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CONTENTS I.
Introduction
II.
Theoretical Framework A. Complex Adaptive Systems and Adaptation B. Morphogenesis in Biology and Architecture C. Heterogeneity and Performance D. The Notion of Non-Linearity E. The Nature of Cybernetic Architectural Production F. The New Digital Materiality - A Soft System between Virtual and Physical
III.
Space Design Through Physics and Perception A. Proprioception and Directional Pull in Space B. Fluidity and Expansion in Space
IV.
Cellular Division Algorithm and Developed Tools A. Cellular Division Algorithms B. Main System Forces C. Space Division Algorithm D. Developed Analysis Tools E. User-Interface Application
V.
System Analysis and Design Control A. Effect of System Forces on Topology B. Curvature Analysis and Topology C. Initial Design Studies D. Design Control of Particle Selection and Division Rate E. Design Control of Cleavage Selection F. System Summary
VI.
Design Search and Pattern Classification A. Design Search through Discrete Cases B. Design Evolution through Probability Distribution C. High Resolution Formations
VIII.
Material and Structure A. Geometry Rationalisation B. Porous Structure Research C. End-effector Design D. Column Prototype E. Porous Concrete Study F. Exhibition Wall Prototype
VIII.
References
IX.
Appendix A. Term 1 Chair Design Workshop // Agent System B. Term 1 Chair Design Workshop // Surface Adaptation and Fibre Formations C. Topoform Group
Chapter I Introduction
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morpho[cyte] morpho[cyte]: morph + cyte, the cell that generates form // morph: derived from the greek word 'μορφή', meaning 'form' // cyte: suffix denoting a cell, derived from the Greek word 'κύτταρο', meaning 'cell'
The research presented throughout this volume focused on digital morphogenetic processes and material and fabrication investigations which were employed in a number of different areas. More specifically, a part of the research looked into computational processes for the development of a design system based on cellular division, combined with a number of custom analysis tools and a userinterface application. The developed design system was then employed for design application on the design project of the research looking at space design in relation to physics and perception and how this kind of generated spaces can produce novel spatial experiences. Another part of the research looked into material processes and different fabrication techniques in bridging the gap between the digital morphogenetic process and fabricated outputs, which was also combined with the investigation of high-resolution heterogeneous fabric of architecture in terms of structure and performance through varying density and porosity. Finally, the research also focused on design search and pattern classification, employed through evolutionary and supervised machinelearning techniques in order to explore the system's generative potential and the possibilities of the design space, and enabling automation of the design process. 7
Chapter II Theoretical Framework
A. Complex Adaptive Systems and Adaptation
In order to investigate grown structures through cellular division, research was made on the theory behind complex adaptive systems and their adaptation ability, as defined by the pioneer of the field John Holland in his book “Hidden Order” [Holland, 1995], in order to have the necessary theoretical tools for understanding nonlinear and complex phenomena, such as adaptive and self-organized grown structures. Key theories on cas from biologist Stuart Kauffman and cognitive scientist Douglas Hofstadter were also reviewed, along with the concept of evolution through natural selection and adaptation as defined by anthropologist Charles Darwin, and further analyzed by biologist Douglas Futuyma. Holland outlines the omnipresence of cas in different scales of natural and artificial systems, all presenting a number of common properties and mechanisms, which are aggregation, nonlinearity, flows and diversity, and tagging, internal modeling and building blocks in respect [Holland, 1995, p.38]. In terms of the adaptation ability, sets of simple rules are triggered by external stimuli, in the logic of if/then conditionals, and lead to local agent adaptation, referred as performance system [Holland, 1995, p.43]. Rules can be combined, leading to emergent behavior and nonlinear outputs, while the strength of each rule can vary, mentioned as credit assignment [Holland, 1995, p.53]. Novel conditions triggered by multiple rules are organized as new building blocks, which help in organising the emergent outputs [Holland, 1995, p.51]. In this research, the properties and mechanisms of cas are used for a better understanding of the developed system's behaviour. Taking place in the same period, the work of S. Kauffman offers more insights on cas and their adaptation ability. In his book “At Home in the Universe” [Kauffman, 1995], Kauffman mentions the ability of these systems to adapt based on a set of simple rules, leading to emergence and complexity out of simplicity, referred as ‘Order for Free’ [Kauffman, 1995, p.30] and having similarities with the mechanisms of Holland. According to Kauffman, mechanisms and concepts such as evolution, coevolution, cell specialization and order out of chaos are the result of adaptation and self-organization in natural systems in order to improve the systems’ fitness [Kauffman, 1995, p.33]. The observation of Kauffman of ‘Order for Free’ is also described in the essay Ant Fugue, written by D. Hofstadter [1979], which presents many similarities with Holland’s cas. In his essay, Hofstadter uses the example of an ant colony to illustrate how a group of relatively unintelligent parts, namely ants, following a set of simple rules, has the ability to form a kind of intelligence and complex behavior when aggregated in big numbers [Hofstadter, 1979, p.166], which is the ant 10
colony in this case (fig.9,10). The ideas of holism and reductionism, or top-down and bottom-up approaches, are used as two different ways for understanding cas [Hofstadter, 1979, p.159], while their combination is essential in order to get a better understanding of a system’s complex behavior. According to biology, evolution can happen through mutation, natural selection, genetic drift or gene flow, with natural selection explaining the adaptation processes of organisms to their environment [Mazzoleni, 2013, p.30]. Looking at the concept of evolution and natural selection as defined by Charles Darwin in his seminal book “The Origin of Species”, it is presented that the main driving force is competition and it is interpreted through a constantly active and changing co-adaptation mechanism in an effort for survival [Darwin, 2009, p.67]. The Darwinian analogy of evolution through natural selection can be seen in the ideas of both Holland and Kauffman, as constant adaptations of a system’s elements in varying timescales and levels of order can lead to its evolution. The timeframe within which evolution and adaptation processes can take place also varies, falling under the categories of macroevolution and microevolution, with the former referring to processes taking place at or above the species level, such as evolution occurring over millennia, and the latter taking place within a population or the lifetime of a generation in a species [Mazzoleni, 2013, p.35]. Finally, according to D. Futuyma, adaptation processes in natural systems aim in improving the chances for survival or reproduction through better fitness in their environment [Futuyma, 2009, p.279], but while there seems to be a definite goal, the individual elements of each system follow rules that are devoid of meaning [Futuyma, 2009, p.283], and the goal can be identified only when observing the system from a holistic point of view.
B. Morphogenesis in Biology and Architecture The term morphogenesis in science has its basis in biology, and it concerns the growth process of an organism which is directly related to its form and the rules underlying it [American Heritage Dictionary], while this process is the result of the constant interaction between form and energy [Wade, 2007, p.46]. One of the most important and early systematic approaches on the relationship between form and growth is the seminal work of D’Arcy Thompson “On Growth and Form” [Thompson, 2014], first published in 1917, which concerns the growth of form in nature and the mathematical rules underlying it.
Alan Turing and Biological Morphogenesis
In 1952, Alan Turing [Turing, 1952] described each cell in living creatures as a vector which is based on bio-chemicals. At the time that these cells grow and evolve, their bio-chemicals not only interact solely at the intra-cellular level, but also at the inter-cellular level with each surrounding cell. Turing focussed on the embryonic stages of cells before they start growing into their final specifications. Taking the frog as an example, he highlighted its early initiation as a result of the division of a zygote, followed by a chain of cellular divisions that eventually create an aggregation of cells that starts defining the embryo. This embryo, as Turing claims, starts creating its symmetrical line, and during that stage the first cells start showing new behaviours, and divide for specific tasks, some of which create the skin, others become part of the heart, others the blood cells, etc. This procedure is exactly what caught Turing’s attention. In his paper on 'The Chamical Basis of Morphogenesis' he was able to back up his claim about what happens biologically shortly after fertilisation, where identical sub-units emerge which shortly thereafter move from an isotropic (i.e., homogeneous in behaviour) state to one that is anisotropic – that is to say, when these identical sub-units start exhibiting different behaviours and tendencies despite their common substance therefore one could reasonably talk about the emergence of heterogeneity in behaviour (NB., not in substance).
Basic growth process through the developed morphogenetic system that is based on cellular division
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Within the context of this research, the concepts of cell specialisation and agreggation in biological processes that give rise to behavioural heterogeneity and different function were used as drivers for feeding information into the developed design system and contributing on the development of the design methdology.
Morphogenesis in Architecture
In architecture, Morphogenesis has been defined by Achim Menges as a design approach that merges morphological complexity with performative capacity [Menges, 2007, p.727], while it is comprised of continuous differentiation of morphology and its related performance, which results to a system’s overall performance [Menges, 2012, p.2]. Morphogenesis in architecture is also defined by Neil Leach in his article “Digital Morphogenesis” [Leach, 2009], referring to ‘a bottom-up logic of form-finding through processes of growth and differentiation’ [Leach, 2009, p.34] that draws inspiration from biology. In the scope of this research, morphogenesis refers to the merging of the above mentioned architectural definitions, integrating performative qualities in architectural form-finding through a digital growth process that is inspired by processes found in natural systems, while also focusing on the aesthetic qualities that are being producing through this exploration.
Design output from the developed morphogenetic system based on cellular division. The morphogenetic process is inspired by natural processes, operating on bottom-up growth processes of self-adaptation 12
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C. Heterogeneity and Performance
Heterogeneity, referring to the occurrence of different formations or qualities throughout a natural or artificial system [Hight, Hensel, Menges, 2009, p.12], is an indispensable quality found in grown and adaptive structures in nature. In order to set a better understanding, the concept of heterogeneity is presented below as used in the philosophy of Gilles Deleuze in his book with Felix Guattari “One Thousand Plateaus” [Deleuze, Guattari, 2004] through smooth and striated space, forming the theoretical framework for the use of the term in this research. After an overall interpretation of the text, smooth space could be described as highly dynamic and constantly changing, similar to cas and their constant adaptation, while striated space is more rigid and inflexible, similar to formal and top-down approaches. The two spaces always coexist and the one transforms the other in different ways [Deleuze, Guattari, 2004, p.474]. Smooth is fundamentally characterized by heterogeneity, but its sole existence would lead to amorphous results due to its constant change, while its coexistence with striated generates a different kind of heterogeneous space that allows a better definition of change within a rigid structure [Deleuze, Guattari, 2004].
the system and other systems in its environment [Hight, Hensel, Menges, 2009, p.16]. According to the authors, the combination of different performances, such as structural and thermal performance, and the local adaptation of the system's elements is what will give rise to the creation of heterogeneous spaces [Hight, Hensel, Menges, 2009, p.34] that are locally discontinuous and diverse, but globally coherent [Hight, Hensel, Menges, 2009, p.16]. This twofold condition, namely local discontinuity and global coherence, is in line with the concept of smooth and striated space by G. Deleuze, and with the bottom-up logic of cas and the top-down approach of holism in respect. Moreover, Deleuze's ideas about the constant coexistence of smooth and striated space and the possible relationships between the two are used by the authors for proposing the need for the coexistence of homogeneous and heterogeneous space within the same structure [Hight et al, 2009, p.16].
In natural systems smooth precedes striated, with striated taking over smooth, but the latter reappears in a different level inside the striated structure and interacts with it [Deleuze, Guattari, 2004, p.480] (fig.12). Other interesting states involve the transition from one to another, their change of state, as well as their superposition [Deleuze, Guattari, 2004, p.482]. According to Deleuze, the interaction forces between smooth and striated are also their most interesting characteristic, while he mentions that ‘even the most striated city gives rise to smooth spaces’ [Deleuze, Guattari, 2004, p.500]. The relationship between heterogeneity and performance can be found in a variety of scales in natural systems, ranging from the cellular to that of a living organism. Starting from the cellular scale, architect David Wade mentions in his book “LI – Dynamic Form in Nature” [2007] that different cell types can be symbiotic and carry different functions and roles, leading to heterogeneous formations [Wade, 2007, p.14]. Based on a similar observation, architects Michael Hensel, Achim Menges and Christopher Hight have proposed the concept of heterogeneous space in architecture [Hight, Hensel, Menges, 2009], calling for an 'ecological' approach towards design, in the sense that it is not aiming in achieving formal heterogeneity, but rather differentiation in terms of performance through the study of the interactions between 14
Opposite page: Design output through the use of the cellular division algorithm with varying degrees of heterogeneity and the constant negotiation between smooth and striated space
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D. The Notion of Non-Linearity It would be helpful to refer back to Holland’s Hidden Order [Holland, 1995], in which the author adopts mathematical models to analyse how non-linearity functions. This assists the research in seeking how to create complex adaptive systems with applications across fields including architecture and design. A number of examples are presented below in order to clarify Holland’s explanation.
“Genes are no more than rudimentary anchors or triggers in a manifoldly more complex dynamic system of active, nonlinear interrelationships. In other words, genes work together in large, integrated complexes to produce effects rather far removed from, and infinitely more subtle than, the raw information stored in their own molecular data banks.” [Kwinter, 1993]
In a prey-predator interaction sketch Holland had predators presented by one letter, say U, in a specified area while the prey presented in another letter, say V, for the same area. The number of interactions between predators and prey can be found by cUV, where c here is a constant that refers to the efficiency of the predators, or in other words, their possibilities of encountering the prey, for instance, having 2 predators and 10 prey running in one area for a specified amount of time and 0.5 chance of encounters will give us the following:
The foregoing sheds some light on the almost mysterious dynamic of such systems given that it is not a matter of rigid linear information exchanges, but it is more of extremely complex interactions that point towards underlying superior adaptive abilities based on the interactions at the inter and intra levels that deal with information within the system and its surrounding environment.
cUV = 0.5(2)(10) = 10 encounters per day per square mile.
By doubling the number of both predators and prey, the number of encounters will actually quadruple, which means that this process is non-linear because the outcome is actually not only the sum of the two variables but their product.
cUV = 0.5(4)(20) = 40 encounters per day per square mile.
From the above it becomes clear that the process in not only based on the sum of two activities. This is but an over-simplified example. Kwinter however has referred to other more complex examples, such as processes found in genetics. In his Soft Systems [Kwinter, 1993] he refers to how various scientists attempted removing the genes responsible for inheriting the eyes in the drosophila fly; however, although the eyes did disappear for a couple of generations, they started reappearing as normal. This experiment illustrates how an organic, living, system is actually more complex and non-linear than to think of it as specific genes holding clear information and passing it on. In other words, such systems are much more than just the sum of their parts. They are a mixture of enormous malleable and interactive processes that keeps these systems flowing and developing.
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As discussed earlier with the ichthyosaur example, albeit with regard to the adaptivity of a broader system –e.g., the oceans – and the occupation of a vacant niche, that example also brings to mind Darwinism as the dominant theory of the evolution of creatures based on their environments, and here one could observe two evolving processes at play; on the one hand, at the agent level and the adaptation of each agent with its environment, and on the other, at a higher level, where the whole system might replace groups of agents with others based on the needs of that system; e.g., such as a species of insects in a rainforest system which might disappear due to the emergence of another species and be replaced by a similar species with a very similar role but adapted following the extinction of the previous species.
Opposite page: Non-linear design output which is the result of local adaptations triggered by local rules. Slight changes to the parameter values would lead to completely different and unpredictable outputs
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E. The Nature of Cybernetic Architectural Production
Another area of investigation as part of this research is the natural relationship between cybernetic and architectural production from a number of early studies by artists and scientists. The vision of novel architectural production as a continuous but in the same time discrete process of mechanical production system has been elegantly illustrated by a French artist, Villemard, from one of the images of 1910’s prints which depicted life in the 2000s, titled Building Site. In the history of cybernetic art, this utopian visual art tried to predict the life of a future architect who is working on the site of a building construction with a series of mechanical material processing by different kind of machines that take commands from such a control panel, mastered by the architect himself. It is noticeable that this vision has innovatively introduced a new way of thinking in architecture production, when architects no longer work by structuring spatial composition, but rather composing a series of material process as a continuous system of discrete commands. In conjunction to the specific experimentation that has been done for this research, Villemard’s idea has given a valuable initial concept for programming the framework of industrial robot toolpath as a discrete but continuous material processing based on different kind of design criteria that is generated by the initial topological geometry. At the same time, working with topology enables us to extract a number of parameters from the initial generated geometry itself to be processed inside a cybernetic system as an embedded data that is valuable for production purpose such as curvature, finite element, etc. Different parts of the design will perform different parameters of performance that require different sets of toolpath to fabricate the material into the desired object. Such a concept that is explained above was also theoretically introduced by Gordon Pask [Pask, 1969] as the architecture relevance of cybernetic. In his concept, Pask [ibid, p68] also mentioned that naturally, cybernetic and architecture share the same common philosophy of an operational research. This term of operational research is considerably articulated into architectural terminology as a process of material and formal language that works as one assembly of geometric realisation through fabrication. In its initial definition by Pask, cybernetic term means a system that is based on regulation, control, adjustment and purpose, filtered through means of feedback. For the purpose of this research, control enables the architect or designer to design specific purpose by a set of regulations. Feedback gives more adaptiveness of the designed regulations to create adjustment with the reality of the design object as matter. In the specific case of the experimentation for this research, the extracted parameters from the initial topological geometry work as a 18
set of control that affect specific regulations for the robotic fabrication toolpath. A similar idea was also introduced by Varenne [2013, p96] who argued that architecture is defined as a prescription or synthesis of mathematical models that has a series of basic principles which he called mould, module and model. Those principles enable us to optimize the form of architecture through a number of technical or aesthetic aspects by discrete and local definition. In this research, generally it is important to set operations or actions with specific parameters that are assembled into a single sequence to obtain specific purpose or goal of the cybernetic system itself. However, according to Pask [1969], cybernetic relevance of architecture is not only playing in the role of architecture as a creation of object as matter, rather widely seeing architecture as an engineered environment that works as cybernetic machine in multi-dimensional approach. Hence, Varenne’s argument is taken as a clear border of this research thesis to limit the concept of architecture as a cybernetic system that merely focuses on the construction and realisation of architectural object through a sequence of material and formal process. In this case, the simulated topological initial geometry and its embedded information are set as a global definition of the programmed cyber-physical system, when the interwoven formation of the thermoplastic material assembly works as a discrete and local operation of the system to achieve the global purpose.
Opposite page: Materialization experiment of the emergent geometry through substractive fabrication method as a tectonic surface
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F. The New Digital Materiality - A Soft System between Virtual and Physical 'Conversely, we are not talking about building systems that can be configured endlessly in the virtual space of a computer. Rather the constructive logic of programming and the material realization are linked to each other' - Willmann, Gramazio, Kohler, 2012 The synthesis of data and material, which decisively failed to develop in the early digital age, is being realized – enticingly, playfully, and sensually – in the recent architecture. This becomes apparent in various material, spatial and structural manifestations, whereby one premise persists. In the moment in which two seemingly separate worlds meet through the interaction between digital and material processes, data and material can no longer be interpreted as a mere complement but rather as an inherent condition thus an essential expression of architecture in digital age. This emerging digital materiality is interplaying between data and material, virtual and physical in the last few decades as an entirely new conception of the material world. The capacity of matter becomes real in both virtual and physical conditions [Delanda, 2015]. Materialisation works as a catalyst, triggering the actuality of matter from the state in which an organism is actual but virtual into reality in physical state by constructing a design of production. Thus, materialisation process becomes one of the most prominent process of the research. Dealing with the quasi random flowing topological surface inside the software, fabrication agency must be then considered further together with the production cybernetic system to transform it into real architectural artefact. Materialisation algorithm works as a soft cybernetic system that is flexible, adaptable and evolving when it is complex and maintained by a dense network of active information or feed loops [Kwinter, 1996]. Constructing the reality of matter in both virtual and physical by generating toolpath and material formation for fabrication.
Opposite page: Digital model of the developed heterogeneous porous concrete structure with varying degrees of porosity 20
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Chapter III Space Design through Physics and Perception
Spatial sculptures of Richard Serra used as initial inspiration for the design of spatial structures in relation to perception (image references: see chapter VIII)
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The design project of this research focused on the effect of physics and perception in space design through the use of the cellular division algorithm for creating spatial experiences. The research looked into the concept of proprioception, defined by Brian Massumi as 'a selfrefferential sixth sense directly attuned to the movement of the body' [Massumi, 2002, p.179], and how the generated structures could be perceived through this sixth sense, resulting in changing the way that users move and interact inside them. The work of artist and sculptor Richard Serra and his generated spaces through torque ellipse structures that create strong spatial experiences that alter the user's movement in space were used as a starting point and inspiration for approaching the design process.
A. Proprioception and Directional Pull in Space The set of designs presented throughout this section aimed in modifying the way that users perceive these spaces when walking through them, causing them to accelerate, change their body position in relation to the structures surrounding them, or getting a feeling of disorientation, with all cases being related to experiencing the space through proprioception. Most of the designs involve confined spaces that isolate the users from their surroundings, while the combination of such spaces with high resolution formations on them that involve strong directionality, fludity or other qualities, lead eventually to novel spatial experiences.
Basic spatial structure comprised of two walls with varying pattern formations in different parts, aiming in different spatial experiences 25
Physics and Disorientation // Space Growth Process through Cellular Division
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Confined space with high resolution formations presenting strong directionality and causing a gravitational pull 29
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Spaces with a strong sense of hotizontal directionality and fluidity that amplify the overall direction of the structure 31
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Torque structures with strong directional pull effect, amplified greatly by the generated formations on the structures' surface 33
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Directional Pull and Twisted Surface // Growth Process through Cellular Division
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Close-up perspective of the subdvided twisted surface creating an effect of strong concentrated pull force towards it 39
B. Fluidity and Expansion in Space Design proposals in this section are focused towards a more architectural approach through the generation of tectonic structures that create space enclosure. The design outputs presented throughout this section are based on the effect of physics on creating the sense of a fluid structure that expands or shifts in space through different pattern formations.
The design presented in this page forms a continuous cavernouslike interior space in which ceiling and walls are merged into one single skin, while the division rules that generated the design combine directional growth with branching formations for generating a core around which the space seems to develop and expand. Similar to primitive sheltering, the space gives the sense of a total enclosure found in cavernous spaces, which could result in the emergence of novel spatial experience.
Cavernous interior space with a strong sense of expansion and fluidity through the fluid branching formations that give the sense of a main structural core expanding in space. 40
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Caveronous interior space with fluid branching formations, producing a hybrid structure combining primitive shelter experience with natural-like formations 42
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Open space with strong directionality and fluidity, affecting the user's spatial perception and giving the sense of a structure that is on constant movement 44
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Continuous column and ceiling structures with fluid branching formations expanding in space, being closer to familiar tectonic elements, while also generating novel spatial experience through the generated formations on them 47
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Chapter IV Celluar Division Algorithm and Developed Tools
A. Cellular Division Algorithms
1_Cleavage selection and creation of new point
Cellular Division Algorithm for Internal Points
Selection of particles between which links are
The main developed algorithm of this research is a cellular division algorithm, based on the work of digital artist Andy Lomas and described in his research paper "Cellular Forms: An artistic exploration of Morphogenesis" [Lomas, 2014].
The algorithm can be applied on the vertices of a closed topological surface, or on the non-naked vertices of an open surface. The logic of the algorithm is based on a number of steps, as described nearby. Each particle is connected to a number of linked particles, and each set of three linked particles is used for the generation of a mesh face, resulting in a triangulated mesh surface. Each list of linked particles for a point is sorted in a clockwise order, which has to be taken into consideration when modifying the topology of the surface through the division process, and update accordingly the indices of the new linked particles.
cut and faces deleted. The new point is generated on the average position of the particles that will be linked to it.
2_Creation of new connections Connections are made between the new particle and its neighbors. The lists of linked particles and linked mesh faces for the new particle are created.
3_Update of linked particles and linked mesh faces for the divided particle The two lists for the divided particle are updated so that the clockwise order remains and all the linked particles and faces are properly sorted.
4_Update of linked particles and linked mesh faces for all the linked particles of the divided particle All the lists for all the neighbor particles have Initial Condition Selected particle with its lists of linked particles and mesh faces 52
to be updated in order for the right order to be maintained in all the parts of the surface.
Sample growth process of an icosahedron used as initial geometry trough the use of the cellular division algorithm
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Cellular Division Algorithm for Border Points
1_Creation of new point The new particle is created
Based on the basic cellular division algorithm, another algorithm was developed for the division of particles that are located on the borders of an open topological surface. Folllowing a similar logic, the algorithm is described in this section in a number of steps.
on the right side of the selected edge particle and its location is the average position of its neighbor particles. Initial conenction with the adjacent edge particle is cut.
In order for the algorithm to work properly, it was essential all the border particles to be sorted in a clockwise order initially, so that the topology of the surface after the division process could remain organised and the indices of the elements of every list of linked particles and linked mesh faces could be updated correctly.
2_Creation of new connections New connections are made between the new particle and its neighbors. The lists of linked particles and linked mesh faces for the new particle are created.
3_Update of linked particles and linked mesh faces for the divided point The two lists for the divided particle are updated so that the clockwise order remains and all the linked particles and faces are properly sorted.
4_Update of linked particles and linked mesh faces for all the linked particles of the divided point All the lists for all the neighbor particles have Initial Condition
to be updated in order
Selected border particle with linked particles
for the right order to be
and linked mesh faces
maintained in all the parts of the surface.
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Sample growth process of an open circular surface used as initial geometry being divided on its edges
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Cellular Degeneration Algorithm
1_Selection of particle for creating opening
Following the same logic of modifying the topology of the initial surface, an algorithm for creating openings across the topological surface was developed. The same logic of modifying the connections and updating the lists of linked particles and linked mesh faces is followed, as described in this section.
The logic of this algorithm is the opposite of the two previous ones, as instead of producing new particles and being related to growth, it causes particles to be removed and it is closer to a cellular death process. In mathematical terms, this algorithm is an effective way of converting an initially closed topological surface to an open surface.
A particle is selected in order to modify the topology around it and create an opening on the surface.
2_Cut existing links The existing links between the selected particle and its linked particles are deleted, and the global mesh faces in this position are removed from the main array list.
3_Delete selected particle The selected particle is removed from the global array of particles, and removed from the topological surface.
4_Update of linked particles and linked mesh faces for all the initially linked particles of the deleted point The lists of all the initially linked particles have to Initial Condition Particle with its lists of linked particles and linked mesh faces 56
be updated in order to be sorted correctly again in a clockwise order.
Sample growth process of an icosahedron used as initial geometry on which openings are created through the use of the void generation algorithm
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B. Main System Forces Overview of system forces
Each particle in the system is comprised of a number of forces that act onto it and affect how the overall topology is modified during the digital growth process. The following forces are used into the system, based on the cellular growth system as developed by Andy Lomas [Lomas, 2014].
Spring Force
The interaction between these forces is necessary for generating form variation and heterogeneity throughout the structure, while absence of one of the forces would lead to amorphous or too homogeneous design outputs. Bulge Force
Spring force Springs that keep each particle connected to its neighbours. The force is based on Hooke's law, and it is controlled by the springs' rest length and strength
Bulge force Force that tends to move each particle along the average direction of its normal position in relation to its neighbours, similar to a torsion spring, leading to increased bulging of the overall topology. Planar Force
Planar force Force that tends to make the topology of every particle more planar, based on the average position of its neighbours.
Separation force Force that works in the same logic as the collision detection algorithm, in order to maintain a minimum distance between each particle, otherwise the result leads to an incoherent state of the topological surface. Separation Force
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C. Space Division Algorithm Collision-detection optimisation
In order to simulate increased number of particles for achieving high resolution outputs and minimising the simulation time, the design system had to be optimised. Apart from optimising the main algorithm for being less memory-intensive, it was found out that the most memoryconsuming process of the system was the collision-detection algorithm, used as part of the separation force, which had to be optimised through a space division algorithm. Simple collision-detection
In the initially generated algorithm, each particle of the system would calculate its distance from each other paticle of the system for collision-detection. As a result, increasing the number of particles by n times would lead to nn number of calculations. Regular grid and octree approaches were investigated, but due to the fixed boundaries of the design space and the simplicity of applying it, the former option was implemented. The approach involved the generation of a three-dimensional regular grid covering all the design space, similar to the logic of a voxelised space, while each particle was assigned an id based on its position within this grid. As a result, the collision-detection is performed only between particles that belong to the same voxel or its neighbor voxels, greatly reducing the number of calculations and reducing the simulation time while saving system memory.
Optimised collision-detection through regular grid
Example of an initial geometry with fixed space boundaries and its separation grid used for optimising collision-detection
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D. Developed Analysis Tools A number of analysis tools were also developed as part of the design system, used for achieving a better understanding and control of the morphogenetic process and maintaining a more performanceoriented design approach. The developed tools are based on a finite element analysis approach of the topological surface and they are used for calculating and analysing curvature, stress deformation and face area. Description of these tools is made throughout this section.
Curvature Analysis The curvature analysis tool calculates the Gaussian curvature for the Voronoi area around each particle, based on the following equation, as described in a research paper on curvature for 3D meshes [Guillaume, L., Florent, D., Attila, B, 2004].
where θ is the sum of the angles between the selected particle and its linked particles, and A is the Voronoi area for the linked mesh faces of this particle.
In addition this tool, another data mapping tool was developed that displays the distribution of the curvature values over the whole structure so that it can provide direct feedback to the user during the simulation.
Example of the developed curvature analysis during the simulation of a closed topological surface that is being subdivided through cellular division 60
Mapping of curvature data
Stress Deformation Analysis
A simplified structural analysis tool was developed based on Hooke's Law for analysing the generated structures in terms of structural performance through the calculation of the stress deformation for every vertex of the geometry.
A number of parameters have to be set in order to run the analysis tool, including anchor points that are in contact with the ground, setting the spring values and the weight of each vertex as self-load based on
the tested material's properties, and also adding any necessary external loads, depending on the investigated case.
The approach is simplified and cannot be used for precise calculations, but it is used as guide for making general conclusions about the structure's performance that is used as feedback on directing the morphogenetic process.
Example of the developed structural analysis tool for calculating and analysing stress deformation throughout the structure
Zero stress deformation
Low stress deformation
High stress deformation
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Face Area Analysis
A face area analysis tool was also developed for mapping the difference between the size of each triangulated face throughout the structure, while also using the area data of each triangle for controlling the morphogenetic process. In order to calculate the area for each face, the following equation was used
where a and b is the length of two of the edges for each triangulated face and θ is the angle between these two edges.
Wireframe Display
Although not an analysis tool, a wireframe display of the geometry was used as part of analysing the structure during its generation through the cellular division process, showing the different densities of particles throughout the structure and areas that have been subdivided further.
Wireframe display of the geometry used for displaying the varying densities of particles across the generated geometry
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Face Area analysis tool mapping the area of each triangulated face in relation to the area of the faces throughout the structure
E. User-Interface Application Due to the complexity of the morphogenetic system, a user interface was developed for accommodating design search by making the simulation environment more simple and user-friendly for being able to be used also by people without any coding knowledge. In this way, more design possibilities could be explored and analysed.
The application is shown below, including the various design functions, analysis tools and different display modes, sliders for adjusting the values of the main parameters, displayed simulation and geometry data and a number of default initial geometries for general experimentation with the algorithm.
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Chapter V System Analysis and Design Control
Due to the complete bottom-up logic of the system and the increased number of parameters affecting the digital growth process, the developed morphogenetic system presented increased degrees of complexity, so a more analytical study was made, in order to get a better understanding of how the various inputs affect the generated geometry and achieve increased design control.
This chapter presents the research made in achieving the desired design control, starting with the analysis of the effect of the various system forces on the topology, followed by the relationship between curvature, topology and different topological properties. Moreover, the effect on the geometry of different rules for making the selection of the points to be divided is presented along with some of the initial design studies, while the chapter concludes with the developed rules that govern which two points are being selected for cleavage selection as part of the cellular division process once a point is being selected to be divided.
A. Effect of System Forces on Topology The effect of the various forces on the topology of the growing geometry was investigated, presented in this section in the two following diagrams in which interrelated parameters are investigated together. Looking at the diagrams, the following observations can be made:
• Increasing the spring rest length causes the geometry to expand, while increasing the spring strength leads to more spiky topology, and each effect is amplified when both are increased. • Increased bulge force makes the geometry expand as if it is inflated. • Increased planar force makes the geometry smoother and transforming it towards a more planar state. • Bulge force and planar force are counteracting towards each other, and a variety of different formations are produced, with the more interesting outputs being around an equilibrium state in which the effect of each parameter does not prevail over the other.
Diagram showing the effect of spring rest length and spring strength on the topology of the digitally grown geometry through the cellular division process
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Effect of bulge force and planar force factor on the topology of the growing geometry during the cellular division process
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B. Curvature Analysis and Topology In this section, curvature is analysed in relation to its effect on topology, in order to achieve increased control of the morphogenetic process through division based on the curvature value of each particle. Moreover, the relationship between curvature and the various system forces is investigated, along with the effect of the cleavage selection during the cellular division process on the curvature at each particle that is being divided.
Positive Curvature
Curvature and Number of Particle Connections
As shown in the following diagrams and chart, it was found that there is a direct relationship between the two parameters, as increasing the number of connections leads to increased curvature. Moreover, zero curvature is presented in areas where there are five to seven number of connections. The observations were used as feedback in the design system for selecting points with the desired curvature to be divided based on the number of linked particles.
Zero Curvature
Curvature and Cleavage Selection Negative Curvature
As part of the first experimentations of how cleavage selection affects the topology and curvature, a first set of outputs was generated, as shown in the opposite page. It is shown that varying the distance between the two selected links to be used as cleavage selection produces outputs of varying toplogy and curvature.
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Effect of cleavage selection on curvature and topology based on the distance between the two selected links
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Curvature and Main System Forces
The relationship between curvature and the various system forces was also investigated, as shown in the following graphs and diagrams. A linear regression analysis was also made for each set of parameters in order to analyse the data quantitatively. Based on the analysis, a number of observations were made: • There is direct relationship between each force and its effect on curvature, with almost perfect fit of the generated trendline, as shown in each of the graphs. • Increased planar force and separation force reduce the total curvature with an exponential rate • Increased spring force strength increases the total curvature with a linear rate • Increased bulge force reduces curvature with a linear rate The above mentioned observations were employed as general guidelines for directing the design process based on the desired outputs and establishing optimum values between the various forces.
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Linear Regression Analysis between each force and
Relationship between curvature and
total curvature
bulge force factor
Relationship between curvature and spring
Relationship between curvature and
Relationship between curvature and planar
force strength
separation force factor
force factor
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Curvature and Stress Deformation
Analysis of the curvature in relation to stress deformation data from the developed structural analysis tool was made in order to identify any potential relationship between the two and achieve control of the generated geometry's structural performance through control of the division process based on curvature. However, as it is shown in the graphs below, there is no linear relationship between the two, as the system is highly complex and non-linear. As a result, this approach was not explored further but alternative approaches were investigated, presented in the following sections. The relationship between the number of linked particles and stress deformation was also investigated, but no linear connection was found either.
Relationship between curvature and stress deformation
Relationship between stress deformation and number of particle connections
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C. Initial Design Studies At the initial part of the research, a number of general design studies were made in order to achieve increased design control of the morphogenetic process and orient the design towards a clear direction. Some of these initial studies are presented in this section, including experimentations with different growth rates throughout the structure, varying rules for particle selection for the cellular division, different cell types throughout the structure with different behaviour and division rules, and the use of directional forces to direct the growth of the structures in space. At this stage, the particles to be divided were selected randomly.
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Initial experimentations with the cellular division algorithm using different parameter values, attraction forces, particle selection rules and division rates 75
Design Study 1: Attraction forces and multiple cell types In experimenting with the possibilities of the design system, some general designs were produced that combined the effect of attraction forces on each particle of the geometry, combined with different cell types with varying properties assigned to different groups of particles. Some of this research is shown below and on the opposite page.
Design study of different cell types within the same structure, generating heterogeneous outputs through varying growth rates 76
General design experimentations with two cell types with different growth rates and parameter values for the system forces, combined with directional attraction forces acting as bottom-up rules 77
Design Study 2: Cellular Division and Directional Attraction Forces Another study looked into the effect of attraction forces for directing the growth of the structure in space. In the example presented below an open topological surface was used with a number of particles used as locked points with fixed position in space, while the rest are being subdvided while also being attracted by a vertical force at the same time and leading to a catenary structure. A signle cell type is used. The selection of the particles to be divided is based on the curvature, with particles having increased curvature being selected for
Growth process of a catenary structure from a planar topological surface used as initial geometry through cellular division and attraction forces 78
division. The cleavage selection for each selected particle to be divided is randomly selected, leading to the generation of coral-like patterns. It was found that increasing the resolution of the structure by being subdivided further, the bulging of the surface is pushed to an extreme level, leading to the generation of a 3-dimensional highly buckled structure. However, the big influence of the attraction forces on the geometry led to abandoning this approach for further investigation.
Sections and perspectives of the generated catenary structures through cellular division showing the increased bulging of the topological surface when resolution is increased 79
Design Study 3: Cellular Division and Locked Border Particles The next investigated design approach that was eventually implemented throughout the research was the use of a fixed design space, in which a simple topological surface is set as an informed topdown design decision and used as initial surface. All the points around the edges are being locked and defining the boundaries of the design space, as it was found that this approach had the most potential in terms of pattern formations and the diversity of the generated outputs. Drawing also inspiration from Gilles Deleuze's concept of smooth and striated space [Deleuze, Guattari, 2004], the developed design system presents the interaction between these two qualities and leads to the generation of heterogeneous formations. The various states and conditions between smooth and striated were described in
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the theoretical framework chapter under the section of Heterogeneity and Performance. Following Deleuze's observations, these states and conditions can also be found in the generated cellular division design system with the fixed design space, as the process begins with a top-down or striated quality, namely the initial geometry, which gives rise to the appearance of smooth qualities through it once the simulation process starts. Moreover, the two qualities start to reappear the one inside the other as patterns and formations beging emerging, and the system remains in a constant influx state. Below: Simulation process of the fixed design space approach in which the border particles are locked and define the boundaries of the design space
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D. Design Control of Particle Selection and Division Rate In achieving increased control of the morphogenetic process, it was found out that another important area of investigation was the way in which particles are being selected to be divided and the rate of their division. The initial results showed that selecting random particles to be divided led to outputs that were too homogeneous and generated coral-like patterns. Due to this, the particle selection was controlled through the generation of a 'nutrient' level for each particle, causing the particle to be divided once it exceeds a defined value, similar to Andy Lomas' approach in his project 'Cellular Form' [Lomas, 2014]. Based on this, research was made on the definition of different rules that govern which particles are selected for cellular division and on the effect of the division rate on the generated outputs.
Effect of the particle selection on the topology
The cellular division algorithm was combined with the developed analysis tools in order to generate a number of rules that govern the particles to be selected for division. More specifically, for each set of linked particles, the particle that presents the lowest or highest curvature or stress value increases its nutrient value based on a predefined value, until it reaches the nutrient threshold and be divided. The morphological variety of this approach is presented in the diagrams nearby. The first set of outputs were generated based on one single condition, (eg. particles with maximum stress), while the second investigation looked into combinations of more Diagram of the effect of each rule for particle selection on the morphogenetic process and on the generated outputs 82
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than one conditions, such as the particles with minimum stress and the particles with maximum curvature, while also varying the weight of each rule, as shown in the previous diagram (eg. 1:2, meaning that the second parameter has double weight, hence double nutrient generation rate). Based on the outputs, the following observations were made: • Maximum stress leads to the formation of elongated areas, resembling veins and structural ribs in plants. • Minimum and maximum curvature and minimum stress generate highly bulged areas with increased number of foldings. • Combining rules and varying the weight of each rule leads to more interesting outputs that generate a combination between foldings, ribs and branching formations.
Effect of the division rate on the topology
The effect on the topology of the nutrient generation rate, directly affecting the division rate, was further investigated and results are shown in the following diagrams. A number of observations were made: • Very high nutrient generation rates leads to more 'messy' and amorphous outputs, as the particles keep being divided before reaching a nearly equilibrium state through the interaction with their neighbour particles and the interaction between the various forces. • When combining nutrient generation rules, the most interesting outputs are found in areas with similar generation rates between the rules • Except from cases of very high nutrient generation rate or big difference between the nutrient generation rates of different rules, the division rate does not have any significant effect on the topology.
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Pattern diagram of nutrient generation rate of 0.02
Fixed nutrient generation rate of 0.04 for minimum
for minimum stress particles and varying nutrient
stress particles and varying nutrient generation
generation rate for maximum curvature particles
rate for maximum curvature particles
Fixed nutrient generation rate of 0.02 for maximum
Fixed nutrient generation rate of 0.04 for maximum
Fixed nutrient generation rate of 0.50 for maximum
stress particles and varying nutrient generation
stress particles and varying nutrient generation
stress particles and varying nutrient generation
rate for minimum curvature particles
rate for minimum curvature particles
rate for minimum curvature particles 85
E. Design Control of Cleavage Selection The final and most important parameter that it was found out to affect the generated outputs and direct the generated pattern formations is the rules governing the cleavage selection of each particle selected to be divided. The rules regulate which two particles are being selected as start and end of the cleavage selection, between which all links are removed, the new particle is being generated and new links are being formed, as described in the main cellular division algorithm section. The various topologic properties of the system were used again, and it was found that they were sufficient for producing a wide variety of outputs. More specifically, for each of the two links for the cleavage selection there are rules that go through all the linked particles of a chosen particle for division and select the one with the minimum or maximum curvature, stress, or proximity to the x,y,z axis. The outputs based on this approach can produce a variety of conditions such as fluidity, branching, structural ribs and veins, strong directionality in relation to each axis, and in-between states and emergent outputs, while this area is presented in more detail in the next chapter.
Generated rules for making the selection of the two links for cleavage selection for each particle selected to be divided
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F. System Summary Summarising the various elements of the system, the diagram in this section shows the various steps that have to be followed in order to set that developed design system. An initial geometry has to be set as a topdown design decision, although the effect of the initial topology on directing the division process and the generated outputs have to be taken into consideration. The position of the geometry in relation to x,y,z axis, the various curves across its surface, and the way of triangulating the mesh, selecting among Delaunay and regular grid triangulation, are all parameters that affect the outputs. As a next step, the perimeter particles have to be locked in defining the boundaries of the design space, and followed by setting the values for the various parameters for the system forces. Finally, the rules for particle selection for division along with the nutrient generation rate have to be set, followed by the cleavage selection rules.
Diagram showing an overview of the developed system with the various steaps that have to be set for running the simulation
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Chapter VI Design Search and Pattern Classification
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In this chapter, based on the conclusions of the previous section, the developed design system is used for exploring the possibilities of the morphogenetic design space and generating a wide variety of outputs. Design search is combined with design evolution through supervised machinelearning techniques, in order to move beyond the simplified approach of user-driven trial and error exploration, and generate formations of unseen aesthetics through an informed and more automated evolutionary design process. As it was described in the previous chapter, one of the most important parameters affecting the generated outputs and their morphogenetic variety is the cleavage selection for each particle selected to be divided. Because of this, the two links selected for cleavage selection are used as the main investigated parameter, while the other parameters of the system have fixed values which were found to produce interesting outputs, while retaining the morphogenetic versatility of the design system. The chapter is organised in two sections, with the first one looking at a finite number of cases in which a single rule is used for each of the two links to be selected for cleavage selection throughout each simulation. On the other hand, the second section looks into combination of rules in one simulation, the use of probability distributions for informing these rules, and employment of supervised machine-learning and evolutionary techniques, combined with some initial explorations on artificial intelligenece and design.
Design output generated through an evolutionary design search process // Probability distribution: Link A // 17% dir X min, 14% dir Y min, 5% dir Z min, 17% dir X max, 15% dir Y max, 16% dirZ max, 4% minStress, 10% maxStress, 2% minCrv, 2% maxCrv Link B // 45% dir Y min, 55% dir Y max 91
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A. Design Search through Discrete Cases The first set of simulations focusing on design search based on cleavage selection looked into the effect of the various rules for cleavage selection on the design outputs. A simple low polygon open surface with Delaunay triangulation was used as an initial geometry. The overall orientation of the surface is parallel to the x-axis, while a small overall curve produced variation on the topology at the various parts of the struture in relation to the y-axis, as shown in the diagram below. The various rules that were presented in the previous chapter, in which the link that is being chosen for cleavage selection is based on the minimum or maximum curvature, stress or directionality in relation to the x,y,z-axis, were used as the main parameter for investigation. In each simulation, a single rule for every particle was selected, such as maximum curvature for the first link and minimum stress for the second link, rendering the cases as discrete.
Based on this approach, all of the possible combinations between the two parameters were simulated, as shown in the diagram below, and they were organised on different categories based on their morphological similarities and pattern formations, as presented in the following pages. The various outputs are related to fluidity, branching, horizontal, vertical or diagonal directionality, patches and foldings, emergent outputs and in-between states among different categories. As a next step, the outputs with increased potential were investigated further by running again a number of simulations and reaching outputs of much higher resolution, in order to reveal any potentially novel aesthetic qualities and formations, with the most interesting outputs presented throughout this section.
Initial geometry and its orientation in relation the x,y,z -axis (left) // Investigated rules for the two links selected for cleavage selection, in which all the possible combinations between the two sets of parameters were simulated (right) 93
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Some of the most representative and interesting outputs that were generated were simulated again in much higher resolution and are presented in the following pages, along with the cleavage selection rules for each case and a short analysis of the reasons behind the generated forms on different parts of the structure. A video showing the growth process for some of the most interesting cases can be accessed by scanning the qr code at the bottom of this page.
QR code redirecting to video showing the growth process of the pattern formations presented in the following pages 105
Directional Fluidity
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Cleavage Selection Links Link A // Maximum Stress Link B // Minimum Direction X
Overall fluid outputs throughout the structure and elongated parts due to the first link being the one with maximum stress
Emergent outputs in parts where the topology is not parallel to the x-axis
Overall horizontal directionality due to the second link being the closest towards the direction of the x-axis, and the initial topology parallel to it
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Heterogeneous Directionality and Emergence
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Cleavage Selection Links Link A // Maximum direction X Link B // Maximum direction Y
Horizontal directionality in areas where the topology is closer to being parallel to the x and y-axis
Emeregent behaviour and local heterogeneity in parts where the topology is not perpendicular to the x and y-axis
Diagonal directionality in parts where the topology is closer to being parallel to x-axis and perpendicular to the y-axis
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Horizontal Directionality and Foldings
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Cleavage Selection Links Link A // Maximum Direction X Link B // Minimum Curvature
Overall horizontal directionality because the first link is the closest to the direction X, leading to more directional outputs when the geometry is parallel to the x-axis
Areas with increased foldings and bulging because of the second link being minimum curvature
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Heterogeneous Directionality and Branching
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Cleavage Selection Links Link A // Maximum Direction Y Link B // Minimum Direction Z
Branching in transition areas where the topology is in-between the state of being parallel or perpendicular to the y-axis
Diagonal directionality in areas that area closer to being parallel to y-axis and z-axis
Smoother topology in parts where the topology is perpendicular to the y-axis
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Heterogeneous Directionality and Branching
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Cleavage Selection Links Link A // Maximum direction Z Link B // Minimum direction Y
Diagonal directionality in parts where the topology is closer to being parallel to the z-axis and perpendicular to the y-axis
Diagonal directionality towards y and z-axis in parts where the topology is closer to being parallel to these two axes
Vertical directionality in parts where the topology is parallel to the z-axis and in an inbetween state in relation to the y-axis
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Vertical Directionality and Fluidity
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Cleavage Selection Links Link A // Maximum stress Link B // Maximum direction Z
Vertical directionality due to the second link being the closest to the z-axis
Fluid outputs and vein formations due to the first link being maximum stress
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Heterogeneous Directionality and Emergence
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Cleavage Selection Links Link A // Minimum direction Y Link B // Maximum direction Y
Diagonal directionality in areas where the topology is perependicular to the y-axis
Almost linear directionality in parts where the topology is closer to being parallel to the y-axis
Emergent behaviour in parts where the topology is in-between parallel and perpendicular states in relation to the y-axis
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Fluidity and Heterogeneity
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Cleavage Selection Links Link A // Maximum stress Link B // Minimum direction Y
Emergent behaviour in parts where the topology is closer to being perpendicular towards the y-axis
Fluid behaviour and vein formations due to the one link being maximum stress
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Directional Branching, Emergence // Cleavage selection links: Link A // Direction Z max, Link B // Direction Y max 155
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Directional Branching // Cleavage selection links: Link A // Direction Z max, Link B // Direction Y min 157
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Directionality and Emergence // Cleavage selection links: Link A // Direction X min, Link B // Direction Y min 159
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Fluid Directionality // Cleavage selection links: Link A // Direction X min, Link B // Maximum Stress 161
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Branching, Emergence and Fluidity // Cleavage selection links: Link A // Direction X max, Link B // Direction Y max 163
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Branching and directionality generated through probability distribution for cleavage selection rules Link A // 3% dir X min, 19% dir Y min, 19% dir Z min, 6% dir X max, 1% dir Y max, 9% dirZ max, 14% minStress, 18% maxStress, 4% minCrv, 8% maxCrv Link B // 48% dir Y min, 52% dir Y max 165
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Fluid branching generated through probability distribution for cleavage selection rules Link A // 30% dir Y min, 70% maxStress Link B // 100% dirY max 167
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B. Design Search through Probabilty Distribution As a next step, the research looked into more complex rules that consist of combination of rules for cleavage selection within each simulation. Instead of looking at discrete cases, the possible rules for each link were assigned a probability value of being selected, as shown in the diagram below. However, this approach expanded the design space to a new level of complexity, due to the very high number of possible combinations between the parameter values, and rendering eventually the user-driven systematic approach that was followed so far unsuitable. Due to this, it was deemed necessary to look into alternative approaches for exploring the possibilities of the design space, such as design evolutionary techniques and supervised machine-learning approaches. The software 'Species Explorer', developed by Andy Lomas and described in detail in his paper 'Species Explorer: An interface for artistic exploration of multi-dimensional parameter spaces' [Lomas, 2016], was used in order to assist the research and apply the above mentioned techniques on the developed design system through it. A number of evolutionary techniques, such as mutation and cross blending, and 'lazy' machine-learning methods such as fitness landscape, are integrated into the software [Lomas, 2016, p.5] and were applied onto the morphogenetic design system.
Discrete Cases // Single Rule
The conclusions from the discrete cases about the effect of the various parameters on the outputs were used as the basis in order to make informed decisions about how to control the design search at this stage and set the range of probability values for each rule. The aim of this design search and evolutionary process was to look further into the formations that were found to be the most interesting and refine the outputs, while also combining more than one categories through the probability distributions for getting potentially interesting in-between states. Moreover, experimentation was made with different combinations and a variety of conditions in order to look for novel and emergent outputs in the design space. In the following pages, an example of the design search process through the Species Explorer software is presented, along with the various generated formations that were organised under categories based on the generated patterns. This data was fed back into the software afterwards in order to 'teach' the machine, making it possible to produce the desired pattern formations automatically through a basic application of artificial intelligence in design.
Non-Discrete Cases // Probability Distribution Discrete cases through the use of a single rule for each link for cleavage selection (left) // Non-discrete cases with multiple rules having different probabilities of being selected for each link for cleavage selection during each simulation (right) 169
Custom score expressions can be set by the user, such as pattern categories Generated outputs from each population organised from the user in a score system from 0 to 10
Generated populations based on different evolutionary and machine-learning techniques
Individual output viewer along with the parameter values used in generating this output
Species Explorer software developed by Andy Lomas, used as part of this research for further design search and employing evolutionary and supervised machine-learning techniques
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Generated outputs organised in categories by the user based on the pattern formations
In looking for novel outputs, populations of random values within the specified distribution range were initially generated, in order to identify any potentially interesting areas to be explored further. At the same time, directed research was made on areas that had been found to produce interesting outputs, such as fluid and directional branching formations, and experimenting with mutation and crossblening evolutionary techniques in order to refine the outputs or achieve interesting formations that combine more than one categories. Finally, all the outputs were organised by the user into categories based on two score systems, namely ranking from 0 to 10 and based on the generated patterns, as shown in the images above and on the opposite page. The former score system was used afterwards in refining even further the outputs based on the designs that have the highest score values, while the latter one was combined with the machinelearning technique of fitness landscape, explained in more detail later in this section. Some of the generated outputs, organised in categories based on the pattern formations, are presented in the following pages. Example of the probability distribution range for each rule for a generated population of random value selection within that distribution range 171
Pattern categories and probability distribution examples
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Fluditiy and Patches
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Branching and Foldings
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Fluid Branching
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Horizontal Directionality
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Vertical Directionality
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Patches and channels
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Patches with channels and branching
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Patches and foldings
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Fluid Emergent Formations
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Fluid Outputs
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Homogeneous // Amorphous outputs
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Design through Supervised Machine-Learning Based on all the generated outputs that were first organised under categories following the two score sets mentioned earlier, new populations were generated through the fitness landscape method. The method was employed at this stage for automating further the design generation process and introducing some first notions of artificial intelligence into the design. More specifically, the software allowed the definition of custom score expressions for evaluating the existing outputs and defining the various probability distributions for each simulation. Expressions were set that combined the two score sets, namely numerical score and pattern, in order to produce outputs in which the values for the probability distribution are closer to those of the outputs with higher score and those within the range of the values that were found to produce the desired pattern, as shown in the following diagram.
Example of generating a new population of design outputs through fitness landscape based on the desired pattern formation and scores of the previously generated designs 184
Fluid Outputs generated based on the score expression "score*Pattern_values["Fluid"]
Branching Outputs generated based on the score expression "score*Pattern_values["Branching"]
Fluid Emergent Outputs generated based on the score expression "score*Pattern_values["FluidEmergent"] 185
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C. High Resolution Formations In combining the versatility of the morphogenetic system and the various conclusions made throughout its investigation with pushing the limits of the available computation power, a number of high resolution outputs are presented in this section. Some of the rules that were found to produce outputs with increased potential in the previous section were applied in this step on a different initial geometry and generated geometries with strong directionality and branching formations. Based on these results, it was observed that increasing the design resolution starts producing patterns that are repeated in different scales, similar to a fractal logic and formations in nature.
High resolution output with 4 million faces 187
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Detail from the growth process of high resolution output reaching 4 million faces 189
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Detail from the growth process of a high resolution output reaching 5 million faces 193
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High resolution output with 5 million faces 195
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Chapter VII Material and Structure
In this chapter, the research mainly focuses on concepts and experimentation of materialization methods for the design that has been generated by the developed design tool. Resolution becomes an important parameter of the strategy for transforming the design model into fabrication model for a number of fabrication methods such as additive and substractive fabrication . Geometry rationalization is then involved to adjust the design model based on fabrication constraints that might be faced to achieve the proper material resolution for the design. In this process, another algorithm such as multi agent-based is system is simply employed to optimize the fabrication model with high resolution of details. A number of geometry properties from the generated topology needs to be eliminated to meet the physical constraints due to material properties and fabrication tool setup. Based on these two main parameters the design itself has tranformed into a fabrication model without ignoring the design intention that should be achieved by the high resolution details of the physical prototype. Furthermore, a speculative study on performance exploration of the design has been also investigated by conducting an early stage research on porous structure and its relationship to the cellular division algorithm using additive manufacturing strategy. This study is then considered as a potential issue that can be developed in the future in terms of material and structural performance.
The data-scape of the initial topology as a main source of the geometry rationalization strategy 202
A. Geometry Rationalization Due to the high complexity of the generated surface from the cellular division algorithm, some sort of geometry properties are analyzed to be disadvantages in terms of fabrication and materialization process. During this step of the research, a number of geometry rationalization methods has been tested to improve the possibility of the geometry to be fabricated using both additive and substractive fabrication method by eliminating some geometry properties such as extreem angle of overhang, undercut from the topology formation and self-intersecting faces of the mesh. Hence remodelling strategies from the original topology have been done to engage some degree of fabrication constraints into the design model.
The original geometry performs some geometry properties that appears as disdvantages for fabrication
The first method of the topology re-modelling is generating a totally different mesh topology based on the size of the fabrication tools such as milling bit or printing nozzle tip. The new surface is generated on the exact and same surface coverage as the original one but perform different structure of topology. As the second step, the new surface is then projected into the the original surface to mimic the initial topology. It is noticable this method produces some disadavantages for the purpose of the design. The rought expression of the initial surface is captured by the new projected surface but the design loses a siginificant details of the topology that performs critical aspects such as directionality.
Mesh remodelling method A
The second method show more promising result then the previous one. As a principal method, this system uses the same logic of projecting new surface on the original one. The innovation that has been made is instead of generating the new different topology, this method tried to capture the initial topology by using the mesh faces which are totally exposed from the direction of the projection. It is noticable that these mesh faces do not perform any disadvantages such as self-intersection etc. These faces are then used as an initial patch for the new surface. Mesh remodelling method B 203
Original Surface Topology
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ReModelled Surface Topology
ReModelled Surface Topology
[Surface Selection Method]
[Re-Meshing Method]
Original Surface Topology
ReModelled Surface Topology [Surface Selection Method]
ReModelled Surface Topology [Re-Meshing Method]
Comparison of Different Geometry Properties
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B. Porous Structure Research Anisotropic Fibrous Formation As an investigation of porous structure in the context of digital materiality, anisotropic fibrous formation is studied as a spesific experimentation into material computation. In biology, most load bearing structures are fibre composites. They are made up of fibre elements with primarily tensile capacity, embedded in a matrix material that surrounds and supports the fibrous reinforcements, maintaining their relative positions. As a synthesis of geometrical system, fibrous geometry has an adaptive ability to transform based on its particular location and direction. This material capacity is called anisotropy. As found in some natural structures such as mollusc shell, spider webs, cocoon, etc. the formation of the fibers is basically an interwoven structure between fiber threads, creating a structural behaviour to support some presssure and tensility force. This kind of structure than translated into the formation of thermoplastic formation composing a surface condition for the design. For the initial experimentation, hermoplastic polymer is choosen as a medium resolution fabrication method due to its capacity to be easily engineered in order to meet the exact requirements of a fabrication process and are today used for a wide variety of applications. Thermoplastic is considered controlable to such rate that through accurate local temperature control free spatial extrusions become possible. The FDM process of the thermoplastic fillaments is used to emphasized the technique based on layer by layer extrusion, combined by three-dimensional fibrous weaving structure. However, this research then tried to develop a concept of an SLS-based fibrous concrete printing to achieve the same principle of structural performance. Fiber interwoven in nature 206
An early concept of a porous 3D printed concrete wall
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Material Prototype 1 The first material prototype is generated based on fibre interwoven system that can be found in nature. A density of lines crossing into each other to create a composite structure deposited from one layer into another layer and created a kind of threads volume. This first experiment is produced using conventional desktop 3D printer with generated form in grasshopper. This study is playing with different level of densities to create different material properties.
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Material Unpredictability The first study of constructing digital materiality between virtual and physical were conducted in the case of material unpredictability. Working with phase changing material, the setup of the speed of the 3D printer is directly connected into the thermoplastic material transformation itself. Gaps between space from one level into another level also created interesting emergent aesthetic of the material. This reality that occured during the fabrication has brought potential consideration for the material strategies and vice versa.
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Material Prototype 2 For the second prototype, another kind of material formation was tested using the same conventional desktop 3D printer. As specific study, a chair design was tested to generate a delaunay based layer by layer fiber interwoven structure. With controlable swarms of particles, a connections of delaunay triangulation is generated in every layer, shaping the whole mass of the chair design.
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C. End-effector design End-effector Version 1 The extruder used during the initial robotic 3D printing experiments is based on the rudimentary logic of Fused Deposition Modelling (FDM), fixed on a 6-mm thick MDF wood skeleton to support its body. The extruder is composed of the following parts (NB., from top to bottom): a Nema 17-stepper motor; a J-head 3D printer gear head; a 2cm aluminium cylinder; a metallic threaded rod; another aluminium cylinder; and a threaded Teflon rod. The Teflon rod plays a key role in insulating the upper parts of the extruder from the heat generated to prevent the material used (namely, PLA) from melting in the other parts of the extruder. Lastly, a metallic nozzle (c. 10 cm length by 3.5 cm diameter) is included to preserve the heat generated by three 12volt cartridge heating elements installed within the upper part of the nozzle. Furthermore, the nozzle contains heat sensors gauging and relaying temperature values to a motherboard that controls the desired temperature. (viz., 190C).
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NEMA 17 stepper motor
Gear Head
Aluminium disk // attachment point with the robotic arm
6mm MDF Wood Aluminium cylinder
Teflon threaded rod
Nozzle
End-effector design version 1 // components diagram
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End-effector Version 2 Due to technical challenges with the initial design, a revised version was developed where the nozzle is supported vertically in order to avoid horizontal obstruction to the desired movement range of the extruder. There were specific issues caused by the earlier extruder, including material obstruction, inaccuracies, wear and tear, skewing of the main axes, and high pressure of the melted material within the nozzle. With regard to the last matter, this had led to the Teflon threaded rod being ejected on several occasions. The revised extruder aimed at addressing these issues. The current design is illustrated in the image on the left and on the diagrams found on the opposite side and following pages, whereby one aluminium cylinder and the metallic rod have been deleted given the scope they create for material obstruction and the skewing of the main axes. Additionally, the nozzle was fixed to the supporting piece of wood with three 5M screws directly onto the nozzle for two purposes: to resist any skewing or rotation; and to stop the aluminium and Teflon pieces from becoming detached due to the material pressure. The revised design includes various intersections between the parts of the wooden skeleton in order to maintain the perpendicular angle. Furthermore, the current extruder is being supported by a 90-degree triangle attached to either side. Lastly, two fans have been installed (as per the illustration). This addition should support the smoothness of the extrusion by addressing any overheating issues.
Improved version of the developed end-effector tool 214
Exploded axonometric diagram of the improved end-effector design 215
NEMA 17 stepper motor Gear Head
Aluminium disk // attachment point with the robotic arm
40mm x 40mm cooling fan
40mm x 40mm cooling fan
6mm MDF Wood
Supporting triangles
Teflon threaded rod
Nozzle End-effector design version 2 // components diagram
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5M screws
D. Column Prototype Material Study on Design After showing a primising potential, the material system from the prototype one is applied into a larger scale fabrication concept of A column prototype to study further application of the material system. In this ystem, the initial geometry, which is the surface, that was generated by the cellular division algorithm is used as a boundary for the material assembly. Hence, instead of trying to achieve the detail of the surface condition, this concept was meant to set the initial geometry as the global goal of the material assembly system. The design then would be tranformed into an emergent tectonic of material system rather than a programmable aesthetic of the surface itself.
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Robotic Fabrication Concept of Column Prototype The column is fabricated as several parts to deal with the robot limitations 219
In the end of the experimentation, it is realized that this materialization strategy might not be suitable as a strategy to achieve a fine resolution of the surface pattern detail that has been generated by the cellular division algorithm. Lack of accuracy and details is considered as a disadvantage of this method to perform the main design purpose to generate flow of perception. However, this research has showed a valuable study about digital materiality, a limitation that can be faced during the process of transforming digital data into physical properties. A potential development in the future is to create a feedbackloop system for robotic fabrication process that works as an artificial intelligence system to adapt with real behaviour of the material in physycal world.
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E. Porous Concrete Study The second part of the material research is a speculative study for future development of the material system based on the celluar division algorithm. The main purpose of this study is to create a fibrous material assembly that is suitable for an SLS based concrete 3D Printing method. It is noticable that by analyzing the growth and the topology of the surface during the cellular division algorithm, there is the potential to take advantage of this process to generate fibrous formations to support the internal tissue of the structure. This study shows a potential future research for programming a kind of microstructure that responds to the demand of structural performance using a generative method based on cellular division for a lightweight concrete structure. More specifically, as shown in the diagram in the opposite page, the cellular division process is combined with fibre generation, in which areas that are being subdivided further generate more fibres. In this case, the division process could be controlled from external inputs or based on FEA tools, so that areas with increased needs for structural support are being subdivided further, hence they have increased fibre density.
Wireframe display of the developed heterogeneous porous structure 222
Diagram of the generation of porous structure as part of the morphogenetic design process 223
Internal Layer // Heterogeneous porous structure
External Layer // Solid surface with clear pattern formations
Section of a design output with heterogeneous porous structure relating directly to the morphogenetic division process 224
In addition to the fibre generation method described in the previous page, another step was implemented in which the generated fibres are being subtracted from the solid volume of the initial wall, leading to the creation of a porous structure, shown in the diagram on this page. It is argued that such an approach could have future applications in lightweight concrete structures which could lead to material economy and the creation of heterogeneous structure that is based on performative inputs, such as structural or thermal perfromance. Moreover, this approach could bridge the gap between form-finding and performance, as the structure is the result of the morphogenetic process through cellular division, while the latter is controlled through performative requirements for each investigated case.
Detail of the generated heterogeneous porous concrete structure 225
Zoomed area of the heterogeneous porous structure 226
Parts of the generated structure with varying density based on the morphogenetic division process 227
F. Exhibition Wall Prototype For the final exhibition, a 4-meter long wall prototype was fabricated using a substractive CNC Milling fabrication method. This method is choosen due to its capacity to produce a fine high resolution details of the surface. This property becomes the main parameter of the exhibition wall to perform the concept of perception of the pattern. However the initial geometry itself does not fit into the material and toolpath constraint for the milling strategy. The developed design tool with cellular alogorithm does not allow to have flat surface as the initial geometry. in the end, and agent based system was employed to scan the curvature of the initial topology and morph it into the new design space that has been adjusted to the material and tool limitation.
Multi agent-based system was employed to transform the pattern from a doublecurved surface based geometry into flat panel space with material size and tool constraints without losing the details of the topology 230
The initial position of the agent were generated by analyzing the peak point of the surface topology. Peak point is considered as a point that all of its neighbour points have negative value. The agent then move by randomly picking one neighbour point as its new location. Once a point is picked the agent will calculate the highest absolute value of its neighbourpoints to get the furthest neighbourpoint according to its normal. This furthest point then works as the anchor point of the adjusment system and the dot product works as the ratio of the adjusment. It is noticeable that this strategy has a better result rather than directly scaling the initial model into the desired model size based on the material and tool limitation. In this case, the initial surface was adjusted into a panel with 60 mm thickness due to the limitation of the milling bit size to achieve fine resolution of details.
Agent based simulation for topology morphing 231
Different setup of milling toolpaths and milling bit were tested to check different result of resolution and time consumption. The final resul then being fabricated by using BN-12 tool with two steps of toolpath. The first step is removing material horizontally linear to the span of the panel. The second step is to follow the surface curvatire by generating the isocurves of the surface geodesic distance to achieve higgher resolution of the pattern details.
Application of milling toolpath on the adjusted surface. Some tool strategy were experimented to check the resolution and the time consumption. 232
Comparison between the rationalized model, initial model and scaled initial model
Result of the milled prototype using the rationalization 233
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The initial position of the agent were generated by analyzing the peak point of the surface topology. Peak point is considered as a point that all of its neighbour points have negative value. The agent then move by randomly picking one neighbour point as its new location. Once a point is picked the agent will calculate the highest absolute value of its neighbourpoints to get the furthest neighbourpoint according to its normal. This furthest point then works as the to the of the material anchor Due point of limitation the adjusment system stock and theproduct machine working space, and the dot works as the ratiothe of whole wall installation should bethat divided the adjusment. It is noticeable this into 8 pieces 500mmresult x 2000mm strategy has aof better ratherpanel than with 100mm However, directly scalingthickness. the initial model into the pattern milled into 60mm due desired only model size based on thedepth material to limitation of the milling bit size to andthe tool limitation. achieve fine resolution of details.
Assembly Logic of the Wall Installation 235
Fabrication Steps of a cnc-milled panel
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Chapter VIII References
Text References • DARWIN, C., 1998. The Origin of Species. Hertfordshire: Wordsworth Editions • DELANDA, M., 2015. The New Materialism. Architectural Design Magazine, Volume 85. London: John Wiley & Sons Ltd. • DELEUZE G., GUATTARI F., 2004. The Smooth and the Striated. A Thousand Plateaus. London: Continuum • FUTUYMA, D., 2009. Natural Selection and Adaptation. Evolution. UK: Sinauer Associates, Inc., 279-301 • GUILLAUME, L., FLORENT D., ATTILA, B., 2004. Constant Curvature Region Decomposition of 3D-Meshes by a Mixed Approach Vertex-Triangle. Journal of WSCG, Vol.12(1-3), 245-252 • HIGHT, C., HENSEL M., MENGES, A., 2009. En route: Towards a Discourse on Heterogeneous Space beyond Modernist Space-Time and PostModernist Social Geography. Space Reader: Heterogeneous Space In Architecture. UK: John Wiley and Sons • HOFSTADTER, D., 1979. Prelude… Ant Fugue. Gödel, Escher, Bach: An Eternal Golden Braid. New York, USA: Basic Books • HOLLAND, J., 1995. Hidden Order: How Adaptation Builds Complexity. Cambridge: Perseus Books • KAUFFMAN, S., 1995. At Home in the Universe: The Search for Laws of Self-Organization and Complexity. Oxford, UK: Oxford University Press • KWINTER, S., 1996. Soft System. Culture Lab ed. Brian Boigon. Princeton: Princeton Architecture Press • LEACH, N., 2009. Digital Morphogenesis. AD Theoretical Meltdown. UK: John Wiley • LOMAS, A., 2016. Species Explorer: An interface for artistic exploration of multi-dimensional parameter spaces. EVA London 2016, 12-14 July 2016. BCS, :London UK, 95-102 • LOMAS, A., 2014. Cellular Forms: An artistic exploration of Morphogenesis. Available from: http://www.andylomas.com/extra/andylomas_paper_ cellular_forms_aisb50.pdf [Accessed December 2015] • MASSUMI, B., 2002. Strange Horizon: Buildings, Biograms and the Body Topologic. Parables for the Virtual: Movement, Affect, Sensation. US: Duke University Press, 177-207 • MAZZOLENI, I., 2013. Architecture Follows Nature: Biomimetic Principles for Innovative Design. New York, USA: CRC Press • MENGES, A., 2012. Biomimetic design processes in architecture: morphogenetic and evolutionary computational design. Bioinspiration & Biomimetics, Vol.7(1) • MENGES, A., 2007. Computational Morphogenesis: Integral Form Generation and Materialization Processes. ASCAAD 2007. Alexandria, Egypt, 725744 • PASK, G. (1969). ‘The Cybernetic Relevance of Architecture’, In Menges, A. & Ahlquist, S. [Eds.] (2011). Computational Design Thinking, AD Reader, London: Jon Wiley & Sons Ltd., pp. 68-77 • TURING, A., 1952. The Chemical Basis of Morphogenesis. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences. London, UK. 237(641), 37-72 • VARRENE, F. (2013). ’The Nature of Computational Things: Models and Simulations in Design and Architecture’, in Brayer, M.A & Migayrou, F. [Eds.]. Naturalizing Architecture, Archilab 2013, Orleans: HYX, pp. 96-105 • WADE, D., 2007. LI - Dynamic Form in Nature. UK: Wooden Books • WILLMANN, J. , GRAMAZIO, F., KOHLER, M., LANGENBERG, S., 2011. Digital by Material: Envisioning an extended performative materiality in the digital age of architecture. Ro-botic Fabrication in Architecture, Art and Design 2011. Switzerland: Springer Interna-tional Publishing
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Image References • p.24, Fig.1 - Richard Serra, Available online: http://www.micro-studio.org/wp-content/uploads/2012/06/SERRA_2011_Cycle2-500x385.jpg [Accessed: 01/09/16] • p.24, Fig.2 - Richard Serra, Available online: http://cdn.artobserved.com/2013/11/Richard-Serra-Inside-Out-2013-%C2%A9-Richard-Serra.Courtesy-Gagosian-Gallery.-Photograph-by-Lorenz-Kienzle.jpg [Accessed: 01/09/16] • p.24, Fig.3 - Richard Serra, Available online: http://www.moma.org/interactives/exhibitions/2007/serra/imgs/Sequence.jpg [Accessed: 01/09/16] • p.24, Fig.4 - Richard Serra, Available online: http://www.brooklynrail.org/article_image/image/6243/hullot-kentor3-web.jpg [Accessed: 01/09/16] •p.24, Fig.5 - Richard Serra, Available online: http://www.phaidon.com/resource/8983c6110ec63d4bbffcab2d6a7a0bee.jpg [Accessed: 01/09/16] • p.24, Fig.6 - Richard Serra, Available online: http://static.guim.co.uk/sys-images/Guardian/Pix/pictures/2008/10/03/serra10e.jpg [Accessed: 01/09/16] • p.24, Fig.7 - Richard Serra, Available online: https://images.patternity.org/Patternity_Double-Ellipsis_Richard-Serra-1998.jpg [Accessed: 01/09/16] • p.24, Fig.8 - Richard Serra, Available online: http://www.archidose.org/Blog/serra2b.jpg [Accessed: 01/09/16]
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Chapter IX Appendix
A. Term 1 Chair Design Workshop // Agent System In this section, the design outputs of the term 1 chair design workshop are presented. The first set of designs concerns design experimentation through the use of agent systems. As a general design principle, a swarm of agents was used for the simulations, moving perpendicular to the ground and around an imported model of a sitted person. The movement of the agents was influenced by the imported model, being attracted or repulsed in different areas and generating the chair design around the body. The three forces of separation, cohesion and alignment, as defined by Craig Reynold, were acting upon each agent and affecting its movement in relation to its neighbor agents. Two design proposals are presented in this section, in which the parameter values of the various forces are modified leading to tighter and looser chair designs. Finally, the generated point cloud from the agents' movement was translated into 3D geometry by the generation of connections between the agents of each layer through Delaunay triangulation.
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Generated point cloud
Generated 3D geometry
Diagram of form evolution of chair proposal 1 through the agents' movement
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Generated point cloud
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Generated 3D geometry
Diagram of form evolution of chair proposal 2 through the agents' movement
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B. Term 1 Chair Design Workshop // Surface adaptation and fibre formations By experimenting with different techniques of generating a chair design that adapts around the human body, the following design system was created. In this system, a 3D scanned model of a human body is used, which is then used as input into the system in order for a set of topological surfaces connected with a spring system to adapt around it and find their position in space.
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The final output offers the ability to provide customised chair designs that can be easily generated by 3D scanning any human model and importing it into the system as a point cloud. As a second step, the generated surfaces are treated as boundaries, between which a set of fibres is generated in order to give volume to the design and translate it into a fabricated geometry.
C. Topoform Group
Leonidas Leonidou
Zuardin Akbar
Ayham Kabbani
Yuwei Jing
leonidas.leonidou.13@ucl.ac.uk
zuardin.akbar.15@ucl.ac.uk
ayham.kabbani.14@ucl.ac.uk
y.jing@ucl.ac.uk
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