database Solutions Solutions

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Initialization Initialization

Initial Initial Design Design

Structural Analysis Data Analysis Data

Naive Naive Pick Pick Initialization Initialization

Classification Loop Classification Loop Optimization Optimisation (Evolutionary Solver) (Evolutionary Solver)

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Data Classification Data Classification (Neural (NeuralNetwork) Network)

Comparison

Altered Design Altered Design

Was Improved Improved?? Was Yes / NoNo Yes

Final Final Design Design

Smallest Output Smallest Output Value Value Case Case

84 Optimisation diagram 85 Visualisation of the

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Database Database Solutions Solutions

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0.377898

0.37874

0.382613

0.386381

0.388152

0.389681

0.390458

0.391214

LACE WALL

0.37471

BEST PERFORMING UNITS

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The process of generating cable networks yielded ten datasets with roughly 130-190 good candidates in each dataset. These networks ranged in size from six to sixteen cables (these are always a multiple of two). From these data sets, eleven candidates were picked through first sorting and filtering out the top twenty best performing candidates in each set. Then communally going through these candidates over three rounds of discussion and voting, evaluating them based on our built up intuitive knowledge of how well they might perform structurally and by their aesthetic value. The eleven chosen units were fully prototyped and evaluated through load testing and analysis of symmetry, cable angles and cable distribution. From this, the final four candidates that would go into the wall were chosen. These were distributed strategically across the wall, with smaller networks at the top and larger networks at the bottom.

86 User preselected units 87 Fabrication data of

some of the preselected units

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0.377898

0.37874

0.382613

0.386381

0.388152

0.389681

0.390458

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LACE WALL

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BEST PERFORMING UNITS

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86 User preselected units 87 Fabrication data of

some of the preselected units

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Offset 0.000

CITA Complex Modelling

Offset 0.007

Offset 0.015

88 Offset approach for achieving the global 89 Overlay of the diamond

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grid of the global shape with different offset values

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Offset 0.000

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88 Offset approach for achieving the global 89 Overlay of the diamond

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LACE WALL DESIGN ITERATIONS MACRO SIMULATIONS Tension and compression analysys of the wall

To evaluate structural performance on the macro scale of the entire wall, the chosen cable networks were generated using the described distribution across a parametric encoding of a full wall. This was managed using a generative model that describes the overall wall curvature from the slight offset of a single tile, generating an array of identical tiles upon which the beam unit can be deployed and the cable networks generated. Just as with single units, this geometry can be plugged into the form finding and structural analysis model for a mechanically accurate simulation of the entire wall. To reach an effectively zero moment state of equilibrium took roughly 250000 iterations with a similar amount of goals to solve. This equates to about 10 hours of solving an a standard PC.

External forces analysys of the wall

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90 K2 Engineering

visualisations on the wall design iterations

91 Beam stress visualisation representation

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Shaping of the wall

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LACE WALL DESIGN ITERATIONS MACRO SIMULATIONS Tension and compression analysys of the wall

External forces analysys of the wall

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90 K2 Engineering

visualisations on the wall design iterations

91 Beam stress visualisation representation

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Shaping of the wall

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Lace Wall was exhibited in the Complex Modelling exhibition in Copenhagen, which showcased three demonstrator projects, which were built within the research project. Lace Wall proposes how future architecture can work with materials in a highly optimized manner, creating super light structures. As our social and environmental contexts are changing, it is paramount that we develop new building practices for a less intensive material culture. Where Lace Wall is speculative and removed from the requirements of everyday architecture it demonstrates a new structural system, that is based on a minimal inventory of bend rods and constraining tension wires. In order to design and fabricate the structure new computational techniques were developed, which integrate design and simulation of bending active hybrid systems. These techniques are fast and robust, can handle unprecedented amounts of interacting elements and can be adapted and programmed to fit to a broad range of design cases in- and outside of the field of lightweight structures. Lace Wall presents new computational workflows and tools to tackle highly interdependent design problems and exceeds in using Machine Learning current design optimization strategies, which are centered around the idea of linear and hierarchical approaches. Lace Wall develops novel computational approaches, that couple design iterations in physical and digital models, define clear feedback loops for the development of structural system and detail and introduce finally methods from Machine Learning into the designerâ&#x20AC;&#x2122;s toolkit.

95 Table with models from the development stage of the project. Final Complex Modelling Exhibition 2016 96 3D scanned fragment of the Lace Wall Installation 97 Close up fragment of the

Lace Wall Installation

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95 Table with models from the development stage of the project. Final Complex Modelling Exhibition 2016 96 3D scanned fragment of the Lace Wall Installation 97 Close up fragment of the

Lace Wall Installation

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99 Close up fragment of the Lace Wall Installation

98 Lace Wall Installation. Final Complex Modelling Exhibition, 2016

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99 Close up fragment of the Lace Wall Installation

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Illustration by CITA Diagram by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Diagram by CITA Illustration by CITA Illustration by CITA Photography by CITA Illustration by CITA Photography by CITA Photography by CITA Photography by CITA Illustration by CITA Illustration by CITA Photography by CITA Illustration by CITA Illustration by CITA Photography by CITA Illustration by CITA Illustration by CITA Photography by CITA Illustration by CITA Illustration by CITA Photography by CITA Photography by CITA Photography by CITA Photography by CITA Illustration by CITA Photography by CITA Illustration by CITA Illustration by CITA

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Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Diagramby CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Photography by A. Ingvartsen Illustration by CITA Photography by A. Ingvartsen Photography by A. Ingvartsen Photography by A. Ingvartsen

1 Lienhard, J. & Knippers, J. (2015) Bending-Active Textile Hybrids. Journal of the International Association for Shell and Spatial Structures in Journal of the International Association for Shell and Spatial Structures, 56(October), pp.37–48.

3 Mele, T. Van et al. (2013) Shaping Tension Structures with Actively Bent Linear Elements in International Journal of Space Structures, 28(3), pp.127–135

Ramsgaard Thomsen, M., & Bech, K. (2011). Textile logic for a soft space. København: The Royal Danish Academy of Fine Arts, Schools of Architecture, Design and Conservation, School of Architecture

Ahlquist, S., Menges, A. (2013) Frameworks for Computational Design of Textile Micro-Architectures and Material Behavior in Forming Complex Force-Active Structures in Proceedings of International Conference ACADIA 2015: Computational Ecologies: Deisng in the Anthropocene. pp. 281–292. 2

5 Ramsgaard Thomsen, M., Bech, K., & Sigurdardóttir, K. (2012). Textile logics in Digital Architecture. In H. Achten, J. Pavlicek, J. Hulin, & D. Matejovska (Eds.), Physical Digitality: 30th eCAADe 2012 (1 ed., Vol. 1, pp. 621-628). Prag.

LIST OF PUBLICATIONS Holden Deleuran, A., Pauly, M., Tamke, M., Friis Tinning, I., & Ramsgaard Thomsen, M. (2016). Exploratory Topology Modelling of Form-Active Hybrid Structures. In J. Chilton, P. Gosling, M. Mollaert, & B. Stimpfle (Eds.), Procedia Engineering (Vol. 155, pp. 71-80). Amsterdam: Elsevier. https://doi.org/10.1016/j.proeng.2016.08.008 Nicholas, P., Tamke, M., & Zwierzycki, M. (2018). Machine Learning for Architectural Design: Practices and Infrastructure. In International Journal of Architectural Computing: Complex Modelling (pp. 123-143) https://doi.org/10.1177/1478077118778580

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Photography by A. Ingvartsen Photography by A. Ingvartsen Photography by C. Gengnagel Photography by C. Gengnagel Photography by C. Gengnagel Photography by J. Lienhardt Photography by CITA Photography by CITA Photography by CITA Illustration by CITA Illustration by CITA Photography by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Photography by A. H. Deleuran Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Photography by CITA Photography by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Photography by CITA

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REFERENCES

Nicholas, P., Ramsgaard Thomsen, M., Tamke, M., Holden Deleuran, A., Ayres, P., La Magna, R., & Gengnagel, C. (2017). Simulation in Complex Modelling. In Symposium on Simulation for Architecture and Urban Design (SIMAUD) (pp. 93-100)

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3 Mele, T. Van et al. (2013) Shaping Tension Structures with Actively Bent Linear Elements in International Journal of Space Structures, 28(3), pp.127–135

Ramsgaard Thomsen, M., & Bech, K. (2011). Textile logic for a soft space. København: The Royal Danish Academy of Fine Arts, Schools of Architecture, Design and Conservation, School of Architecture

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INFORMATION RICH DESIGN

DATE

VENUE

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2014

Exhibition

The Danish Council for

Mette Ramsgaard Thomsen

“What does it mean to

Independent Research

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make an experiment?“ Meldahls Smedie, Denmark

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Learning to be a Vault is a speculative design project examining the use of machine learning techniques for implementing flexible and adaptive design solutions. The project couples generative design processes that integrate material simulation with unsupervised clustering algorithms. Through this integration, open model topologies and emergent feature production become critical operators for achieving design agency in high-order parameter spaces. The project was exhibited at the What Does It Mean To Make An Experiment? exhibition at the Royal Academy of Fine Arts School of Architecture, spring 2014. Learning to be a Vault examines means of creating design methods that circumvent the inherent reduction and fixity of parametric design models. The issue of parametric design modelling lies firstly with the need to reduce parameters in order to keep

an intuitive overview of the design space and, secondly, with the difficulty of changing the underlying model topology. The problem with this ‘inflexibility of the flexible model’ is well known and the subject of significant effort within the field (1, 2). Here, tools for multi-objective optimisation are prototyped (3) by which processes of ‘optioneering’, or ‘versioning’, explore and give designers feedback about the nature of a given solution space, to challenge a traditional perception of design as singular end-points in order to present a modelling practice that is inherently manifold and expansive (4). Learning to be a Vault questions how machine learning can further engage these problems by allowing designers to work in high-order parameter spaces in which relationships are emergent and open to change during the design process (5). The project employs multiple learning strate-

gies. Firstly, it employs evolutionary methods for generating a large number of model instances across a defined design space, and secondly, it uses unsupervised classification algorithms in order to interrogate and categorise these in an emergent taxonomy of clusters. Learning to be a Vault undertakes this within a network of models sharing information and creating feedback between design processes. The generative algorithm uses a spring-based simulation that allows for the integration of material behaviour as a parameter for design optimisation. The resultant models are assessed using a multi-objective solver and produce results along the Pareto front. Finally, a k-means clustering algorithm searches the design space and classifies the solutions into legible groups. Machine learning is defined as a computer program that is said to learn from expe-

rience when it is configured to improve performance in a given task through the acquisition and processing of incremental data (6). In architecture, machine learning has been explored since the mid-90s with varying focus on design generation, shape recognition, and design space exploration and categorisation (7). Closely tied to statistics, machine learning encompasses a breadth of tools for analysing and building predictions from large, well-defined data sets. A core concept in machine learning is the definition of feature domains. Features are measurable properties shared by the data on which the analysis is done. Defining features is a complex practice, often necessitating domain knowledge. However, features can also hold a transformative potential, eliminating the necessity of explicitly modelling parts and their relationships (8) and making them thereby interesting in our search for new design

1 The bending active

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1 The bending active

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form generation

material simulation

extract pareto front

performance assesment

k-means clustering

visualisation

evolutionary recursion angular variance number of members base point comparison start radius start radial variance end radius intersections total material base point variance linear variance total area interiour obstruction average obstruction average secondary radius secondary radius variance average secondary height secondary height variance

minimal deflection restriction of bending radii area coverage connectivity between elements height of secondary members

descriptive variables: primary means for navigating the design space

2 Networked model

of Learning to be a Vault showing the different modelling processes. Importantly generative and analytical parameters are not mirrored but instead clearly differentiated allowing the unsupervised clustering algorithm to come up with unknown categorisations.

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difficult to understand distance in high-di-

K-means clustering is a distance-based, unsu-

the Voronoi boundary containment. Then, the

pervised learning algorithm that uses intrin-

average value of all contained data points is

sic relationships between data points in large

used to recalculate the centroid of the Voronoi

sets to discretise them into clusters containing

diagram. This process is repeated until the cells

the most similar instances. This happens by

achieve a stable state such that data points no

calculating the distance between data points

longer move between clusters and, thus, cen-

in the n-dimensional space. While it can be

troids no longer require recalculation (5).

mensional spaces, results often make intuitive sense… K-means clustering operates by using the Euclidean distance between data points in n-dimensional space—where n is the number of features used to drive the clustering algorithm—to find solutions for similarity for a user-specified k number of clusters. It does so through an iterative process of computing the ‘nearest-distance centroid rule’, which can be visualised as a Voronoi diagram. The algorithm begins by assigning k-number of random points in the data as centroids for the diagram. It then evaluates all of the other points in the set and assigns them to a ‘cluster’ based on

Learning to be a Vault uses the Complex Modelling project The Rise as its point of departure. By using the same material system, rattan, and the same structural performance, active bending, it builds on both crafts-based material understanding, as well as the tools for design-integrated simulation developed by the design team. Like The Rise, Learning to be a Vault makes use of the material’s inherent flexibility to employ active bending. In Learning to be a Vault, this ability to perform structurally is encoded into a parameterised design model with a deliberately large solution space. Initial testing of this design method took place within an ideation workshop at IAAC, Barcelona. Here, participants were asked to develop a series of physical models examining simple systems of actively bent arches networked together to form novel vaulted configurations. The brief was purposely broad, asking participants to devel-

op material systems that could be permutated and extended through parametric and generative extensions. The idea was to enact the method through physical prototyping. Participants produced 90 models, which were evaluated, classified and developed in further generations. However, we quickly understood that while hand-modelling through physical prototypes enabled interesting and novel results, they were not as consistent in their parametrisation as desired. Participants would continually skip steps, change order and challenge predefined decisions during design development. The workshop ended with the identification of a single system for further digital probing. Subsequently, generative design algorithms were developed to synthesise the found material behaviours, topological transformations were formalised and quantitative, multi-objective optimisation design goals defined.

3 Diagramme explaining the process of K-means clustering. K-means algorithm on a twodimensional data set with k=9 A - data array B - boundaries for k random sample points C - test for inclusion and move centroids D - redefine boundaries E - repeat c & d until stability F - stable solution

methods. Learning to be a Vault employs unsupervised learning. Supervised learning relies on known training data with predicted outcomes in order to let the model develop features and weights that allow it to effectively predict the outcomes for unknown data. In contrast, unsupervised models do not use training data and instead allow for the features of the data set to self organise and emerge during analysis (9). In Learning to be a Vault, this process of self-organisation is explored through k-means clustering (10) and used to navigate and classify a large solution space.

4 (next page) Partial

section of 30 out of 80 clusters, representing over 2000 total phenotypes

5 (next page) Variation in clustering numbers 6 (next page)

Visual interface for understanding the dynamics of different clustering passes, with each incremental pass adding another descriptive cluster

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form generation

material simulation

extract pareto front

performance assesment

k-means clustering

visualisation

minimal deflection restriction of bending radii area coverage connectivity between elements height of secondary members

descriptive variables: primary means for navigating the design space

2 Networked model

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/ 439

difficult to understand distance in high-di-

K-means clustering is a distance-based, unsu-

the Voronoi boundary containment. Then, the

pervised learning algorithm that uses intrin-

average value of all contained data points is

sic relationships between data points in large

used to recalculate the centroid of the Voronoi

sets to discretise them into clusters containing

diagram. This process is repeated until the cells

the most similar instances. This happens by

achieve a stable state such that data points no

calculating the distance between data points

longer move between clusters and, thus, cen-

in the n-dimensional space. While it can be

troids no longer require recalculation (5).

4 (next page) Partial

section of 30 out of 80 clusters, representing over 2000 total phenotypes

5 (next page) Variation in clustering numbers 6 (next page)

Visual interface for understanding the dynamics of different clustering passes, with each incremental pass adding another descriptive cluster

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7 Sequential build-up of

the vault

8 Digital array diagram of the selected models for fabrication

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9 Models of the vaults at the final exhibition

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7 Sequential build-up of

the vault

8 Digital array diagram of the selected models for fabrication

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9 Models of the vaults at the final exhibition

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1 Points on circle

2 First row of arches

3 Second row of arches

4 Third row of arches

5 Connecting ring

6 Choose the both legs of an arch and connect them with the opposite plus 3 legs clockwise

7 Choose the both legs of the next arch and connect them with the opposite plus 3 legs anti-clockwise

8 Flip the legs of the remaining arches and bring the remaining legs closer to each other

9 Remove the legs closer or further away of the center of the circle on the indicated path

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The final design model employs multiple generative and analytical learning strategies in its interrogation of a broad design space. The model consists of three key part-models passing information between each other in a circular feedback loop. The first model employs a recursive array of elements in which two primary elements, one that attaches both ends to the base plane and another to span between them, are allowed to iterate and permutate in a wide range of parametric variations to create a large solution space (4). Solution sets are then passed through an integrated spring-based simulation engine to both form find and analyse for deflection. The form-found models are passed on to a multi-objective optimisation solver and each solution set is evaluated for suitability for continued breeding according to five objectives:

• • • • •

Minimal deflection Restriction of bending radii Area coverage Connectivity between elements Height of secondary members This optimisation then provides the genotypes for a next generation of phenotypes and the process is recursively repeated. The multi-objective evolutionary approach intentionally produces a high volume of phenotypes that are highly varied and intractably numerous so as to gain an intuitive overview and understanding of any chief typologies that may emerge (5). In all, more than 2000 Pareto-optimised phenotypes across 80 generations are produced and then classified using k-means clustering on a collection of 18 variables. While each individual value can seem trivial and non-specific, their combination gives rise to clear clusters, which allows for the intuitive reading of emergent typologies

within the solution space. There are clusters of vault-like structures, circular symmetries, spidery crossed domes and pleated arches. Each cluster evidences different design strategies and criteria. During design development, we found that it was important to keep track of the emergent classification taking place during the running of the k-means algorithm. To do so, we created a data visualisation interface by which each generation of clustering can be tracked. “One measure for determining the

how adding numbers of clusters from one pass

efficacy of a clustering analysis is the average

In this way, the designer can evaluate the right

variance for all variables of each constituent

level of categorisation for the design space and

data point relative to its cluster centroid. Here,

actively balance searchability against compu-

a smaller variance indicates clusters that bet-

tational effort.

ter describe their constituent data points… For

As a speculative project, Learning to be a Vault examines how machine learning can enable new practices for topologically open models in which parametrisation can be purposely high order and yet understood through emergent design criteria.

this experiment, a dashboard is developed that allows for the designer to rapidly understand the dynamics of different clustering passes, with each incremental pass adding another descriptive cluster. The dashboard indicates

Like many of the Complex Modelling projects, Learning to be a Vault is an abstract project concerned with methodological questions. The objective is here to isolate a modelling enquiry and search solutions in a simplified design enquiry. A key point in Learning to be a Vault is that all 2000 models are optimised along the Pareto front, meaning each is an ideal solution. By clustering the solution space along features that lie beyond the optimisation criteria of the foundational generative algorithm, new emergent discoveries about the solution space emerge.

to the next decreases variance for the entire solution, but does so at a decreasing rate, and at the expense of searchability. To facilitate finding an effective threshold, it allows for the designer to select individual clusters, see the individual phenotype most representative of the cluster centroid, read the relative average values of the descriptors used for executing the algorithm, and see which clusters are similar to it both within the same clustering pass and in those both preceding and subsequent to it” (5).

10 First physical

models develop in the IAAC workshop. Simple transforms of an arch based structural morphology 11 Final exhibition of

design space search

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LEARNING TO BE A VAULT

INFORMATION RICH DESIGN

1 Points on circle

2 First row of arches

3 Second row of arches

4 Third row of arches

5 Connecting ring

6 Choose the both legs of an arch and connect them with the opposite plus 3 legs clockwise

7 Choose the both legs of the next arch and connect them with the opposite plus 3 legs anti-clockwise

8 Flip the legs of the remaining arches and bring the remaining legs closer to each other

9 Remove the legs closer or further away of the center of the circle on the indicated path

447

• • • • •

how adding numbers of clusters from one pass

efficacy of a clustering analysis is the average

In this way, the designer can evaluate the right

variance for all variables of each constituent

level of categorisation for the design space and

data point relative to its cluster centroid. Here,

actively balance searchability against compu-

a smaller variance indicates clusters that bet-

tational effort.

ter describe their constituent data points… For

10 First physical

models develop in the IAAC workshop. Simple transforms of an arch based structural morphology 11 Final exhibition of

design space search

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REFERENCES

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3 Vierlinger, R., Bollinger, K. (2014) Accommodating change in parametric design, in Proceedings of the 34th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA): Design Agency, ISBN 9781926724478] Los Angeles 23-25 October, 2014), p. 609 - 618

IMAGE CREDITS Photography by A. Ingvartsen Diagram by CITA Illustration by CITA Illustration by CITA Illustration by CITA 6 Illustration by CITA 7 Illustration by CITA 8 Illustration by CITA 9 Photography by A. Ingvartsen 10 Illustration and diagrams by IAAC / CITA 11 Photography by A. Ingvartsen

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8 Han, Z., Hong, M., & Wang, D. (2017). Deep Learning and Applications in Signal Processing and Networking for Big Data Applications (pp. 126-168). Cambridge: Cambridge University Press. 9 Hinton, Jeffrey; Sejnowski, Terrence (1999). Unsupervised Learning Foundations of Neural Computation. MIT Press

Stasiuk, D., Ramsgaard Thomsen, M. (2014). Learning to be a Vault - Implementing learning strategies for design exploration in inter-scalar systems in Fusion, Proceedings of the 32nd International Conference on Education and research in Computer Aided Architectural Design in Europe, 381390. Vol. 1. eCAADe: Conferences 1. Newcastle upon Tyne, UK: Northumbria University. 5

10 Steinhaus, H. (1957). Sur la division des corps matériels en parties”. Bull. Acad. Polon. Sci. (in French). 4 (12): 801–804.

6 Mitchell, T.M. (1997). Machine Learning, McGraw-Hill in Science/Engineering/Math

Tamke, M, Nicholas, N., Zwierzycki, M., (2018) Machine learning for architectural design: Practices and infrastructure in “International Journal of Architectural Computing”, Vol 16, Issue 2, 2018

LIST OF PUBLICATIONS Stasiuk, D., Ramsgaard Thomsen, M. (2014). Learning to be a Vault - Implementing learning strategies for design exploration in inter-scalar systems in Fusion, Proceedings of the 32nd International Conference on Education and research in Computer Aided Architectural Design in Europe, 381-390. Vol. 1. eCAADe: Conferences 1. Newcastle upon Tyne, UK: Northumbria University.

2 Harding, J. (2016) Evolving Parametric Models using Genetic Programming with Artificial Selection in H. Aulikki; T. Österlund and P. Markkanen (eds.) Complexity & Simplicity - Proceedings of the 34th eCAADe Conference - Volume 1”, University of Oulu, Oulu, Finland, 22-26 August 2016, p. 423-432

Ramsgaard Thomsen, M., (2016). Complex Modelling - Questioning the infrastructures of information modelling in A. Herneoja, T. Österlund, (eds.) Proceedings of the 34th eCAADe Conference - Volume 1. 34th eCAADe Conference: Complexity & Simplicity. p. 33–42.

Burry, M, (2015), Prototyping the Unfamiliar: New Dilemmas of Scale with an Evolving Digital Design Landscape, in C. Gengnagel, E. Nagy, R. Stark (eds.) Rethink Prototyping: Transdisciplinary Concepts of Prototyping, Springer

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10 Steinhaus, H. (1957). Sur la division des corps matériels en parties”. Bull. Acad. Polon. Sci. (in French). 4 (12): 801–804.

6 Mitchell, T.M. (1997). Machine Learning, McGraw-Hill in Science/Engineering/Math

Tamke, M, Nicholas, N., Zwierzycki, M., (2018) Machine learning for architectural design: Practices and infrastructure in “International Journal of Architectural Computing”, Vol 16, Issue 2, 2018

450

ISOROPIA

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A central insight in Complex Modelling is that in order to implement feedback, the model needs to be able to change its defining design parameters and, more fundamentally, its inherent structural topology. In Complex Modelling, feedback in the design chain enables self-regulation through bi-directional design agency in which modelling steers behaviour through design while concurrently behaviour informs modelling through prediction (1). However, feedback necessitates the ability to change, adapt and better the design. This returns us to idea of the body plan (1). While parametric modelling entails a fundamental fixing of the underlying model topology, retaining flexibility in design necessitates the freedom to reconfigure the underlying topology of the model. In Complex Modelling, we question the underlying data structures of the information model. By devising alternative strategies for topological representation and transferring basic graph analysis methods from computer science, we examine new kinds of design representation. Freed from the direct relationship to geometry, graph representations are flexible methods by which the inherent connectivity between parameters can be

visualised, understood and, in turn, manipulated. Like geometry, graph representations are based on nodes and edges, and a given set of nodes can support many different topologies. As abstract representations, nodes can denote different kinds of features without prescribed meaning or scale, which gives great flexibility to modelling representation. Within generative design processes, graph representations are particularly interesting means of supporting search and optimisation. Here, their high level of abstraction allows for unrestrained and exhaustive exploration of combinationarial possibilities otherwise not possible in parametric models. However, it also brings about the problem of combinatorial explosion in which computing, mapping and evaluating the possible interrelationships of the design space become intractable. In our work with neural networks methods such as NEAT (NeuroEvolution of Augmenting Topologies) (2), we examine evolutionary processes that can change and optimise design topologies and their associated graph representations. These networks employ mutations by which new connections and nodes can

be introduced or adapted, allowing for fundamental re-parameterisation of the design object. The central remit of Complex Modelling is to understand the interactions between low-scale material performance and high-scale structural performance. Here, graph representations are used to understand material connectivity. In Lace Wall, graph representations are employed as a means of understanding and optimising cable networks, as well as in the creation of fabrication instructions. In Inflated Restraint, the inflated surface is analysed for anticlastic curvature, and the topology of the net, its physical connectivity, is generated as a result.

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TOPOLOGICAL MODELLING

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TOPOLOGICAL MODELLING

DATE

VENUE

SUPPORT

TEAM

2016

Meldahls Smedie KADK

The Danish Council for Independent Research

Phil Ayres

Complex Modelling

Prof. Dr. Yordan Kyosev / TexMind UG,

Petras Vestartas

Exhibition

Moenchengladbach, Germany

Mateusz Zwierzycki

Copenhagen, Denmark

FLUKE / PPH Consult A/S, Denmark

Danica Pistekova

Lindab A/S, Denmark

Maria Teudt

Stof 2000, Copenhagen, Denmark

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Inflated Restraint is a freeform cable-stiffened pneumatic membrane. At architectural scale, this structural hybrid is most commonly found in the context of air-supported structures with relatively regular curvature. In this case, we target the design and production of air-inflated structures with complex and irregular curvature. The project combines two lines of investigation: (1) how computational techniques for clustering and graph traversal can support membrane decomposition for geometrically defined design targets and (2) how to model the interactions between cable restraint and membrane to inform their topological design. Our enquiry targets the generation, analysis and fabrication tasks related to the membrane cutting pattern. The cutting pattern is a principle contributing factor in the performance and aesthetic quality of architectural membranes. It is therefore a central design

concern that spans across different scales of consideration and implicates fabrication constraints. Within the project, we define three interlinked scales of design consideration, namely the textile (microscale), the pattern patch (mesoscale) and the membrane (macroscale), and seek to determine the relevant channels of feedback between these scales to inform our novel design method. The design workflow is developed and refined through iterative cycles of digital and physical prototyping. The physical prototypes act as a means of evaluating workflow efficacy based on four measures of success: (1) that there is a close geometric correlation between the model and the physical pneu; (2) that the inflated surface achieves the desired curvatures; (3) that the membrane has a smooth transition across patches; and (4) that the membrane is fully tensioned without any areas of

compression resulting in underperforming compression wrinkles. Through the project development, we find that the naked-edge relaxation of patch elements is an essential step for final surface quality. We also find that the cable-net topology can easily be derived within the digital modelling environment, but that its geometric dimensions need to be determined through surface surveying. Clustering and graph traversal methods are utilised for an initial segmentation on the basis of curvature regions of the design mesh and then reapplied to subdivide these regions into individual patches that conform to fabrication criteria. As the process progresses down the scale from membrane to curvature region to patch, local topological features are inherited into sub-models that can easily be reassembled for simulation tasks.

These relations are key to providing a principled flexibility in the exploration of topological variations. Topological variations are driven through the process of segmentation and by adjusting the weight of critical design criteria such as curvature change and patch size. In this project, clustering and graph traversal are proven to be robust techniques for this topologically orientated decision making, supporting the transition from the geometrically pre-defined design target to specification of the membrane patch. Integrated simulation is also proven to be essential for providing feedback to adjust cable net geometries for a given membrane. Here, analysis of the textile mechanical properties that determine the performance of the membrane informs the integrated simulation. This enables investigation of the interaction between membrane and restraint net.

1 Detail of Inflated

Restraint in the context of the Complex Modelling exhibition, 2016

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VENUE

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TEAM

2016

Meldahls Smedie KADK

The Danish Council for Independent Research

Phil Ayres

Complex Modelling

Prof. Dr. Yordan Kyosev / TexMind UG,

Petras Vestartas

Exhibition

Moenchengladbach, Germany

Mateusz Zwierzycki

Copenhagen, Denmark

FLUKE / PPH Consult A/S, Denmark

Danica Pistekova

Lindab A/S, Denmark

Maria Teudt

Stof 2000, Copenhagen, Denmark

INFLATED RESTRAINT

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1 Detail of Inflated

Restraint in the context of the Complex Modelling exhibition, 2016

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INFLAITED RESTRAINT

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INTRODUCTION

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The principle challenge in cutting pattern generation is the subdivision of a target geometry into a set of sub-surfaces with minimal distortion (1). Within the literature, there is general consensus on the design workflow necessary to achieve this goal: design commences with form-finding, progresses through structural analysis and concludes with the generation of a cutting pattern (1, 2, 3, 4). In general, the aesthetic of architectural membranes follows principles of regularity and minimal deviation between membrane sub-panels (5, 6). In this project, we explore alternative principles of free-patterning, using methods of constraint-informed mesh segmentation [7]. We use these methods to achieve predefined design targets that can contain complex and anticlastic curvatures.

2 The largest of the two

pneu has regions of high negative Gaussian curvature

3 Detail of freeform patches

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PATTERN CUTTING FOR ARCHITECTURAL MEMBRANES

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INTRODUCTION

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2 The largest of the two

pneu has regions of high negative Gaussian curvature

3 Detail of freeform patches

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PATTERN CUTTING FOR ARCHITECTURAL MEMBRANES

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Membrane Stiffness = 10.0 Membrane Volume * 1.5 Net Stiffness = 10.0

Membrane Stiffness = 1.0 Membrane Volume * 1.5 Net Stiffness = 10.0

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Membrane Stiffness = 10.0 Membrane Volume * 1.5 Net Stiffness = 10.0

Membrane Stiffness = 5.0 Membrane Volume * 1.5 Net Stiffness = 10.0

Membrane Stiffness = 0.1 Membrane Volume * 1.5 Net Stiffness = 10.0

Membrane Stiffness = 10.0 Membrane Volume * 1.5 Net Stiffness = 10.0

CABLE-STIFFENED PNEUMATICS

Membrane Stiffness = 2.0 Membrane Volume * 1.5 Net Stiffness = 10.0

STRUCTURAL HYBRIDITY Cable-stiffened pneu combines the structural logics of cable nets and inflated membranes. The utility of this structural hybrid has been apparent for millenia in the form of ancient carrying devices. It then found application around the end of the 18th century in early aeronautics in the production of air balloons and, subsequently, airships. The transfer into engineered architectural approaches occured around the mid-20th century, and its development coincides with early adoption of digital computation in engineering due to analytical complexity. The structural benefit of cable-stiffened pneu is a result of the division of the membrane into smaller regions with reduced radii of curvature. This relieves the membrane stresses that are a product of inflation pressure and radius of curvature (8).

Membrane Stiffness = 0.1 Membrane Volume * 3.0 Net Stiffness = 10.0

4 Simulation studies exploring inflated pneu and net interactions across different stiffness paramaters and net topologies. 5 Cable restraint study

inducing local asymmetric curvature regions

6 Cable restraint net study

inducing curvature regions with minimised local deviation

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Membrane Stiffness = 10.0 Membrane Volume * 1.5 Net Stiffness = 10.0

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Membrane Stiffness = 10.0 Membrane Volume * 1.5 Net Stiffness = 10.0

Membrane Stiffness = 1.0 Membrane Volume * 1.5 Net Stiffness = 10.0

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Membrane Stiffness = 10.0 Membrane Volume * 1.5 Net Stiffness = 10.0

Membrane Stiffness = 5.0 Membrane Volume * 1.5 Net Stiffness = 10.0

Membrane Stiffness = 0.1 Membrane Volume * 1.5 Net Stiffness = 10.0

Membrane Stiffness = 10.0 Membrane Volume * 1.5 Net Stiffness = 10.0

CABLE-STIFFENED PNEUMATICS

Membrane Stiffness = 2.0 Membrane Volume * 1.5 Net Stiffness = 10.0

Membrane Stiffness = 0.1 Membrane Volume * 3.0 Net Stiffness = 10.0

4 Simulation studies exploring inflated pneu and net interactions across different stiffness paramaters and net topologies. 5 Cable restraint study

inducing local asymmetric curvature regions

6 Cable restraint net study

inducing curvature regions with minimised local deviation

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MESHES AND MEMBRANES

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In computational design approaches, mesh data-structures are most commonly used for representing membranes. During the design process, the treatment of meshes can be distinguished into two general approaches. The first is to segment a mesh that represents the whole membrane using geodesics extracted from the design target [1]. However, this approach disrupts mesh regularity when cutting geometry does not correlate with mesh geometry. The resulting need to split mesh faces and manage the implications to vertices and edges means that segmentations are topologically estranged from the parent mesh. The second approach is to pre-determine the segmentation of the design target with individual meshes representing membrane patches (2, 9). This allows mesh topology to be maintained through relaxation processes; however, it also impedes speculative early-design iteration.

K 0-7

7 Segmentation of extracted curvature regions into patches 8 Topological relations can be mapped from patch, to curvature region, to complete membrane

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7 Segmentation of extracted curvature regions into patches 8 Topological relations can be mapped from patch, to curvature region, to complete membrane

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9 Segmentation of the larger pneu 10 Segmentation of the smaller pneu

In contrast to these approaches, our method supports design exploration and topology-finding based on criteria of surface curvature and patch size. A design mesh defining the entire membrane is only ever segmented at the level of whole mesh faces, thus preserving topological integrity to the parent, as well as the relationship to neighbouring patches during geometry-altering relaxation processes. Altering the criteria parameters, or their weighting, in the graph traversal process provides the mechanism for an in-depth exploration of patch configurations.

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9 Segmentation of the larger pneu 10 Segmentation of the smaller pneu

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ITERATIVE PRODUCTION FOR FEEDBACK Physical prototyping has been an essential means of gaining insight into how the cutting pattern mediates between digital design methods, production and outcome. The four measures of success, close geometric correlation, desired curvatures, smooth transitions and no compression wrinkles, have driven critical modifications across the design and fabrication process. These include the implementation of an additional relaxation procedure on the boundary curves of segmented patches to minimise surface pinches. Furthermore, regular markers on the patch edge are incorporated to guide the sewing of complex curves and finally, a novel free-form patching aesthetic is articulated to replace strategies of regular strip segmentation.

11 The larger pneu showing

good surface continuity and interaction with the minimal net

12 Early prototype

exhibiting poor surface continuity

13 Early prototype with a regular strip segmentation strategy. Surface pinch defects are clearly visible

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PHYSICAL PROTOTYPING

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11 The larger pneu showing

good surface continuity and interaction with the minimal net

12 Early prototype

exhibiting poor surface continuity

13 Early prototype with a regular strip segmentation strategy. Surface pinch defects are clearly visible

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GENERATING CUTTING PATTERNS MESH SEGMENTATION STRATEGY In contrast to conventional approaches of pattern-cutting generation, which operate on form-found geometries, we begin with the definition of an unconstrained target mesh. The mesh is then analysed to determine regions of synclastic, anticlastic and neutral curvature. These regions are then segmented using the Dijkstra (shortest path) graph traversal algorithm. The naked edges of the segmented areas are then relaxed to minimise jagged outlines and pinched areas, which pose respective difficulties during sewing and inflating. A K-Means clustering algorithm and neighbour indexing are used for grouping patches for fabrication and for distributing patterns relative to material quantities.

Method 2: K-mean Clustering + Kangaroo 2 relaxation

14 Investigations of different

segmentation approaches

15 The design target mesh 16 Results of preliminary mesh curvature analysis

Method 1: Dijkstra - Shortest Path (NetworkX) + Kangaroo 2 relaxation

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Method 2: K-mean Clustering + Kangaroo 2 relaxation

14 Investigations of different

segmentation approaches

15 The design target mesh 16 Results of preliminary mesh curvature analysis

Method 1: Dijkstra - Shortest Path (NetworkX) + Kangaroo 2 relaxation

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17 Automated nesting of like-coloured patches for laser-cutting

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FABRICATION TO INFLATION SEWN JUNCTIONS

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19 First inflation of

the smaller pneu after completion of the sewing

20 Patches are sewn using a simple running stitch 21 Seamstress insights informed patch boundary with markers to regulate the sewing of curves

Air loss is a reality for all inflatables (8). In our case, the pneu system reaches full inflation with a pressure in the region of 200â&#x20AC;&#x201C;350 Pa, a comparable pressure to air-supported structures. With such a low operating pressure, and a small combined volume of 12.8m3, considerable air loss can easily be balanced with a suitable air supply. This allows patch connections to be made with a simple running stitch, which also benefits the overall surface quality.

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FABRICATION TO INFLATION SEWN JUNCTIONS

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19 First inflation of

the smaller pneu after completion of the sewing

20 Patches are sewn using a simple running stitch 21 Seamstress insights informed patch boundary with markers to regulate the sewing of curves

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22 Inflation sequence taken

over seven minutes

23 Load testing of the running stitch junction

Inflation of the membranes takes approximately seven minutes using a proprietary duct fan with a maximum flow of 64 liters per second at a maximum pressure of 300 Pa. At full operating pressure, membrane stresses are not enough to have to consider the anisotropic characteristics of the coated textile and are well within the failure limits of the sewn junction (10).

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22 Inflation sequence taken

over seven minutes

23 Load testing of the running stitch junction

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MINIMAL NETS MEDIAL AXIS

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24 Identification of the

medial axis curves from the design mesh

25 Medial axis curves

extracted from a laser scan of the inflated membranes

The topology of the cable restraints is determined from curvature analysis of the design target model. We identify the principle medial axes on the mesh, the curves with the highest negative curvature, to establish the primary loops of the net. As such, the net topology is independent from the subdivision of the membrane. In simulation, we ‘inflate’ the membrane model to verify its interaction with the cable restraint model. Here, the measures of success are that the net does not exhibit ‘slippage’, that the two systems find and maintain equilibrium and that the net induces local regions of increased membrane curvature to relieve membrane stresses.

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24 Identification of the

medial axis curves from the design mesh

25 Medial axis curves

extracted from a laser scan of the inflated membranes

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26 Point-cloud of the larger

pneu

27 Surface deviation analysis between pneu and the design model 28 Point-cloud of the two

pneu

29 Sectional study of point-cloud in relation to the design mesh to determine deviation

As a final evaluation step, the physical pneu is compared to the design mesh. A point-cloud of the physical setup is captured by Lidar scanner. This is â&#x20AC;&#x2DC;best adjustedâ&#x20AC;&#x2122; to the design mesh and the degree of surface deviation determined. Here, our measures of success are that there is a close geometric correlation between the model and the realised pneu and that the inflated surface achieves the desired curvatures. Areas of high deviation from the target are localised around regions of anticlastic curvature. However, in general, we find that there is relatively good correlation despite a general deviation indicative of the membrane being underinflated.

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26 Point-cloud of the larger

pneu

27 Surface deviation analysis between pneu and the design model 28 Point-cloud of the two

pneu

29 Sectional study of point-cloud in relation to the design mesh to determine deviation

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pressure reading point

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31 Inflated Restraint

installed as part of the Complex Modelling

30 Detail of air intake and

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pressure reading point

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31 Inflated Restraint

installed as part of the Complex Modelling

30 Detail of air intake and

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REFERENCES Gründig, L, Moncrieff, E., Singer, P., Ströbel, D. (2000), “High-performance cutting pattern generation of architectural textile structures.” in IASS-IACM, Fourth International Collo-quium on Computation of Shell & Spatial Structures.

6 Otto, F., Burkhardt, B., Drüsedau, H. (1982), “Manufacturing.” in IL15 Air Hall Handbook, Institute for Lightweight Structures, West Germany.

Nejur, A., Steinfeld, K. (2016), “Ivy: Bringing a Weighted-Mesh Representation to Bear on Generative Architectural Design Applications.” in ACADIA // 2016: POSTHUMAN FRONTIERS: Data, Designers, and Cognitive Machines, Proceedings of the 36th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA), pp. 140-151.

2 Kim, J-Y., Lee, J-B. (2002), “A new technique for optimum cutting pattern generation of membrane structures.” in Engineering Structures, Volume 24, pp.745-756.

8 Dent, R. (1971), Principles of Pneumatic Architecture. Architectural Press, London.

Philipp, B., Breitenberger, M., Wuchner, R., Bletzinger, K. (2015), “Form-Finding of Architectural Membranes in a CAD-Environment Using the AiCAD-Concept.” in Ramsgaard Thomsen, M., Tamke, M., Gengnagel, C., Faircloth, B., Scheurer, F. (eds.) Modelling be-haviour: design modelling symposium 2015. Springer, pp. 65-74.

Tabarrok, B., Qin. Z. (1993) “Form finding and cutting pattern generation for fabric tension structures.” in Microcomputers in civil engineering vol. 8, Elsevier Science Publishers Ltd, Amsterdam.

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Photography by A. Ingvartsen Photography by A. Ingvartsen Photography by A. Ingvartsen Illustration by CITA Photography by CITA Photography by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Photography by A. Ingvartsen Photography by A. Ingvartsen Photography by A. Ingvartsen Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Photography by CITA Photography by CITA Photography by A. Ingvartsen Photography by CITA Photography by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Illustration by CITA Photography by A. Ingvartsen Photography by A. Ingvartsen

10 Ansell, M., Harris, B. (1982), “Fabrics – Characteristics and Testing.” in IL15 Air Hall Handbook, Institute for Lightweight Structures, West Germany.

5 Knipper, J., Cremers, J., Gabler, M., Lienhard, J. (eds.) (2011), Construction Manual for Polymers + Membranes. Birkhäuser, Edition Detail.

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Ayres, P., Vestartas, P. & Ramsgaard Thomsen, M. (2017) Enlisting Clustering and Graph-Traversal Methods for Cutting Pattern and Net Topology Design in Pneumatic Hybrids in Humanizing Digital Reality: Design Modelling Symposium Paris 2017. Springer, p. 285-294.

IMAGE CREDITS

3 Otto, F., Drüsedau, H., Hennicke, J., Schaur, E. (1982), “Architectural and Structural Design.” in IL15 Air Hall Handbook, Institute for Lightweight Structures, West Germany.

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6 Otto, F., Burkhardt, B., Drüsedau, H. (1982), “Manufacturing.” in IL15 Air Hall Handbook, Institute for Lightweight Structures, West Germany.

2 Kim, J-Y., Lee, J-B. (2002), “A new technique for optimum cutting pattern generation of membrane structures.” in Engineering Structures, Volume 24, pp.745-756.

8 Dent, R. (1971), Principles of Pneumatic Architecture. Architectural Press, London.

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10 Ansell, M., Harris, B. (1982), “Fabrics – Characteristics and Testing.” in IL15 Air Hall Handbook, Institute for Lightweight Structures, West Germany.

5 Knipper, J., Cremers, J., Gabler, M., Lienhard, J. (eds.) (2011), Construction Manual for Polymers + Membranes. Birkhäuser, Edition Detail.

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IMAGE CREDITS

3 Otto, F., Drüsedau, H., Hennicke, J., Schaur, E. (1982), “Architectural and Structural Design.” in IL15 Air Hall Handbook, Institute for Lightweight Structures, West Germany.

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DATE

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SUPPORT

TEAM

2015

Aarhus, Denmark

Aarhus School of Architecture,

CITA, ZHA Code, McNeel

Anders Holden Deleuran (CITA),

Ali Farzaneh (AA London),

David Reeves (ZHA Code),

Daniel Piker (Fosters + Partners,

Jens Pedersen (AAA Aarhus),

Robert McNeel & Associates),

Architectural Association London

Michael Weinstock (AA London), Andreas Eggertsen (Norwegian University of Science and Technology; SnĂ¸hetta)

RETHINKING PATTERNS: ELEPHOETUS

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Rethinking Patterns was the first instance of the international Architectural Association Visiting School Programme series in Denmark. It focused on the generative modelling and form finding of meshes, analysing these for lighting properties, using this data to drive the design of material systems that would modulate light, and developing these into the plane and fabricating them using sheet materials. These explorations were structured around a series of workshops. Iterating through successive stages of tutorials, ideation and development, computational modelling, and CNC fabrication. Leading to an exhibition at the AAA where probes and prototypes developed by participants and tutors were presented to the public. The Elephetus prototype presented here was designed, modelled, and fabricated during the last three days of the summer school by tutors Anders Holden Deleuran and Dave Reeves,

using the surplus 3mm plastic sheet materials. It was envisioned as a hanging lamp screen, modulating light from three active fluorescent tubes, one in each of its legs. Where dynamic lighting would glow translucently with differing levels and colors through the three different plastic sheet materials used, and direct light would emit from the open hatch pattern connecting the meso elements, generating shadow patterns. As a complex material system, the Elephetus prototype can be described as constituting a self supporting and bending active monocoque shell. That is, it is a structural system in which the loads are supported entirely through its external skin and stiffness is achieved through the active bending of lightweight and slender plates upon the meso scale. These elements are interfaced and connected along their open perimeter edges to compose a single, con-

tinuous, double curved, and in this case topologically complex overall macro surface. All without requiring formwork or other types of guiding construction jigs. This class of structural system typology has seen a substantial increase in popularity during the past couple of years, most notably through the large scale installation works of Marc Fornes/TheVeryMany. This rise in popularity has likely been due to both its structural, material and fabrication efficiency, its aesthetic value, and the proliferation of new computational modelling methods, such as the ones presented here, being developed and made available to a wider public. This includes also notably the Ivy Grasshopper plugin developed by Andrei Nejur, which references Elephetus as a precedence [1]. Within the Complex Modelling research scope, the Elephetus prototype can be described as primarily exploring the top-

ic of topological modelling, and secondarily form finding and planar fabrication/ assembly strategies. The project is hence concerned with solving not just the form finding of bending active monocoque shells, but also the intrinsically connected and arguably somewhat overlooked problem of topology finding. That is, what are the processes by which we generate topological representations and explore/search for good fit topological variation of our design objects? And crucially, how do we interface such processes across scales of design engagement? Asking here how we can encode our design intent going from the scale of the macro shell surface to the pop rivets that connect the meso scale slender plates? Within the computational modelling pipeline developed for generating Elephetuses, these modelling concerns were structured into four successive modelling stages within one Grasshopper

1 Inside the Elephetus

prototype. Captured during assembly before closing up its three legs

2 (next page) The

reference Grasshopper model used during assembly. Red dots indicate starting faces of the strips and integers their index of generation during mesh walking. Colored strips have yet to be assembled

3 (next page) The smaller pringle prototype made prior to Elephetus. Here showing captures from the automated design space search. Attempting to minimise the occurrence of small walks

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2015

Aarhus, Denmark

Aarhus School of Architecture,

CITA, ZHA Code, McNeel

Anders Holden Deleuran (CITA),

Ali Farzaneh (AA London),

David Reeves (ZHA Code),

Daniel Piker (Fosters + Partners,

Jens Pedersen (AAA Aarhus),

Robert McNeel & Associates),

Architectural Association London

Michael Weinstock (AA London), Andreas Eggertsen (Norwegian University of Science and Technology; SnĂ¸hetta)

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1 Inside the Elephetus

prototype. Captured during assembly before closing up its three legs

2 (next page) The

reference Grasshopper model used during assembly. Red dots indicate starting faces of the strips and integers their index of generation during mesh walking. Colored strips have yet to be assembled

3 (next page) The smaller pringle prototype made prior to Elephetus. Here showing captures from the automated design space search. Attempting to minimise the occurrence of small walks

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definition: 1) Generating topologically complex manifold meshes, 2) Form finding meshes toward shell bending behaviour, 3) Decomposing unstructured meshes into geodesic developable strips, 4) Generating fabrication and assembly information. A topologically complex manifold is defined here as constituting a continuous, orientable, and non-intersecting surface with a genus larger than zero (i.e. two-sided surfaces with one or more holes/handles). NURBS modelling is fundamentally problematic for this type of geometric representation, as one must combine multiple quadrilateral surface patches for anything more complex than a torus. Polygonal meshes may conversely approximate the topology of any manifold using one continuous and flexible data structure that inherently lends itself well to interfacing design scales from macro to micro (and vice versa). Our generative design modelling logic

here was based upon drawing a medial representation (i.e. a set of spatial curves) describing the positive and negative space of the shell. From these a three-dimensional discrete scalar field can be generated, and a mesh approximating an isosurface through this field can be extracted using the well known marching cubes algorithm [2]. This was implemented in C# scripting components using Dave Reevesâ&#x20AC;&#x2122; Spatial Slur geometry processing library [3]. An inherent downside to the marching cubes logic is that the generated mesh vertices are coincident with the cartesian scalar field grid, yielding highly heterogeneous local geometry (i.e. long skinny and short fat triangle faces) and network topology (i.e. vertices with many different valences). To improve the mesh quality for both the downstream form finding and decomposition into strips, a remeshing algorithm was implemented, which iteratively

collapses, splits, and flips mesh edges with the objective of generating an equilaterally triangulated mesh with consistent valence counts [4]. This was implemented into the pipeline using Daniel Pikerâ&#x20AC;&#x2122;s Mesh Machine component, now part of his Kangaroo3D plugin [5]. Kangaroo3D was also implemented for the following stage, in which the remeshed shell geometry is form found towards performing appropriately as a bending active slender plate structure. The form finding logic applied here is similar to the modelling of the elastica curve as applied in the Hybrid Tower and Lace Wall projects (i.e. sequential pairs of line segments along a polyline will attempt to maintain an angle of 180 degrees, while also maintaining their lengths). Only here the 2D curve bending logic is dimensionally extended to 3D surfaces, by instead operating upon the four points describing the hinge at each

closed edge of the mesh. That is, for all edges that are not on the open mesh perimeter, their two neighbouring faces are identified, and these two triangles are instructed to bend out to 180 degrees across their shared edge. Yielding the mesh macro surface to assume an appropriate bending active geometry. These behaviours were implemented using an early build of the Kangaroo2 projection based dynamic relaxation [6] solver, with both the goals and physical system being implemented in GHPython scripting components. Unlike the structured quadrilateral meshes typically implemented for modelling topologically complex manifolds within both design and entertainment (i.e. subdivision modelling methods such as the well known Catmullâ&#x20AC;&#x201C;Clark scheme [7]), the unstructured triangular meshes output from common remeshing processes do not feature intrinsic natural face loops. From

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which one can more readily decompose a mesh into strips (i.e. series of consecutive faces that connect edge to edge and may be unfolded into the plane). This problem has been addressed previously within computational geometry research, where there have been different needs for and approaches to partitioning unstructured triangle meshes into strips. These include mesh data compression [8], efficient real-time rendering [9], and of more direct relevance, papercraft fabrication [10]. Such methods generally share a similar high level logic of iteratively traversing the mesh data structure using its topological information (i.e. querying neighbouring faces, face-vertices etc.), steering the traversal using heuristics designed to satisfy various objectives (such as maximising the length of each strip [9]). Within the computational design community, such approaches have informally become known

as mesh walking algorithms. While there are likely many lower level mesh walking logics, the one developed for Elephetus depend entirely upon graph theory. That is, we implement a network graph as the underlying data structure for traversing the network topology of the mesh, using graph theoretical algorithms that compute shortest paths. This logic was based on the conjecture that shortest walks within a roughly equilateral triangle mesh will be analogous to true geodesics on continuous surfaces (i.e. shortest and straightest curves between point pairs), and therefore should unroll into relatively straight strips. In discrete mathematics, a graph is a topological structure consisting of nodes where some pairs of these are connected by edges (as such, a mesh is a graph). Nodes describe the objects within the network and their properties, edges describe how nodes connect and the

properties of these connections. Within the Elephetus MeshWalker algorithm, an undirected and weighted dual graph of the input RhinoCommon mesh is generated as the basis for traversal. That is, each face within the mesh constitutes a node in the graph and the shared borders between faces constitute edges (i.e. the edges are undirected). To compute shortest paths within the graph its edges must have a property assigned that represents the cost of travelling through them (i.e. the edges are weighted). These weights are initialised to a value of one prior to running the iterative walking algorithm. This was implemented using the undirected graph class of the networkx CPython library [11] and developed in GHPython. The traversal logic implemented in the MeshWalker algorithm is essentially analogous to peeling an orange. First one must pick a start- and endpoint on its surface,

then peel away a strip between these, then repeat this process until the surface has been peeled away entirely. This logic is implemented using a while loop, where at each iteration we check whether the graph still has any nodes left, then compute a shortest path (i.e. corresponding to the faces in a mesh walk strip), and then remove the nodes constituting this path from the graph. Eventually leading to a graph with zero nodes left. Two primary factors determine the properties of the resulting walks during this algorithm: 1) The method by which one picks destination points, and 2) The heuristics used to steer the walk along the remaining surface. To pick destination points, the closest graph nodes from the endpoints of an input line are found. This encoding has the effect that strips will have a predominantly parallel orientation along the shell surface in the direction of this line. To compute the walks between node

mapping the topological connectivity of the strips. Visualised here as a hierarchical tree diagram. Generated using DOT/ GraphViz implemented in GHPython

5 Approximately two thirds of the generated fabrication drawings. These were CNC knife cut using two plastic sheets 6 (next page) A - E: Perspective and elevation renders captured straight from the Rhino viewport F: Remeshed shell after relaxation, visualising curvature 7 (next page) The process

of assembly took place in the large workshop of the Aarhus School of Architecture over the course of about a day using a single manual pop-rivet gun

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mapping the topological connectivity of the strips. Visualised here as a hierarchical tree diagram. Generated using DOT/ GraphViz implemented in GHPython

of assembly took place in the large workshop of the Aarhus School of Architecture over the course of about a day using a single manual pop-rivet gun

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pairs Dijkstraâ&#x20AC;&#x2122;s famous Shortest Path First algorithm [12] is implemented. The shortest property implying the least expensive path, as measured by the sum total of the edge weights travelled through. Dynamically manipulating edge weights can hence be used to intentionally steer the MeshWalker towards generating desirable properties of the strips, and the topology of how they run alongside each other. When edge weights are constant, the resulting walks tend to approximate geodesic face sequences that will unfold to fairly linear strips. This however has the tradeoff that strips will tend to veer away from each other, leaving small face islands in between them. Strips will furthermore be inherently short, which is arguably less aesthetically pleasing and additionally will produce increased assembly complexity. To counteract these features from emerging, we informed the shortest path algorithm to

preference traveling along the open/naked perimeter of the remaining graph. Under the conjecture that this would yield longer strips with fewer islands, at the cost of these being less linear when unfolded. This logic is implemented as the first step within the while loop. Where we identify edges ending in nodes with a valence smaller than three (i.e. these nodes/faces are naked) and set the weight of these to a value lower than one. Thereby increasing the perimeter attractiveness by making it less expensive to travel through. To search for fit solutions we implemented David Ruttens Galapagos solver [13]. Allowing it to rotate the destination line (around the three world axes) and manipulate the naked perimeter edge weight value, while attempting to minimise the occurrence of small walks. To unroll the strips into the plane for generating the fabrication drawings, the faces

that compose each mesh strip are iteratively rotated from one end of the strip to the other, using the angle to the next face subtracted from 180. Leaving each strip planar and orientated to the plane of its last face. These are orientated to the world XY plane and distributed along the Y-axis. Here the mesh perimeter polylines are offset inward to generate the hatch pattern between plates. A hexagon generated at each perimeter segment midpoint is unioned onto the polyline and filleted. A hole is generated at the midpoint, such that the overlapping hexagonal tabs can be riveted together along these plate-plate seams. The drawings are tagged by index and color, manually nested, and were cut using a CNC knife cutter in less than an hour. In order to determine an appropriate order of assembly we again turned to graph theory. Our conjecture here was to start from

the most connected strip first (i.e. the one connecting to most adjacent strips) and assemble out from here. To identify this central strip we generated another network graph, this time mapping the adjacencies of the strips (i.e. nodes are now strips and edges are coincident sub-perimeters shared between strips). By computing the sum of shortest path lengths from one node to all other nodes in the graph, the closeness centrality measure of this node can be determined [14]. The node with the highest centrality value is equal to the most connected strip. Contrary to the generative MeshWalker algorithm, this implementation of graph theoretical methods hence more strongly resemble conventional network analysis. Although here applied to a complex material system, and solving the sequence dynamics of how to quite literally compose the shell from the meso to macro scale within the physical world.

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REFERENCES Nejur, A. and Steinfeld, K. (2016) ‘Ivy : Bringing a Weighted-Mesh Representation to Bear on Generative Architectural Design Applications’, in Velikov, K., Ahlquist, S., Campo, M. del, and Thün, G. (eds) Proceedings of the 36th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA), pp. 140–151.

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2 Bourke, P. (1994) ‘Polygonising a Scalar Field’. Retrieved from www.paulbourke.net/ geometry/polygonise. 3 Reeves, D. (2019) Spatial Slur. Retrieved from www.github.com/daveReeves/SpatialSlur.

Botsch, M., Kobbelt, L., Pauly, M., Alliez, P. and Levy, B. (2010) Polygon Mesh Processing. A K Peters.

5 Piker, D. (2019) ‘Kangaroo3D’. Retrieved from www.kangaroo3d.com. 6 Deuss, M., Deng, B., Bouaziz, S., Pauly, M., Deleuran, A. H. and Piker, D. (2015) ‘ShapeOp - A Robust and Extensible Geometric Modelling Paradigm’, in Proceedings of Design Modelling Symposium 2015: Modelling Behaviour, pp. 505–515.

Catmull, E. and Clark, J. (1978) ‘Recursively Generated B-Spline Surfaces on Arbitrary Topological Meshes’, in Computer Aided Design, 10(6), pp. 350–355.

Hagberg, A. A., Schult, D. A. and Swart, P. J. (2008) ‘Exploring Network Structure, Dynamics, and Function using NetworkX’, Proceedings of the 7th Python in Science Conference, (SciPy), pp. 11–15.

Photography by CITA - Center for Information Technologies and Architecture Illustration by CITA - Center for Information Technologies and Architecture Illustration by CITA - Center for Information Technologies and Architecture Illustration by CITA - Center for Information Technologies and Architecture Illustration by CITA - Center for Information Technologies and Architecture Illustration by CITA - Center for Information Technologies and Architecture Photography by CITA - Center for Information Technologies and Architecture

12 Dijkstra, E. W. (1959) ‘A Note on Two Problems in Connexion with Graphs’, Numerische Mathematik, 1, pp. 269–271. 13 Rutten, D. (2013) ‘Galapagos: On the Logic and Limitations of Generic Solvers’, Architectural Design: Computation Works: The Building of Algorithmic Thought, 83(2), pp. 132–135. 14 Deleuran, A. H. and Derix, C. (2013) ‘Topological Infrastructure Analysis of the Built Environment’, EAEA-11 conference 2013 - Conceptual Representation: exploring the layout of the built environment, pp. 419–426.

8 Taubin, G. and Rossignac, J. (1998) ‘Geometric compression through topological surgery’, in ACM Transactions on Graphics, 17(2), pp. 84–115.

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10 Mitani, J. and Suzuki, H. (2004) ‘Making papercraft toys from meshes using stripbased approximate unfolding’, ACM Transactions on Graphics, 23(3).

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9 El-Sana, J., Evans, F., Kalaiah, a., Varshney, a., Skiena, S. and Azanli, E. (2000) ‘Efficiently computing and updating triangle strips for real-time rendering’, Computer-Aided Design, 32(13), pp. 753–772.

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2 Bourke, P. (1994) ‘Polygonising a Scalar Field’. Retrieved from www.paulbourke.net/ geometry/polygonise. 3 Reeves, D. (2019) Spatial Slur. Retrieved from www.github.com/daveReeves/SpatialSlur.

Botsch, M., Kobbelt, L., Pauly, M., Alliez, P. and Levy, B. (2010) Polygon Mesh Processing. A K Peters.

Catmull, E. and Clark, J. (1978) ‘Recursively Generated B-Spline Surfaces on Arbitrary Topological Meshes’, in Computer Aided Design, 10(6), pp. 350–355.

8 Taubin, G. and Rossignac, J. (1998) ‘Geometric compression through topological surgery’, in ACM Transactions on Graphics, 17(2), pp. 84–115.

1 2 3 4 5 6 7

10 Mitani, J. and Suzuki, H. (2004) ‘Making papercraft toys from meshes using stripbased approximate unfolding’, ACM Transactions on Graphics, 23(3).

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DeLanda, M. (2002) “Deleuze and the Use of the Genetic Algorithm in Architecture” in Designing for a Digital World” ed. Neil Leach, New York; Wiley, pp. 117-18

G. &. D. A. Beylerian (2007) UltraMaterials: How material innovation is changing the world, London: Thames and Hudson.

Weinan, E. (2011) Principles of Multiscale Modelling. Princeton University Press, New Jersey.

2 Nicholas, P., Ramsgaard Thomsen, M., Tamke, M., Holden Deleuran, A., Ayres, P., La Magna, R., & Gengnagel, C. (2017). Simulation in Complex Modelling. In Symposium on Simulation for Architecture and Urban Design (SIMAUD) (pp. 93-100)

2 Nicholas, P. Stasiuk, D. Clausen Nørgaard, E. Hutchinson, C. Ramsgaard Thomsen, M. (2015) “A Multiscale Adaptive Mesh Refinement Approach to Architectured Steel Specification in the Design of a Frameless Stressed Skin Structure”. Springer, Cham, Switzerland.

Ramsgaard Thomsen, M. (2016) “Complex Modelling—Questioning the infrastructures of information modelling”. In Complexity & Simplicity—Proceedings of the 34th eCAADe Conference - Volume 1. Herneoja, A. Österlund, T. Markkanen, P. (eds.). 34th eCAADe Conference. University of Oulu. pp. 33–42.

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3 Ramsgaard Thomsen, M. (2016). Complex Modelling: Questioning the infrastructures of information modelling. In A. Herneoja, T. Österlund, & P. Markkanen (Eds.), Proceedings of the 34th International Conference on Education and Research in Computer Aided Architectural Design in Europe: Complexity & Simplicity (pp. 33-42). eCAADe (Education and Research in Computer Aided Architectural Design in Europe) and ITU / YTU.

2 Tamke, M. Nicholas, N. Zwierzycki, M. (2018) “Machine learning for architectural design: Practices and infrastructure”. In International Journal of Architectural Computing, Vol 16, Issue 2. Sage Publications Ltd, London. 2018. 3 Stasiuk, D. Ramsgaard Thomsen, M. (2014) “Learning to be a Vault—Implementing learning strategies for design exploration in inter-scalar systems.” In Fusion, Proceedings of the 32nd International Conference on Education and research in Computer Aided Architectural Design in Europe. Vol. 1. eCAADe: Conferences 1. Northumbria University, Newcastle upon Tyne, UK. pp. 381–390

Ramsgaard Thomsen, M. (2016). Complex Modelling: Questioning the infrastructures of information modelling. In A. Herneoja, T. Österlund, & P. Markkanen (Eds.), Proceedings of the 34th International Conference on Education and Research in Computer Aided Architectural Design in Europe: Complexity & Simplicity (pp. 33-42). eCAADe (Education and Research in Computer Aided Architectural Design in Europe) and ITU / YTU.

2 DeLanda, M. (2002) “Deleuze and the Use of the Genetic Algorithm in Architecture” in Designing for a Digital World” ed. Neil Leach, New York; Wiley, pp. 117-18

Nicholas, P. Zwierzycki, M. Ramsgaard Thomsen, M. (2017) “Localised and Learnt Applications of Machine Learning for Robotic Incremental Sheet Forming”. In Humanizing Digital Reality: Design Modelling Symposium Paris 2017. Springer, Singapore. pp. 373–382.

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DeLanda, M. (2002) “Deleuze and the Use of the Genetic Algorithm in Architecture” in Designing for a Digital World” ed. Neil Leach, New York; Wiley, pp. 117-18

G. &. D. A. Beylerian (2007) UltraMaterials: How material innovation is changing the world, London: Thames and Hudson.

Weinan, E. (2011) Principles of Multiscale Modelling. Princeton University Press, New Jersey.

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2 DeLanda, M. (2002) “Deleuze and the Use of the Genetic Algorithm in Architecture” in Designing for a Digital World” ed. Neil Leach, New York; Wiley, pp. 117-18

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PEOPLE

CITA ACADEMICS

VISITING FACULTY

PH.D STUDENTS POST DOCTORATES

RESEARCH ASSISTANTS

INTERNS

Mette Ramsgaard Thomsen Professor and Head of CITA 2005 - present

Christoph Gengnagel Velux visiting Professor UdK Berlin 2013 - 2019

Anders Holden Deleuran PhD cand. 2014 - present

David Andres Leon Research Assistant 2016 - 2017

Amelie Unger Intern 2016

David Stasiuk PhD cand. 2012 - 2019

Esben Clausen Nørgaard Research Assistant 2014 - 2017

Ashkan Cheheltan Intern 2016

Riccardo La Magna Post Doctorate 2016

Henrik Leander Evers Research Assistant 2012 - 2017

Hasti Valipour Goudarzy Intern 2015

Hollie Gibbons Research Assistant 2014

Patrick Welss Intern 2017 - 2018

Martin Tamke Associate Professor 2006 - present Paul Nicholas Assistant Professor 2011 - present Phil Ayres Associate Professor 2009 - present

Michel Schmeck Early Stage Researcher UdK Berlin 2016 Billie Faircloth Velux Visiting Professor Kieran Timberlake Philadelphia, USA 2015 - 2017 Ryan Welsch Senior Researcher Kieran Timberlake Philadelphia, USA 2015 - 2017

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PEOPLE

Danica Pistekova PhD at Academy of Fine Arts Bratislava, Slovakia 2016 Gregory Quinn PhD at Udk Berlin 2013 - 2016 Cecilie Søs Brandt-Olsen Researcher, PhD at DTU BIG Enginnering 2016

Ida K. F. Tinning Research Assistant 2014 - 2016 Mateusz Zwierzycki Research Assistant 2015 - 2017 Petras Vestartas Research Assistant 2017 Scott Leinweber Research Assistant 2015 - 2016 Sebastian Gatz Research Assistant 2017 - present

Sebastian Risi Assistant Professor ITU 2015

Vasiliki Fragkia Intern / Research Assistant 2017 - 2018

Mark Burry Professor Swinburne University Melbourne, Australia 2016

Yuliya Šinke Baranovskaya Research Assistant 2016 - 2019

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Claus Bollinger Professor IOA Vienna, Austria 2016

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PEOPLE

CITA ACADEMICS

VISITING FACULTY

PH.D STUDENTS POST DOCTORATES

RESEARCH ASSISTANTS

INTERNS

Mette Ramsgaard Thomsen Professor and Head of CITA 2005 - present

Christoph Gengnagel Velux visiting Professor UdK Berlin 2013 - 2019

Anders Holden Deleuran PhD cand. 2014 - present

David Andres Leon Research Assistant 2016 - 2017

Amelie Unger Intern 2016

David Stasiuk PhD cand. 2012 - 2019

Esben Clausen Nørgaard Research Assistant 2014 - 2017

Ashkan Cheheltan Intern 2016

Riccardo La Magna Post Doctorate 2016

Henrik Leander Evers Research Assistant 2012 - 2017

Hasti Valipour Goudarzy Intern 2015

Hollie Gibbons Research Assistant 2014

Patrick Welss Intern 2017 - 2018

Martin Tamke Associate Professor 2006 - present Paul Nicholas Assistant Professor 2011 - present Phil Ayres Associate Professor 2009 - present

CITA Complex Modelling

PEOPLE

Danica Pistekova PhD at Academy of Fine Arts Bratislava, Slovakia 2016 Gregory Quinn PhD at Udk Berlin 2013 - 2016 Cecilie Søs Brandt-Olsen Researcher, PhD at DTU BIG Enginnering 2016

Sebastian Risi Assistant Professor ITU 2015

Vasiliki Fragkia Intern / Research Assistant 2017 - 2018

Mark Burry Professor Swinburne University Melbourne, Australia 2016

Yuliya Šinke Baranovskaya Research Assistant 2016 - 2019

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Claus Bollinger Professor IOA Vienna, Austria 2016

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