Report Bartlett MArch GAD 2013

Computational design input changes the nature of architectural design UCL Orfanou Efstratia | RC8 | Daniel Widrig | David Scott MArch GAD

e_orfanou@hotmail.com

Efstratia Orfanou Postgraduate Student | Architect Engineer David Scott Report Rutor Daniel Widrig Design Tutor | RC8 July 2013 Master of Architecture, Graduate Architectural Design The Bartlett School University College London

2013 UCL

Computational input changes architectural design MArch GAD

_Contents 04 _Abstract 06 _Introduction 08 _The phenomenon of computational design 12 _Examples of computational design 18 _Impact | work in RC8 28 _Remain critical 32 _Conclusion 36 _References 40 _Figures 01 02

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Computational input changes architectural design MArch GAD

_Abstract The appearance of the newly introduced computational design methods has affected to a great extent the architectural context and consequently the architectural design. Starting as tools, computational design methods were generated to enhance architect’s skills and designs, either for representational or justification reasons. As architectural design consistently tests the boundaries of its practice, architects’ tasks are transformed, creating new demands and roles for them.

This paper is an attempt to explore the effect of computational input on architectural design and architect’s practice and to consider the principles that describe their new qualities.

Beginning with the definition of computational design and the traditional description of architectural design, and continuing with the presentation of related projects, this thesis highlights the way computational design is changing the field of design in architecture. In conclusion, this paper will examine the new parameters that computational design introduces and how these affect the architectural design and consequently architect’s role.

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Computational input changes architectural design MArch GAD

_Introduction In an era where Computer - Aided Design (CAD) is taken for granted and hand- sketched drawings have been replaced by digital versions, computational design makes a step further attempting to change the architectural standards.

Until now, architecture has more to do with shapes and volumes, as they are formed based on the function of spaces they represent. The appearance of architectural design is more or less, a reasonable sequence of an in depth study of how the desirable object / building / space / structure would work, perform or interact within a certain environment. The site, the function and the concept play the role of a driving force, determining the final outcome. It is undoubted that aesthetics as well have their distinct place in architectural design process. Most of the times, the final appearance of an architectural design process could be easily justified by project’s needs and demands. In other words, it seems that CAD applications are a tool to represent architect’s design and thoughts, without offering any further information or data for the project.

On the other hand, computational design input offered architects the ability to design any possible form and create the most innovative images of space and architecture, deriving ideas and information from the digital tools.

Computational applications of analysis, simulation, modeling and fabrication are developed in that way so as to give feedback to the actual design. For the first time, architects could use computer facilities, not only for representing their ideas, but also informing, enhancing and upgrading their design. Sometimes, architectural design in computational context is driven from the tools’ potentials, setting the architect able to design spaces free from physical constraints. However, this ‘freedom’ is put into question when such exquisite images could not be projected into the real world.

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In order to solve this problem, architects started searching for ways and methods to argue about their design by either justifying or building them. Beginning by borrowing knowledge from other fields, architects expanded their background. It could be supported that architects act, in a way, more like directors than designers of the project.

Architects are now responsible to develop and follow carefully a step-by-step process, which will lead to a series of products: “Architectural production is increasingly subsumed within a (technical) culture of design computation and digital fabrication, founded upon the shift from analog, intuitive practices towards parametric, mathematical logic” (Perez S., 2012). Computational design is developed as a tool that facilitates that process. As a result, two aspects of architecture are emphasized: 1. the analytical approach of data related to the design and its potentials and 2. the fabrication methods of it. These two facets are not brand new, but tend to be treated as the main parts of architectural design, in this computational scene.

Within this context, computational design tools are generated so as to respond to the new approach. Simulation software programs and 3D scanning machines analyze any possible information, creating data useful for architects to organize and optimize their design. At the same time, 3D printers, Computer Numerical Control (CNC) machines and 3D software programs enable designs’ fabrication, inventing novel techniques and materials.

At this point, the nature of architectural design as it was posed until now is put into question. In order to enhance their design, architects initiate computational design, but at the end these roles may be reversed. Is computational design a tool at architects’ disposal or a new framework for defining their design? Does computational design upgrade their skills or relocate their interest to new territories?

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Computational input changes architectural design MArch GAD

_The phenomenon of computational design Ten years ago the idea of a printed house seemed like a science fiction scenario that could not be projected to reality.

In 2006, Behrokh Khoshnevis, professor at the University of Southern California, talked about 3D printing homes, using the applications of Computational Design into a larger scale.

Nowadays, the ‘Landscape House’ (fig. 01, 02) from Universe Architecture firm is running to its completion (“Landscape House”, 2013) proving that 3D printing technology has great potentials for construction industry. As a result, more and more references similar to the ‘Landscape House’ projects are being published every day, rendering the era of computational design and fabrication as the next step of architecture. However, what is computational design and which are the tools that render it as the next – if not the present – architectural movement? In this chapter, we will attempt to define the computational design and explore the ways in which this movement affects or even changes architectural design and architect’s role.

Fig. 01, Landscape House 3D printed physical model, (archello, 2013).

Fig. 02, Landscape House 3D model, (archdaily, 2013).

Computational design as the words describe, is the design that is based on computer’s digital tools and software, basically scripting and 3D modeling and is strongly connected to the “avant-garde style, parametricism” (Schumacher P., 2009). As Patrik Schumacher has put it in his article entitled Parametricism - A New Global Style for Architecture and Urban Design: “The current stage of advancement within parametricism relates as much to the continuous advancement of the attendant computational design processes as it is due to the designer’s realization of the unique formal and organizational opportunities that are afforded by these processes” (2009).

People tend to confuse computational design with Computer-Aided Design (CAD). Nevertheless, the difference between these two definitions is of great importance. CAD is 07 08

a way of transferring design’s representation from analogue to digital form by using lines, surfaces and solids when we speak about three dimensional objects, while the buildings’ form itself remains the same (Iwamoto L., 2009). On the other hand, computational design organizes the design information, enriches it by analyzing it and offers potentials of evolution to its final outcome. As Achim Menges describes it: “In summary, one can say that the transition from computer-aided to truly computational design entails a shift from (i) modeling objects to modeling processes, (ii) from designing shape to designing behavior, (iii) from defining static digital constructs to defining computing systems capable of reciprocal data exchange and feedback information” (2012).

From its origins, computational design sets architects free of limits and qualifies them with tools and ways to conceive more complicated, organic and flexible designs. New tools as simulation, analysis and variation render architects capable of dealing with more complicated problems. As long as the parameters change, the provided tools offer various solutions in order to respond to the same question.

Another asset of computational design is this of fabrication’s control. Up until the computational design’s appearance, architects used to work separately the digital information from the physical models so as to examine the performance and the constructability of their design, respectively: “… physical models for aesthetics, digital models for “system fit” (Iwamoto L., 2009). But now, as computational design tools evolve, designers are called and provided with the ability to direct the process and materials’ behavior as well as the final appearance of their design. Being more precise, we could support that architects are asked to design and plan the process that will lead into a production of various iterations and less to design the final product itself. It seems that the architectural design is considered as the design of the process.

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Computational input changes architectural design MArch GAD

For having a more rounded image of architectural design change, we have to define the nature of it before computational design input. Architects used to be both the designer and the director of the idea, but were not related to the part of the construction. Physical models cover more needs of representation and diagrammatic depiction than being the actual designed object. As Bob Sheil refers to: “…most architects do not make the things they design.

They make design information...” (2012). Physical models constitute representations of the designed project and are utilized as means to examine the relationship between volumes, scales or open – close areas. In respect to computational design, physical model work as prototypes, as part of the final project, on which qualities and properties are tested and at the end, presented. ”Originally the construction of full-scale mock-ups and prototypes had been reserved for only the most advanced projects dealing with the design of connection details and wall sections. With the focus on design and construction of full-scale prototypes and operational assemblies, this full-scale production of experiments has dramatically altered the landscape of design potentials by discovering new means of material expression through digitally based detailing” (Anzalone P. et al., 2012). Between physical and digital models there is a continuous exchange of information, which enriches the final design. Sometimes, physical models result from digital procedures, through the use of computational machines like 3D printers and robotics. Architects are strongly involved in the fabrication of design, from the process to the final construction of it. Architects are those who carefully outline fabrication’s steps, supervise them and control them so as to achieve the desirable outcome and for this part are assessed. In other words, computational design is changing the way architects are getting organized (Peters B., 2013).

As a consequence, architectural design is addressed to establish the following process and set the rules for its efficient function.

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In an attempt to conclude what mentioned above, we could say that architectural design used to be more related to the final outcome and its appearance, based on functional and spatial qualities. In computational design context, architectural design is all about establishing specific process, a sequence of steps, so as the ultimate series of products to be developed.

Another aspect of computational design that is worth to be mentioned is this of materiality. Although architects seem to be increasingly intrigued by other fields, such as biology, mathematics or even astrophysics, material and its potentials are always at the centre of their interest. Most of the projects developed within computational design context, are strongly related to materials’ behavior, qualities and performance: “ This profound shift requires that the (parametric, robotically aided) architect to renegotiate the process of making with respect to the material, economic, legal ad social implications of automated fabrication” (Perez S., 2012). We could probably say that computational design brings again into architects’ attention the aspect of materiality in a way that material defines their design. Many are the cases in which material’s performance provides with information the architectural design, either by outlining the process of fabrication or by influencing design’s appearance.

In order to understand this change and how it can alter architectural design, we will present some examples of computational design. We will attempt to identify the parameters that change through architectural process and how they influence the architectural design itself.

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Computational input changes architectural design MArch GAD

_Examples of computational design CAD software programs give the architects the opportunity to design without limitations and structural matters, thus allowing them to express their designing intentions freely.

While many software programs have developed a variety of simulation plug-ins or supporting programs, from which architects get an impression of constructing stuff, physical tests are, in many cases, the most reliable way to experiment with a material. Computational design is developed in a way so as to cover this gap between digital and physical model and include material’s qualities into design process. Even more, sometimes the materiality tends to establish the rules of a project and not just enhancing its appearance. As Neri Oxman describes it: “Forget about the way [the design] looks. Think about how it behaves� (Quirk V., 2012).

Fig. 03, ICD/ITKE Pavilion 2010,simulation tests,(achimmenges, 2010).

Fig. 04, ICD/ITKE Pavilion 2010, (achimmenges, 2010).

In this chapter, we will present three projects made based on computational design tools and facilities. The criteria for this selection include: 1. research facilitated by computational design tools, 2. process designed with computational design tools, and 3. fabrication using computational design tools.

Through describing these projects, we will try to extract the principles that redefine architectural design as the design of a process and a material driven designing procedure.

The first example of computational design presented here, took place at the University of Stuttgart, under the guidance of the Institute for Computational Design (ICD) and the Institute of Building Structures and Structural Design (ITKE), in 2010. The teams, led by Achim Menges, Simon Schleicher and Moritz Fleischmann, utilize the material characteristics and qualities of birch plywood strips (fig. 03) so as to design and construct a temporary research pavilion (fig. 04).

Although in the physical model, material form is strongly connected to external forces, in the digital model form, material qualities are considered to be separate aspects.

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The team of this project questions this approach and designs the project starting from the view that “material computes”(Menges A., 2010). The elastic bending behavior of birch plywood strips supports the structure. These strips are robotically manufactured as planar elements, and subsequently connected so that the elastically bent and tensioned regions alternate along their length. The force, which is locally stored in each bent region of the strip, and maintained by the corresponding tensioned region of the neighboring strip, greatly increases the structural capacity of the system. In order to prevent undesirable local stress concentrations as well as the adjacency of weak spots between neighboring strips, their couplings need to shift their locations along the structure, resulting in 80 different strip patterns constructed from more than 500 geometrically unique parts. The combination of both the stored energy resulting from the elastic bending during the construction process and the morphological differentiation of the joint locations enables a very lightweight system (Menges A. et al., 2011).

It is clear that in this project parametric principles are used in a way that the form of the structure is defined by the properties of the material. As Achim Menges sets it in ICD/ITKE Research Pavilion 2010 project’s description: “The research pavilion demonstrates an alternative approach to computational design: here, the computational generation of form is directly driven and informed by physical behavior and material characteristics” (2010). Completing an in depth research on how birch plywood behaves under specific conditions and using the applications of robot (fig.

05), the designers are able to outline and define every step of the followed procedure. Moreover, the research designers are interested in aspects such as efficiency, cost, time and durability of the structure and consequently of the material.

The use of computational design tools is the only way to answer to these questions. Through this project, they achieve

Fig. 05, ICD/ITKE Pavilion 2010, fabrication process, (achimmenges, 2010).

Fig. 06, ICD/ITKE Pavilion 2010 (achimmenges, 2010).

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Computational input changes architectural design MArch GAD

to prove that computational design and materialization is a feasible proposition from now on (Menges A. et al., 2011).

In conclusion, what it is derived from this project is that architectural design is all about initiating a line of actions based on material’s qualities (fig. 06).

Keeping up with the next project, we are moving to the London based firm of Foster and Partners and their project of 3D moon base (fig.07). After the European Space Agency commissioned the architectural firm, designers worked on a concept where the material drives the process. Many are the projects in which Foster and Partners take advantage of the environmental qualities, using local materials to build them.

In the case of the moon, they research how the regolith or lunar soil can function as a building matter (De Kestelier X., 2013).

Fig. 07, Foster+Partners, 3D printed structures on the moon (archdaily, 2013).

Fig. 08, Foster+Partners, 3D printed structures on the moon (archdaily, 2013).

The designed lunar base works as a shelter for hosting four people and protecting them from meteorites, high temperature fluctuations and gamma radiation. A space rocket transfers a tube-shaped module, which unfolds the base. The supporting structure of the construction is an inflatable dome that expands from the one side of this tube and then a robot-operated 3d printer erects layers of regolith so as a protective shell to be created (fig. 08). Using a pierced structure like foam, they keep shell strong enough to handle with the forces (“Foster + Partners designs 3D moon base”, 2013).

The designers try in this project to imitate nature and set up an “organism” which creates itself by taking advantage of its surrounding environment. Apart from the ability to study the moon conditions, computational design facilitates the team to simulate the environment of the moon along with the lunar soil so as to make experiments and examine the potentials of this operation. Furthermore, the fabrication facilities that a 3d printer can provide, resolve the part of 13 14

self - creation in the most effective way. The project of a lunar base seems infeasible without computational design input. From study to fabrication and design’s process, computational design tools render the architect equipped enough to complete this project. At the same time, they called to be aware of studies on various fields, such as biology, space crafting and programming so as to deliver their tasks. In other words, we realize that in this project, the design of the followed process and the experimentation with material are what define the architectural design. As Xavier De Kestelier mentions: “It has been a fascinating and unique design process, which has been driven by the possibilities inherent in the material” (2013).

The last project presented in this paper is the Silk Pavilion of MIT Media Lab, completed in 2013. Directed by Neri Oxman, this project attempts to combine the knowledge of the natural system and this of digital world, and project it into architectural context. After meticulous research on how silkworms generate cocoon by using only one silk thread (length: 1km) (fig. 09), the team directed a process similar to the natural so as to achieve a variety of different degrees of density. Using applications of CNC machine, the process started with the creation of 26 polygonal panels, covered by silk thread (fig. 10). The shape of the structure derived from an algorithm that indicates that a continuous thread passing through hooks creates different densities (fig.

12). Completing the set up of the panels, the team placed 6.500 silkworms at the dome’s bottom (fig. 13). Controlling the spatial and environmental conditions that affect the silkworms, such as natural light and heat, the team tried to define their behavior so as to achieve the desired densities along the domed structure (“Silk Pavilion”, 2013) (fig. 11).

In this project, architects started observing a natural organism and how it works and then managed to translate its principles to an architectural concept. Studying how

Fig. 09, Silk Pavilion, silkworms in action (MIT, Matter Media Lab, 2013).

Fig. 10, Silk Pavilion, fabrication process (MIT, Matter Media Lab, 2013).

Fig. 11, Silk Pavilion (MIT, Matter Media Lab, 2013).

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Computational input changes architectural design MArch GAD

Fig. 12, Silk Pavilion, network (MIT, Matter Media Lab, 2013).

silkworms generate a 3D cocoon, what environmental conditions result into specific densities and qualities, and how a predefined site can deal with these factors, architects achieved to combine a natural process with an artificial one so as to create the desirable design. Computational design tools, from data analysis and simulation applications to construction facilities and control of the overall system, rendered the project feasible. We could say that through computational design applications, architects are able to understand, control and enhance the nature’s systems and use this knowledge for their design.

In this case, as well as the formers, the material and the procedure of making are the central focus and the motivation of the project. Once again, the design, the shape, the form are evolved from materials’ qualities or the way these are edited. Material is not just an attire of a formalistic design, but a premeditated performance, which gives feedback to the form (Thomsen M. et al., 2013). Therefore, architectural design seems to be relocated from designing forms to designing procedures, while material has the leading role.

Fig. 13, Silk Pavilion, natural + artificial (MIT, Matter Media Lab, 2013).

Fig. 14, Silk Pavilion, artificial network (MIT, Matter Media Lab, 2013).

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Computational input changes architectural design MArch GAD

_Impact | work in RC8 In the era of computational design, some architects are more interested in the materialization of their design, than the form of it. As new methods and techniques are provided, the design is driven from qualities and potentials of the material itself, which on many occasions constitutes the main part of a project: “Digital fabrication has a direct consequence on the way that material is considered in design, shifting material thinking into the core of design intention” (Thomsen M. et al., 2013). Moreover, the design of the followed procedure in which material’s potentials are examined is associated with architectural design, redefining architect’s practice.

In a similar approach, Research Cluster 8, under Daniel Widrig’ s guidance brings into focus the way that traditional, low-tech practice can be combined with computational design approach and tools and establishes new methods and processes (fig. 15). With prototyping and new kind of craft in leading role, we attempt to redefine materials and properties of them, and afterwards extract information for the design (“Cluster 8: Crafting Space”, 2012).

Fig. 15, Eroded form No. 4, 3D printed plaster (danielwidrig.com, 2012).

Based on what mentioned above, I started working on a scenario in which computational design software gives the form to the design, while the fabrication of it and / or the process to achieve it is what identifies it. A repetitive appearance of aggregated elementary volumes of bisymmetric hendecahedra, was the starting point of this project so as to explore the materialization of fabric.

The materials’ qualities such as softness, inability to be self-supported and the changeability, draw the need of a framework as the most reasonable solution for developing a process. A system under tension comes up with a plethora of different versions, after following the same process.

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Moving one step further, I experimented with the idea of converting this system into an independent structure, by testing diverse procedures and materials: from resin and varnish to pva glue. As a result, a process of specific steps is established in order for a series of 3D objects made of fabric to be created.

The steps are: 1. form bricks of bisymmetric hendecaedra by stitching its faces 2. connect the bricks with each other 3. place them into cubic wooden framework and apply tension forces on them so as to shape the desirable forms 4. impregnate them using resin and finally 5. remove the final piece out of the box. This process enables architects to manufacture a plethora of various products with nonrepetitive character (fig. 17), operarting always with the same system. Computational software facilitates here the digital design of possible products. The designing freedom that a 3D program offers to architects worked as the stimulating force for using fabric as structural material. The material experimentation leads to the outline of fabrication process, which is followed by the digital optimization of the system. In other words, a dialogue is developed between digital and physical model, in which feedback is given back and forth (fig. 16).

Moving on to the second term and following the same reasoning, working this time however in a group with Bassing Stefan, Martensen Matthew and Zhong Qiuying, we zoom in the structure of fabric so as to redefine it.

Having as a goal to create lightweight but still structurally independent bricks, we investigate how different patterns and weaving techniques can facilitate this combination.

After meticulous research, we inferred that specific crossing patterns are stronger than parallel or twisted and resin works in a more efficient way when it is applied on a multilayer surface. In addition, combining this knowledge

Fig. 16, fabric_ation, from unit to system (2012).

Fig. 17, fabric_ation, final model made of fabric after special editing (2012).

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Computational input changes architectural design MArch GAD

with threads of different thickness, we modify the outcome’s qualities. The designed process of this project is described as: 1. assembling the parts of frame, 2. applying a coat of wax on the wooden frame in order to protect wood from resin, 3. weaving the component regarding the desired structural behavior, 4. impregnating the woven component, 5. removing the frame by breaking it (fig. 18). Following this procedure, we create structurally efficient bricks made of threads.

Fig. 18, ara[X]nes, fabrication process (2013).

As architects in a computational context, we planned and designed a series of steps in order to construct a variety of

Fig. 19, ara[X]nes, physical model (2013).

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different versions, utilizing computational tools. Material’s investigation provides digital applications with information regarding its properties and performance. Settling again a mutual exchange of information between digital and physical world, we attempt to create a system where one side affects the other. The project was basically focused on the materiality of threads which when combined with different weaving patterns could offer various structural operations. At the same time, computational applications visualized the image of aggregated components so as to give us an aesthetical impression of how these bricks would look and help us build specific forms and shapes (fig. 21).

Having the digital information regarding the appearance of bricks, we made multiple physical tests so as to examine the structural efficiency and afterwards we moved back into digital model so as to try different combinations of aggregation. In the end, we produced 4 bricks with different structural behaviour which when aggregated based on the digital model, they create the final piece (fig. 20). In other words, this project promotes the design of the followed process so as to produce a plethora of different outcomes based on the parameters that material sets. The material and the process are what drive the design and finally form the project’s appearance (fig.19). Therefore, architects in this project establish the system that will result in multiple iterations, making use of material’ s identity, qualities and performance.

Gaining knowledge and experience on issues like patterning, resin applications, threads and fabrics qualities, and in a team of two, (Martensen Matthew and me), we worked on how a threading system can perform as a framework for a secondary system, for the rest of the year. The questioning aspect in this project is how this structure can work appropriately into an architectural context but at the same time preserve the information already initiated. We

components brick

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fully covered _closing up the structure => providing sun / rain protection (shelter) _one continous shell

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1 more extra notches on this edge to optimize the weaving pattern

weaving info

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grid cotton 2mm

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semi covered _acting as moment of transition / connection between fully closed and mere support conditions within the structure (indo skeleton / skeleton)

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skeleton _strongest brick, assembled in strands they form the primary support structure (lattice / scaffold)

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slightly changed gaps between notches so as to optimize the final appearance

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indo skeleton _acting as moment of transition / connection between semi closed and mere support conditions within the structure (skeleton)

extra parts to achieve the internal weaving pattern

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crossing + grid cotton 2mm

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Fig. 20, ara[X]nes, 4 structural efficient bricks (2013).

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Computational input changes architectural design MArch GAD

are intrigued by the idea of establishing a system in which site acts as a part of it rather than just a background for it.

Site is considered as the first framework (system A), where outlined bisymmetric hendecaedra (system B) (fig. 24) are deformed, defining space. In order to enhance the density quality of the system, we introduce into every volume, clusters of smaller bisymmetric hendecaerda (system C), using this time as framework the system B. Developing the idea of a more complicated ensemble, we experiment with

Fig. 21, ara[X]nes, Digital aggregations (2013).

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various qualities: from completely open (just structure) to entirely covered parts, from vectors to surfaces and then to volumes. So we launch one more system (system D), with different materiality identity (fig. 23). After testing multiple materials such as rope, 3D printed parts, latex, or even molded plaster, we conclude with the concept of fiberglass. Fiberglass, as it consists of threads, has the ability to create surfaces and volumes, when combined with resin. As long as resin is wet, fiberglass sheet transforms into flexible parts, which can be adjusted on the volumetric forms shaped by the threading system (systems A, B and C). When resin gets dry, fiberglass behaves as hardener for the network of threads / ropes, render the piece structurally efficient.

Working digitally at the same time, we try to investigate the relationship between the systems, and the way they interact with each other, using simulation options in Maya (fig. 26, 28). Having as reference the living bridges of Meghalaya in India (fig. 22), where people knitting together roots, vines and branches so as to create “a solid latticework structure” (“How to grow your own bridge: Villagers create ‘living’ crossings by training roots across a river”, 2011), we attempt to translate this technique into a controlled but at the same time non-rational performance. Testing various thickness and lengths of ropes, threads and fiberglass, physical models contribute to the idea of different densities, giving feedback to the digital model (fig. 25). In this project, prototypes mainly serve for testing materials and their performance, hinting more or less the appearance of the structure (fig.

27, 29).

Fig. 22, Meghalaya Living Bridges, India.

concept

B. initial structure | define space

1.

C. internal threads | density iterations

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internal threads

D. fibers | resolution | structural support

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The designed process in this project concerns fabrication and concept qualities, as well. Each system supports the other regarding the structural aspect, performing or enhancing at the same time diverse grades of density. As a consequence,

initial structure

fibers

Fig. 23, Relationships between systems B, C, D, (2013).

xperimentation

concept . fabrication process

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Computational input changes architectural design MArch GAD outilined volume following the form either individual parts or clusters of them

unfolded pepakura envelope of bisymmetric hedecaedro

component made of threads ready to be installed

outilined volume following the form either Fig. 24, 0utilined volume following the form of component, (2013). individual parts or clusters of them

solid . 150mm

digital representations

we end up with a variety of conditions, from fully pierced areas to solids, from structure to volumes or from light areas to darker ones. Once again, the set up of a process and the materiality are what characterize the project, working with consistency in a computational context.

All projects described constitute steps of one research, question the nature of materials and attempt to redefine them. Through the computational design aspects, we work on planning a process in which every stage leads to the next one. It seems that the final outcome is less important than the procedure that has to be followed so as to create it. Most of the times, the main intention is to establish a course of

gradient . 150mm

solid . 50mm

component made of threads ready to be installed

gradient . 50mm

Fig. 25, Experimental board, fiberglass, (2013).

Fig. 26, Digital iterations, (2013).

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actions that will produce a variety of products. It would be supported that as architects, we design products up to an extent and then we leave the conditions we set to react with each other so as to produce the final pieces, systems or qualities.

Into this context, the gap between digital and physical model is getting more and more narrow, providing each other with information. If until this point, physical models were used as volumetric representation of forms and relationships among them, in computational design era physical models work as the middle for experimentation

Fig. 27, Physical model, (2013).

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Computational input changes architectural design MArch GAD

and prototyping. Although computational design software offers an enormous amount of freedom, the computational fabrication tools set a plethora of parameters that either divert or restrain the initial design: â€œâ€Śthrough the mechanism of skill, the builder engages with the internal forces of the material: these, in turn, provide a set of constraints that test and shape the buildingâ€? (Adamson

Fig. 28, Digital iterations, details, (2013).

Fig. 29, Physical model, details (2013).

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G., 2007). Fabrication process and material qualities become now the major part of architectural design, giving information to the project’s appearance, which used to be the main focus of architectural design.

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Computational input changes architectural design MArch GAD

_Remain critical Architecture as a field is broad and nowadays more than ever, what is considered to be an architect’s job is not that clear. Many times architects are asked to deal with complicated issues that require specialized knowledge on a field in order to be solved. On other occasions, architects want to get involved with aspects that they are not familiar with in order to enhance their design. In both cases, the architectural design seems to be evolved, while technological innovations and achievements are supporting that. As computational design is strongly related to technological evolution, it is undoubtedly considered as a parameter that affects the nature of architectural design and its potentials.

Through the examples mentioned, we have an image about the prospects that computational design can offer to the architects, but at the same time we realize the plethora of things one must be aware of so as to benefit from. As material and fabrication are the common aspect of all projects presented, it is obvious that this is where the interest of architecture is focused on now. “These advances represent an opportunity for architects to relocate themselves within the design space of the construction industry, back at the heart of the process” (Glynn R., 2011).

Regarding the examples of architecture that described in previous chapters, it is apparent that computational design input has defined and oriented these projects to a new direction. Without simulation and analysis software, neither Menges’ nor Foster and Partners’ projects would be feasible. Furthermore, if 3D printing and robotics’ applications did not exist we could not talk about the socalled “self-created” lunar home, a fact that, in confluence with simulation programs, would change the significant 27 28

part of Foster and Partners project. On top of that, we could easily imagine how different the Silk Pavilion of MIT Media Lab would be, if all these rigorous appliances and machines would not exist to observe, analyze, control and construct the project. All these projects have in common as starring parameter either the fabrication procedure or the material, or both. The design of these projects is completely driven from the material qualities or abilities, giving feedback to the form, the performance and the appearance of the project.

There is no doubt that computational design provides architects with tools not only to design complicated forms but to build them as well, something that would nowadays be otherwise inconceivable: “…implementation of which (developed hardware and software tools) informed the architectural form and led to construction of unique objects unobtainable by standard design and construction procedures” (Guzik A. , 2009). On the other hand, many people wonder if this evolution of computational design sets architects free to broaden their influence or allocate their interest to something more specialized. Architects role until computational design launch, includes the design based on function, form and appearance. Models made by architects are utilized as volumetric representations in order qualities as shape, relations and proportions to be examined. Since computational design input, architects plan and design the procedure that should be followed in order to fabricate their design and models work more as experimental objects and prototypes. In a way, architects deliver and focus on tasks that are not included in their domain of expertise. As Bob Sheil states: “Through the progressive elimination of craftsmen and skilled machine operatives, the expertise that designers relied upon to translate their work has diminished and in many respects transgressed into their own domain” (2012). It seems that

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architectural design is more appreciated for the way it is organized and lined up than its final outcome.

At this point, architects are those who decide whether computational design tools are a way to enhance their skills or a reason to shift their interest to something else.

For achieving a specific goal, architects need to make use of various tools. However, sometimes, the creation and development of these tools become the main part for them. There are not few the cases where architects build the suitable software for themselves so as to achieve the desirable design, relocate their subject from design, to set up a code, which is more or less a programmer’s task (Theodoropoulou A., 2007). What I am trying to say is that although architecture’s boundaries are pretty vague, the definition of architecture is strongly related to the design.

There are many parameters that influence design principles, from function to aesthetics and from cost to efficiency but it is at the architects’ disposal how these will be balanced.

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_Conclusion In an era where technological achievements undergo every second, architecture could not be left out of this.

Computational design, as a new movement provides architects with novel tools and potentials: “Open any publication or visit any design website and you will encounter page after page of renderings that were unimaginable before the advent of computational design tools” (CASE, 2013). From software programs to building machines, computational design portrays the trend of fabrication more alive than ever. “CONSTRUCTUBILITY = COMPUTABILITY” Daniel Willis and Todd Woodward (2008) say in Diminishing Difficulty and infer that the key point of computational design is in making. The designer-maker that Bob Sheil refers to at Manufacturing the Bespoke (2012) does not even need a drawing to construct a chair. However, in computational design era the project is a dynamic system consisting of drawings, physical models, simulation analysis, animation and assembly. Every step must be precisely executed so as to have the final project. 3D printers, robotics, CNC machines, 3D scanning appliances and software support architects to represent and build every possible design. In this paper, it is questioned whether computational imput are indeed the cause of change for the nature of architectural design and if so, in what way.

Three projects of computational design are presented so as to illustrate the aspects of architectural design that are modified in this context. From systematic Menges to organic approach of Oxman, and ambitious lunar base project of Foster and Partners, we become aware of the importance that data and fabrication have for computational design.

Through a whole year of experimentation and design, in Research Cluster 8 we organized and outlined the different steps that should be followed so as to have a series of iterations. In most cases, the materialization is what drives 31 32

the design of a project, defining the potentials and its final image. Physical models take the role of prototype instead of this of design’s representation that used to be: “..the design process was intended to concentrate mainly on the construction technique rather than on material properties” (Guzik A., 2009). In other words, the architectural design is shifted from designing the final piece, to designing the process that will lead to more than one piece.

In this primary stage of computational design, architects tend to focus on the new offered aspects and applications and slightly change their tasks and role. From designing the final product, they address themselves more to design the procedure that leads to a variety of products. Most of the times, the projects of computational design are driven from the material aspects, offering feedback to the form. Architects are called to examine material’s qualities, structure, origins or systems and ultimately, plan and design the process that should be followed so as to produce multiple iterations. As a consequence, architectural design seems to be affected by computational design and converting from final piece design to the design of the process that will lead to the final piece.

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_References _Introduction 1. Perez S., “Towards an Ecology of Making”, in Borden G. and Meredith M. (eds.), Matter: Material Processes in Architectural Production, (New York: Routledge 2012), pp.

380. _The phenomenon of Computational Design 1. “Universe Architecture”, http://www.universearchitecture. com, (accessed 04 April 2013).

2. Schumacher P., “Parametricism - A New Global Style for Architecture and Urban Design”, in Leach N. and Castle H. (eds.), Digital Cities AD, (London: Wiley, 2009).

Available online at http://www.patrikschumacher.com/ Texts/Parametricism%20-%20A%20New%20Global%20 Style%20for%20Architecture%20and%20Urban%20 Design.html (accessed 29 March 2013).

3. Iwamoto L., “Digital Fabrications: Architectural and Material Techniques”, (New York: Princeton Architectural Press, 2009), pp. 5.

4. Menges A., “Biomimetic design processes in architecture: morphogenetic and evolutionary computational design”, Bioinspiration & Biomimetics, v. 7, n. 1, (2012).

Available online at http://iopscience.iop.org.libproxy.ucl. ac.uk/1748-3190/7/1/015003/ (accessed 01 April 2013).

5. Iwamoto L., “Digital Fabrications: Architectural and Material Techniques”, (New York: Princeton Architectural Press, 2009), pp. 5.

6. Sheil B., “Manufacturing the bespoke: making and prototyping architecture”, (Chichester: Wiley, 2012) pp. 8.

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7. Anzalone P. and Bayard S., “Detailing Articulation”, in Borden G. and Meredith M. (eds.), Matter: Material Processes in Architectural Production, (New York: Routledge 2012), pp.

262.

8. Peters B., “Technology and the Future Culture”, mentioned at his lecture during Smartgeometry Conference 2013 , (London, 2013).

9. Perez S., “Towards an Ecology of Making”, in Borden G. and Meredith M. (eds.), Matter: Material Processes in Architectural Production, (New York: Routledge 2012), pp.

382. _Examples of computational design 1. Quirk V., “How 3D Printing Will Change Our World (Part II)”, http://www.archdaily.com/255156/how-3d-printingwill-change-our-world-part-ii/ , (accessed 13 April 2013).

2. Menges A., “Form Generation and Materialization at the Transition from Computer-Aided Design to Computational Design”, Detail, English Edn, v. 2010, n. 4 (2010), pp.330-35.

3. Menges A., “ICD/ITKE Research Pavilion 2010”, http:// www.achimmenges.net/?p=4443, (accessed 21 April 2013).

4. Menges A., Schleicher S. and Fleischmann M., “Research Pavilion ICD/ITKE”, in Glynn R. and Sheil B. (eds.), Fabricate: making digital architecture, (Famborough: Autodesk, 2011), pp. 22-7.

5. De Kestelier X., “Press Release 31.01.2013”, http://www. fosterandpartners.com/news/foster-+-partners-workswith-european-space-agency-to-3d-print-structures-onthe-moon/ , (accessed 13 April 2013).

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6. “Foster + Partners designs 3D moon base”, http:// uk.phaidon.com/agenda/architecture/articles/2013/ february/06/foster-partners-designs-3d-moon-base/ , (accessed 13 April 2013).

7. “Silk Pavilion”, http://matter.media.mit.edu/ee.php/ environments/details/silk-pavillion, (accessed 05 June 2013).

8. Thomsen M. and Tamke M., “Digital Crafting: Performative thinking for material design”, in Peters B. and Peters T. (eds.), Inside Smartgeometry: Expanding the Architectural Possibilities of Computational Design, (United Kingdom: Wiley, 2013), pp. 245. _Impact | work in RC8 1. Thomsen M. and Tamke M., “Digital Crafting: Performative thinking for material design”, in Peters B. and Peters T. (eds.), Inside Smartgeometry: Expanding the Architectural Possibilities of Computational Design, (United Kingdom: Wiley, 2013), pp. 243.

2. “Cluster 8: Crafting Space”, http://www.bartlett. ucl.ac.uk/architecture/programmes/postgraduate/ units-and-showcases/march-architectural- design/ cluster8/2012-2013, (accessed 04 July 2013).

3. “How to grow your own bridge: Villagers create ‘living’ crossings by training roots across a river”, http://www. dailymail.co.uk/news/ar ticle-2035520/Meghalayavillagers-create-living-bridges-training-roots-river.html, (accessed 11 July 2013).

4. Adamson G., “Thinking Through Craft”, (Oxford: Berg, 2007), pp. 100 - 101.

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_Remain critical 1. Glynn R. and Sheil B., “Fabricate: making digital architecture”, (Famborough: Autodesk, 2011), pp. 20-1.

2. Guzik A., “Digital fabrication inspired design: Influence of fabrication parameters on a design process”, (University College London, unpublished Master report thesis, 2009).

3. Sheil B., “Manufacturing the bespoke: making and prototyping architecture”, (Chichester: Wiley, 2012), pp. 9.

4. Theodoropoulou A., “Architectural Authorship in Generative Design”, (University College London, unpublished Master report thesis, 2007), pp. 52. _Conclusion 1. CASE, “Mind the gap: Stories of exchange”, in Peters B. and Peters T. (eds.), Inside Smartgeometry: Expanding the Architectural Possibilities of Computational Design, (United Kingdom: Wiley, 2013), pp. 209.

2. Willis D. and Woodward T., “Diminishing Difficulty”, in Saunders S.W. (ed.), Harvard Design Magazine, (Cambridge, MA: Harvard University Press, 2008), pp. 71-83.

3. Sheil B., “Manufacturing the bespoke: making and prototyping architecture”, (Chichester: Wiley, 2012), pp. 19.

4. Guzik A., “Digital fabrication inspired design: Influence of fabrication parameters on a design process”, (University College London, unpublished Master report thesis, 2009), pp. 13.

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_Figures _Cover Figure 00, Physical model, (2013). Orfanou E. and Martensen M. (team work during the third term of MArch GAD at Bartlett, UCL). _The phenomenon of computational design Figure 01, Landscape House 3D printed physical model, (2013). Available online at http://www.archello.com/en/ project/landscape-house-0/image-8, (accessed 22 April 2013).

Figure 02, Landscape House 3D model (2013). Available online at http://www.archdaily.com/327542/contourcrafting-picks-up-speed/, (accessed 22 April 2013). _Examples of computational design Figure 03, ICD/ITKE Pavilion 2010, simulation tests, (2010). Available online at http://www.achimmenges. net/?p=4443, (accessed 20 April 2013).

Figure 04, ICD/ITKE Pavilion 2010, under construction, (2010). Available online at http://www.achimmenges. net/?p=4443, (accessed 20 April 2013).

Figure 05, ICD/ITKE Pavilion 2010, fabrication process, (2010). Available online at http://www.achimmenges. net/?p=4443, (accessed 20 April 2013).

Figure 06, ICD/ITKE Pavilion 2010, fabrication process, (2010). Available online at http://www.achimmenges. net/?p=4443, (accessed 20 April 2013).

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Figure 07, Foster+Partners, 3D printed structures on the moon (2013). Available online at http://www.archdaily. com/326429/foster-partners-to-3d-print-structures-onthe-moon/, (accessed 22 April 2013).

Figure 08, Foster+Partners, 3D printed structures on the moon (2013). Available online at http://www.archdaily. com/326429/foster-partners-to-3d-print-structures-onthe-moon/, (accessed 22 April 2013).

Figure 09, Silk Pavilion, silkworms in action, MIT, Matter Media Lab, (2013). Available online at http://matter.media.mit. edu/ee.php/environments/details/silk-pavillion, (accessed 04 July 2013).

Figure 10, Silk Pavilion, fabrication process, MIT, Matter Media Lab, (2013). Available online at http://matter.media.mit. edu/ee.php/environments/details/silk-pavillion, (accessed 04 July 2013).

Figure 11, Silk Pavilion, MIT, Matter Media Lab, (2013).

Available online at http://matter.media.mit.edu/ee.php/ environments/details/silk-pavillion, (accessed 04 July 2013).

Figure 12, Silk Pavilion, network, MIT, Matter Media Lab, (2013). Available online at http://matter.media.mit.edu/ ee.php/environments/details/silk-pavillion, (accessed 04 July 2013).

Figure 13, Silk Pavilion, natural + artificial, MIT, Matter Media Lab, (2013). Available online at http://matter.media.mit. edu/ee.php/environments/details/silk-pavillion, (accessed 04 July 2013).

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Figure 14, Silk Pavilion, artificial network, MIT, Matter Media Lab, (2013). Available online at http://matter.media.mit. edu/ee.php/environments/details/silk-pavillion, (accessed 04 July 2013). _Impact | work in RC8 Figure 15, Eroded form No. 4, 3D printed plaster, dDaniel Widrig, (2012). Available online at http://www.danielwidrig. com/index.php?page=Work&id=Eroded_Form_No_4 (accessed 09 July 2013).

Figure 16, fabric_ation, from unit to system (2012).

Orfanou E. (personal project during the 1st term of MArch GAD at Bartlett, UCL).

Figure 17, fabric_ation, final model made of fabric after special editing(2012). Orfanou E. (personal project during the 1st term of MArch GAD at Bartlett, UCL).

Figure 18, ara[X]nes, fabrication process (2013), Bassing S. , Marttensen M., Orfanou E. and Zhong Q.(team work during the second term of MArch GAD at Bartlett, UCL).

Figure 19, ara[X]nes, fabrication process (2013), Bassing S. , Marttensen M., Orfanou E. and Zhong Q.(team work during the second term of MArch GAD at Bartlett, UCL).

Figure 20, ara[X]nes, 4 structurally efficient bricks (2013), Bassing S. , Marttensen M., Orfanou E. and Zhong Q.(team work during the second term of MArch GAD at Bartlett, UCL).

Figure 21, ara[X]nes, digital aggregations (2013), Bassing S. , Marttensen M., Orfanou E. and Zhong Q.(team work during the second term of MArch GAD at Bartlett, UCL).

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Figure 22, Meghalaya Living Bridges, India. Available online at http://www.dailymail.co.uk/news/article-2035520/ Meghalaya-villagers-create-living-bridges-training-rootsriver.html (accessed 14 July 2013).

Figure 23, Relationships between systems B, C, D, (2013).

Orfanou E. and Martensen M. (team work during the third term of MArch GAD at Bartlett, UCL).

Figure 24, Outilined volume following the form of component, (2013). Orfanou E. and Martensen M. (team work during the third term of MArch GAD at Bartlett, UCL).

Figure 25, Experimental board, fiberglass, (2013). Orfanou E. and Martensen M. (team work during the third term of MArch GAD at Bartlett, UCL).

Figure 26, Digital iterations, (2013). Orfanou E. and Martensen M. (team work during the third term of MArch GAD at Bartlett, UCL).

Figure 27, Physical model, (2013). Orfanou E. and Martensen M. (team work during the third term of MArch GAD at Bartlett, UCL).

Figure 28, Digital iterations, details (2013). Orfanou E. and Martensen M. (team work during the third term of MArch GAD at Bartlett, UCL).

Figure 29, Physical model, details (2013). Orfanou E. and Martensen M. (team work during the third term of MArch GAD at Bartlett, UCL).

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_Notes

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