MASTERS IN ADVANCED DESIGN & DIGITAL ARCHITECTURE Abdulbaky Yusuf - HakimShafaei Milad
Emergent Systems
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Jordi Truco Calvet
Director:
Architect ETSAB, MArch Emergent Technologies and Design AA
Teachers:
Sylvia Felipe Architect ETSAB, MArch Emergent Technologies and Design AA
Eva Espuny Architect ETSAM,MArch ADDA Elisava,MSc Interactive Technologies and Architectural Design Research, ICD/ITKE, Stuttgart University
Lorraine D. Glover
BArch Pratt Institute School of Architecture
Marilena Christodoulou
Architect Aristotle University of Thessaloniki, Grecce. ADDA Elisava
Anna Pla
Design Degree ELISAVA, MArch Columbia University, MArch AA
Fernando Gorka de Lecea
Architect ETSAUN, ADDA Elisava
Marcel Burbina
Architect ETSAB, Master Digital Arts Pompeu Fabra
Pau de Sola Morales
Architect ETSAB, Phd Harvard Design School
Roger Paez
Architect ETSAB, GSAPP Columbia
Nuria Coll
Product Designer ELISAVA, BA in Design Univeristy of Southampton
Lectures:
Geometry and Natural Patterns
Jerome Noailly
Research in Bioengineering
Ferran Vizoso
Animal Architecture
Jordi Truco
Hypermembrane, Modular Complexity
Javier PeĂąa
Active Materials, Passive systems and Biomechanis of Materials
Mireia Ferrate
Sylvia Felipe
Cybernetics
Jalal El Ali Buro
Happold Experience
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CONTENTS Research.................................................................. 9 CASE STUDY MUSMECI BRIDGE............................................................................. 11 MORPHOGENESISM & EMERGENCE...................................................................... 17 GENETIC VS GENERATIVE...................................................................................... 23 MANUFACTURING DIVERSITY............................................................................... 33
Composite Prototypes................................................................................. 37
The Final Prototype:.................................................................................... 53
Robot Fabrication....................................................................................... 60
GRAPH THEORY.................................................................................................... 67 RESPONSIVE SYSTEMS.......................................................................................... 73
DesignProject Part 1 BIODESIGN LABORATORY.......................................... 78 MATERIAL INTELLIGENCE...................................................................................... 79 ALGORITHMIC SYSTEM......................................................................................... 97 PARAMETRIZATION.............................................................................................. 109 DIGITAL PROCESS................................................................................................. 117 RESPONSIVE ENVIRONMENTS WORKSHOP.......................................................... 129
Design Project Part 2 ABIOTIC ARCHITECTURE............................................ 140 NEW CENTRALITY - VALLCARCA............................................................................. 141
Prototype................................................................. 175
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
Research
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CASE STUDY MUSMECI BRIDGE
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
“There is no reason why the unknown factors should always be the internal stresses and not, for example, the geometric parameters which define the form itself of the structures, since in this latter case a uniformity of stresses and a much more complete and efficient use of material may be obtained. With this method, it is possible to arrive at a synthesis of new forms rich in expressive strength.” Sergio Musmeci
Form Finding Technique 1967 Using structure as an architectural form maker Sergio Musmeci used to focus on new processes of form generating techniques . His goal was to generate a minimized material structure by form. His philosophy, “The form is the unknown, not the inner stresses”, demonstrated in his form finding experiments. The shell membrane which form the lower part of the bridge would have an equi-stressed membrane, no bending stress, and a mean curvature of zero. The new form is generated from textile membranes and soap film model. It’s related to phenomena of natural systems. The design is a result of persistent methodical development in the work of Musmeci. This unprecedented form is not mimicking natural systems, it’s based more on the conversion of some structural theories to a new form.
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His first attempt was creating a membrane which contains tensile stress to convert it to a structural surface contains compression to create a 2D form of a previous bridge in Rome
After analysing the Laplace equation, the results are approximated values of minimal surfaces. Musmeci illustrated the solution by the diagram below.
During the design process of the bridge, he used physical, parametric and analytical techniques to create and test the force-modelled surface.
The first attempt was exploring the potential of a soap film (which is a minimal surface with similar surface tension in all directions within a specific set of boundary conditions) to start defining the 3D geometry of the design in order to minimize the energy under the constraints.
Musmeci noticed that the result is not curved enough and he discovered the effect of the boundary conditions which simulate the point support condition between the deck and the surface on the force-modelled surface. Then Musmeci created a second 1:100 scaled prototype with neoprene rubber of the bridge size. Unlike the soap film model, this new prototype was not an isotropic minimal surface. To achieve this curvature the pre-stresses forces in the longitudinal direction were three times larger than those in the traverse direction of the bridge.
Musmeci computed roughly the geometries that this soap film generates using the Laplace equation.
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Musmeci found that the geometries of the form-finding techniques could be interpreted into a viable bridge typology. But also the prototype had limitations for taking the project beyond the preliminary design phase. Prototypes, for form finding research, are time-consuming to construct and to alter when fast design exploration is desirable.
Musmeci built a 1:10 scale prototype of the bridge for analysis, it was a micro-concrete structure. The prototype was fabricated and tested in the Institute of Experimental Models and Structure.
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
Musmeci built and load-tested a methacrylate 1:100 scale prototype of the bridge to perform a preliminary structural analysis to evaluate the stresses after adding loads upon the bridge.
After testing the last 1:10 prototype, Musmeci was convinced that it’s time now for constructing the bridge which was a result of form finding techniques.
When the form is generated, it’s important to get the geometry definition needed for further analysis and construction, but it is a challenge because small measurement mistakes in getting the geometry from the prototype can be translated into large errors in the geometry description at the full scale and will result in undesirable bending stresses in the surface when loaded. So Musmeci choose to adopt a numerical form finding technique known as Dynamic Relaxation to obtain a precise geometry definition
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MORPHOGENESISM & EMERGENCE
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
Introduction That animals build, and indeed “design,” and that they often make optimal use of materials at hand to do so, creating massive projects of relatively impressive scale, seemed to late Victorian science a remarkable fact. That some improvised while building, overcoming obstacles to realizing their designs in what appeared to be ingenious ways, provided more of a challenge to the whole notion of instinctual behaviour, and consequently, to the too-comfortable belief that only big-brained humans were impressive improvisers. The Experience of Animal Architecture: Nineteenth Century Theories of Mind Dan Bivona
Weaver Bird The popular name for a group of birds, forming the family Ploceidm, similar to the finches. The name refers to the structure of the nests of these birds, which are woven in a wonderful manner of various vege-table substances. About 275 species of Ploceide are known, of which over 200 are found in Africa, and the remainder in tropical Asia, the Philippines and other East Indian islands, and Australia. They are small birds, with a strong conical bill, sometimes coral red. The claws are large and very long. The wings are pointed, the first quill remarkably short. There is great diversity in the form and appearance of the nests constructed by different species. One of the best-known species is the yellow weaver (Plo-.ceus philippinus), the baya (q.v.) of India. Many other weaver birds construct nests much on the same plan— pouches elongated into tubes, entered from below; some are kidney-shaped, with entrance at the side. They often suspend their nests in the same way from the extremities of branches, and prefer branches which hang over water, probably as affording security against enemies. Social habits are prevalent among them, and many nests of the same species are often found close together. Some of them at-tach one year’s nest to that of the year pre-ceding, as certain Madagascan species, which sometimes thus make five nests in succession, one hanging to another. Some of the 19
African species build their nests in company, the whole forming one structure. The social weaver birds (Philetcerus sooius) of South Africa construct in communities an umbrella-shaped roof in a tree, beneath which may be 300 bird homes. An acacia with straight, smooth stem, such as pre-daceous animals cannot climb, is often selected. The birds begin by constructing the roof (of coarse grass), each pair afterward building their own nest, formed in an excavation on the under side of the roof. As new nests are built every year, the weight of the structure often becomes so great as to break down its support.
Function of Nests For the function of nests we can mention, support for adult eggs, Mate attraction – weaver birds marsh wren, Female timuation, Thermoregulation, Inuslation, Microsite selection, Decrease Predation and Nest predators.
Nest Structure A weaver bird collects the building materials. It will cut long strips from leaves or extract the midrib from a fresh green leaf. There is a reason for its choice of fresh leaves: The veins of dry leaves would be stiff and brittle, too difficult to bend, but fresh ones make the work much easier. The weaver bird begins by tying the leaf fibers around the twig of a tree. With its foot, it holds down one end of the strip against the twig while taking the other end in its beak. To prevent the fibers from falling away, it ties them together with knots. Slowly it forms a circular shape that will become the entrance to the nest. Then it uses its beak to weave the other fibers together. During the weaving process, it must calculate the required tension, because if it’s too weak, the nest will collapse. Also it needs to be able to visualize the finished structure, since while building the walls, it must determine where the structure needs to be widened Once it finishes weaving the entrance, it proceeds to weave the walls. To do so, it hangs upside down and keeps on working from the inside of the structure. It will push one fiber under another and pull it along with its beak, until it accomplishes a stunning weaving project.
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Another member of the weaver bird family builds a solid, rainproof nest. This bird obtains the perfect mortar by gathering plant fibers from the environment and mixing them with its saliva, which gives the plant fibers both elasticity and makes them waterproof.
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
The weaver bird won’t just begin building its nest. It proceeds by calculating in advance what it needs to do next—first, collecting the most suitable building materials, then forming the entrance before going on to build the walls. It knows perfectly well where to thin or thicken the structure, and where to form a curve. Its behavior displays intelligence and skill, with no trace of inexperience. With no training, it can do two things at once holding down one end of the fiber with its feet, while guiding the other end with its beak. None of its movements is coincidental; its every action is conscious and purposeful.
Another interesting example of nest building is performed by sociable weaver birds of southern Africa, which nest in a single huge, cooperatively built structure with separate entrances. With the ingenuity of accomplished architects, sociable weavers build these nests, some of which are home to as many as 600 birds. When it comes to nest building, why does this species choose the more complex over the easier option? Can we possibly ascribe to chance the fact that they can build such complex nest structures all by themselves? Surely not like all other creatures in nature, they too act by the directives of God.
Weaver birds repeat this process until their nest is complete. It’s no doubt impossible to claim that they have acquired these skills unconsciously, by chance. These birds construct their nests like an architect, construction engineer, and site foreman all rolled into one.
Each species of bird has its own way of constructing nests. Each technique requires a design planned in advance, and is of such a complexity that couldn’t be expected from creatures without intellect or the faculty of forethought.
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GENETIC VS GENERATIVE
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
Self – Organization As a ripple of light the fish turn. Like some animate fluid, the school glides and turns again. The synchrony of motion is captivating. A similar integration of behavior can be seen in a bird flock. The volume and shape of the group change as the group turns and arcs overhead, and yet the aggregate remains cohesive. Many group-living vertebrates exhibit complex, coordinated, spatiotemporal patterns, from the motion of fish and birds, to migrating herds of social ungulates and patterns of traffic flow in human crowds. The common property of these apparently unrelated biological phenomena is that of interindividual interaction, by which individuals can influence the behavior of other group members. It is on how these interactions result in the collective behaviors of vertebrate animal groups that we focus here. Specifically, we consider systems in which insights from self-organization theory have been useful in improving our understanding of the underlying mechanics. Self-organization theory suggests that much of complex group behavior may be coordinated by relatively simple interactions among the members of the group. According to this theory, the form, and therefore often the function, of the collective structure is encoded in generative behavioral rules. Self-organization has been defined as ‘‘a process in which pattern at the global level of a system emerges solely from numerous interactions among the lower-level components of a system. Moreover, the rules specifying interactions among the system’s components are executed using only local information, without reference to the global pattern’’ (Camazine et al., 2001). It should be noted that often in nature, pattern-forming processes may not strictly conform to this classification: In some instances, such as animal migration, individuals may modify their local (self-organizing) interactions with others with reference to global information, such as a general desire to move in a certain direction. This type of system therefore self-organizes within the context of global cues. There has been expanding interest in pattern formation in biological systems (Gerhard and Kirshner, 1997; Maini and Othmer, 2000; Camazine et al., 2001). The study of pattern formation covers a wide range of areas, including attempting to explain fetal development (Keynes and Stern, 1988), patterns on the coats of mammals (Murray, 1981), the structure of social insect nests (Theraulaz and Bonabeau, 1995), and the collective swarms of bacteria (Ben-Jacob et al., 1994), army ants (Deneubourg et al., 1989), and locusts (Collett et al., 1998). In particular there is growing interest in the relationship between individual and population-level properties. A fundamental question is how large-scale patterns are generated by the actions and interactions of the individual components. Many pattern-forming processes in biological systems, such as cellular sorting or the collective 25
organization of group-living (particularly eusocial) insects, are dynamic mechanisms whereby the large-scale patterns [e.g., clustering of cell types (Glazier and Graner, 1993) or periodic activity cycles in ant colonies (Boi et al., 1999)] can be accounted for by the interactions among the individual components of the system (e.g., differential adhesion among cells; ants responding locally to the activity of others). Applying such a self-organization viewpoint to vertebrate groupings is a more recent development, and despite the importance of understanding group dynamics for ecological processes (Levin, 1999), many collective behaviors are still only qualitatively understood. Vertebrates often have superior cognitive abilities and more complex behavior patterns than organisms such as social insects. Consequently it may appear that this approach may be less able to account for the collective behaviors of these organisms. However, the self-organization approach is applicable to even the most complex of organisms, such as humans, but is restricted to certain aspects of their behavior, such as the motion of pedestrians within crowds (see Sections II.B.1 and II.C), where interactions may be (mechanistically) relatively simple. A further reason that vertebrate groups have been less well studied in this context is that for many vertebrate groups, such as 2 IAIN D. COUZIN AND JENS KRAUSE ungulate herds, pelagic fish schools, or human crowds, the interactions among the individuals are much harder to study than those in group-living insects, or bacterial swarms, where the manipulative experiments required to understand the underlying mechanisms better are easier to perform (and replicate). Here we review progress in this newly emerging area of study: that of applying self-organization theory to mobile vertebrate groups composed of many interacting individuals (such as bird flocks, ungulate herds, fish schools, and human crowds) in an attempt to improve our understanding of underlying organizational principles.
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Understanding the Dynamics of Collective Behavior Mathematical modeling is becoming increasingly recognized as an important research tool when studying collective behavior. This is because it is usually not possible to predict how the interactions among a large number of components within a system result in population-level properties. Such systems often exhibit a recursive, nonlinear relationship between the individual behavior and collective (‘‘higher order’’) properties generated by these interactions; the individual interactions create a larger scale structure, which influences the behavior of individuals, which changes the higher order structure, and so on. Consider the movement of ungulates across grassland, or over snow-covered terrain. The motion of an individual is likely to change the environment through which it moves (by compression of the grass or snow). This local change influences the motion of other individuals passing near that point: they exhibit a tendency to maximize their comfort of travel (and hence minimize energy expenditure) and thus have a greater propensity to move over the ground previously walked on. This results in further changes to the environment at that point (further compression of the substratum), which in turn increases the probability of others to choose to move over that point if close to it.
When modeling population-level processes, continuum approaches (‘‘Eulerian’’ models) have typically been used. These abstract the movement of large populations to population densities, and movement is usually represented by diffusion and advection processes. Such approximation procedures are useful, because there are well-developed mathematical tools for their analysis. Although well suited to the movement of large populations (e.g., bacterial, planktonic, and certain insect aggregations), they are less suitable for most vertebrate animal groups, which consist of a relatively small number of individuals. Furthermore, the analysis of such models is typically greatly complicated when social interactions, or interactions between individuals and their environment, are an important organizing mechanism. Consequently, here we consider primarily the motion of groups as resulting from interactions among the individual group members and use, where appropriate, individual-based (or Lagrangian) models of animal motion to elucidate certain (often generic) principles. This approach to modeling shares certain properties with techniques developed in nonlinear statistical physics to simulate the motion of particles, as for example in gases, fluids, or magnets. While particles may be subject to physical forces, animal behavior can conceptually be considered to result from individuals responding to ‘‘social forces,’’ for example, the positions and orientations of neighbors, internal motivations (e.g., degree of hunger), and external stimuli (such as the positions of obstacles). In understanding the movement decisions of animals we must better understand how and
why motivations exist, and how these translate to collective patterns.
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
Taken over a larger area, this feedback results in the generation, and use of, trail structures. Thus individuals change the local properties of their environment, which influences the motion of others, which further alters the environment, and so on. The generation of animal (including human) trails is discussed in more detail later, and the results of computer models are used to reveal the dynamics of this system.
The global level (emergent) dynamics of the group are usually not explicitly encoded: there is often no global blueprint or template for the pattern (although the formation of trails, as described, may to some degree be considered as the generation of an interactive, labile template). The form of the collective structure, and hence often the function, is usually encoded in generative behavioral rules. Such rules, being subject to natural selection, allow the generation of self-organized adaptive patterns at the group level. Because the costs and benefits to individuals when grouping may change dynamically, even as a function of the position of an individual relative to other group members, changes in individual rules are likely to occur as group members attempt to maximize their individual fitness. This can result in groups adopting different shapes, or motions, as well as being a potential driving force for internal structuring within vertebrate groups. Such properties are also discussed here. Environmental factors, such as physical habitat structure or temperature, may influence the behavior of individuals within groups, and consequently their motion and structure. These factors may affect the cohesion of groups, or act as ‘‘seeds’’ for self-organized aggregation processes. Individuals may balance global goal-oriented behavior (such as a desire to move up a temperature gradient) with local conditions, such as avoidance of isolation from a group, or alignment with group members. Such a balance of external and internal social forces may underlie the motion of certain vertebrate groups, such as migrating fish schools. The structure of the environment through which individuals move is also important. In some cases, the spatial heterogeneity in the environment may be temporally stable (relative to the timescale over which grouping mechanisms function), such as the positions of trees, rocks, and other landmarks. Such heterogeneity may influence both 27
the suitability of the environment for locomotion, and the effective range of interaction among individuals. This variability is likely to have a strong influence on both individual movement patterns and interaction range. In other cases spatial variation in habitat is dynamic, such as the flows and turbulent eddies within certain aquatic environments. A further important factor to consider when understanding the collective behaviors of animal groups (and self-organized pattern-forming processes in general) is the influence of stochastic (random) events. Animal behavior is inherently probabilistic, and stochastic properties of animal movement are likely to strongly influence the structure of many vertebrate groups. It is becoming increasingly evident that self-organized patterns often arise because of the amplification of random fluctuation (Nicolis and Prigogine, 1977; Seeley, 1995), as is discussed here when we consider the shape of migrating wildebeest herds. By developing stochastic computer models of animal groups the essential statistical mechanics of the system may be captured. The aim of modeling is often not to attempt to include all the known properties of a system, but rather to capture the essence of the biological organizing principles. One of the principal aims of self-organization theory is to find the simplest explanation for complex collective phenomena. A commonly perceived problem when modeling animal behavior, especially that of humans, is that of the representation of complex organisms through simple behavioral rules. The apparent complexity of the entities to be represented in a computer model may be misleading, however. To gain insight into the dynamics of a collective phenomenon, all of the complex details may not be necessary or even relevant. For example, much of human behavior within crowds is carried out almost automatically with little conscious decision making, and although the organism is complex, the interactions need not necessarily be so.
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Furthermore, when exploring potential grouping mechanisms it is often useful to deliberately explore a simplified representation of the system that characterizes a broader range of general mechanisms. That a biological population is described as being self-organized does not suggest that all individuals within the population are simple, identical, or have the same influence on one another. Of course, this is not to say that more specific representations of certain systems are not important. On the contrary, developing models of specific cases of a broader mechanism is extremely valuable. However, there are currently often limitations in the quality of empirical information available, and thus creating a generalized model can often be more appropriate. Also, without an understanding of the behavior of the simplest system we cannot possibly know how changes made to the model affect its behavior. Even with relatively few parameters, the exploration of parameter space can be time-consuming and complex. A further point to bear in mind is that with collective systems, understanding the behavior of an individual in isolation does not necessarily provide information about the properties of that individual within a collective situation, where nonlinear interactions may determine much of the group dynamics.
Flocking Perhaps the most visible phenomenon that brings to mind swarm intelligence is the travelling behaviour of groups (flocks, swarms, herds, etc...) of individuals that we are all familiar with. The mesmerizing behaviour of large flocks of starlings is a common morning sight over river estuaries. Swarms of billions of monarch butterflies, herds of wildebeest, schools of tuna fish, swarms of bees, all share common emergent behaviours, chiefly being:
2. Swarms change direction smoothly, as if the swarm was a single organism; 3. Unlike a single organism, yet still smoothly and cleanly, swarms sometimes pass directly through narrow obstacles (in the way that a stream of water passes around a vertical stick placed centrally in the stream’s path). In some ways, such swarm behaviour is arguably less mysterious than other emergent behaviours; it seems clear that we might be able to explain this behaviour via a built-in predisposition for individuals to stay with their colleagues, and we can readily imagine how evolution will have favoured such behaviour: There is safety in numbers. However, the devil is in the detail, and it took seminal work by Reynolds (1987) to outline and demonstrate convincing mechanisms that can explain these behaviours. Reynolds’ work was within the computer graphics community, and has had a volcanic impact there. Now known as ‘Reynold’s rules’, the recipe that achieves realistic swarm behaviour (with some, but not obtrusively much, parameter investigation needed depending on the species simulated) is this triplet of steering behaviours to be followed by each individual in a swarm: Separation: steer to avoid coming too close to others.
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
1. The individuals stay close to each other, but not too close, and there seem to be no collisions;
Alignment: steer towards the mean heading of others. Cohesion: steer towards the mean position of others To understand how realistic swarm simulation works, it is important to note that each boid has its own perceptual field – i.e. it could only ‘see’ a certain distance, and had a specific field of view (boids cannot see behind them, for example). The adjustments it makes to its velocity at any time are therefore a function of the positions and velocities of the boids in its perceptual field, rather than a function of the flock as a whole. The rules are key ingredients to a realistic appearance in simulated flocks, but there are several other details, particularly regarding obstacle avoidance and goalseeking behaviour.
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Processing software Processing is an open source computer programming language and integrated development environment (IDE) built for the electronic arts, new media art, and visual design communities with the purpose of teaching the fundamentals of computer programming in a visual context, and to serve as the foundation for electronic sketchbooks. The project was initiated in 2001 by Casey Reas and Benjamin Fry, both formerly of the Aesthetics and Computation Group at the MIT Media Lab. In 2012, they started the Processing Foundation along with Daniel Shiffman, who joined as a third project lead. One of the aims of Processing is to allow non-programmers to start computer programming aided by visual feedback. The Processing language builds on the Java language, but uses a simplified syntax and a graphics user interface.
Multi-Agent systems Algorithm The project has been developed in Processing software according to the behavior of the combination between cotton thread and latex. Combining cotton thread with latex causes self-organization according to the material properties and organization of the fibers. This self organization system forced us to use programming based software such as Processing to generate variation of shapes using mathematics. Physic libararies in processing give us an ability to apply real forces to the objects.
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Using Multi agent system according to the behavior of the threads considering cohesion and separation features of agents. Density of patterns will change the behavior. When It’s more dense agents willing to attract to each other so the result could be thicker in these parts which causes repulsion on the other parts. This how the algorithm works for the whole system. Dividing curves into points to use them as an agent which can react to each other. Each agent can react to its neighbor according to the multi agents algorithm. This is how local changes affect the whole system to create new shape. Agents could measure distances to other agents and check the conditions which we put according to the physical models and apply their forces to them. Organization of the patterns and number of layers will totally change the final result. Because it creates different number of agents with different distances which causes new shapes.
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
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MANUFACTURING DIVERSITY
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Nature has given cotton qualities that make it a smoother, softer and more comfortable choice. Cotton breathes. The quality of the cotton depends on the length of the individual fibres, or staples - the longer the staple, the better the cotton. Longer staples can be combed finer to remove more small fibres, allowing the cotton to be spun into a finer-textured thread with more tensile strength, and woven into a softer, more lustrous fabric.
Epoxy Resins The large family of epoxy resins represent some of the highest performance resins of those available at this time. Epoxies generally out-perform most other resin types in terms of mechanical properties and resistance to environmental degradation, which leads to their almost exclusive use in aircraft components. As a laminating resin their increased adhesive properties and resistance to water degradation make these resins ideal for use in applications such as boat building. Here epoxies are widely used as a primary construction material for high-performance boats or as a secondary application to sheath a hull or replace water-degraded polyester resins and gel coats. An epoxy is a resin used for bonding or coating. Most epoxies are not conductive, but some epoxies contain conductive metals, such as silver or nickel. These electrically conductive resins are used to coat or bond electrical components.
gether to give the composite unique properties. However, within the composite you can easily tell the different materials apart as they do not dissolve or blend into each other.
Natural composites Natural composites exist in both animals and plants. Wood is a composite – it is made from long cellulose fibers (a polymer) held together by a much weaker substance called lignin. Cellulose is also found in cotton, but without the lignin to bind it together it is much weaker. The two weak substances – lignin and cellulose – together form a much stronger one. The bone in your body is also a composite. It is made from a hard but brittle material called hydroxyapatite (which is mainly calcium phosphate) and a soft and flexible material called collagen (which is a protein). Collagen is also found in hair and finger nails. On its own it would not be much use in the skeleton but it can combine with hydroxyapatite to give bone the properties that are needed to support the body.
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
Cotton
Modern examples The first modern composite material was fiberglass. It is still widely used today for boat hulls, sports equipment, building panels and many car bodies. The matrix is a plastic and the reinforcement is glass that has been made into fine threads and often woven into a sort of cloth. On its own the glass is very strong but brittle and it will break
The applications for epoxy-based materials are extensive and include coatings,adhesives and composite materials such as those using carbon fiber and fiberglass reinforcements (although polyester, vinyl ester, and other thermosetting resins are also used for glass-reinforced plastic).
Composite materials A composite material is made by combining two or more materials – often ones that have very different properties. The two materials work to35
if bent sharply. The plastic matrix holds the glass fibers together and also protects them from damage by sharing out the forces acting on them.
Why use composites? The biggest advantage of modern composite materials is that they are light as well as strong. By choosing an appropriate combination of matrix and reinforcement material, a new material can be made that exactly meets the requirements of a particular application. Composites also provide design flexibility because many of them can be moulded into complex shapes. The downside is often the cost. Although the resulting product is more efficient, the raw materials are often expensive.
Digital Fabrication The continuous, highly curvilinear surfaces that feature in digital architectures brought to the front the question of how to fabricate the spatial and tectonics of such non-Euclidean forms. It was the issue of constructability that brought into question the credibility of spatial complexities introduced by the digital design.
Subtractive Manufacturing A CNC router (Or Computer Numerical Control router) is a computer-controlled cutting machine related to the hand held router used for cutting various hard materials, such as wood, composites, aluminium, steel, plastics, and foams. CNC stands for computer numerical control.
Laser Cutting Laser cutting is a technology that uses a laser to cut materials, and is typically used for industrial manufacturing applications, but is also starting to be used by schools, small businesses, and hobbyists. Laser cutting works by directing the output of a high-power laser most commonly through optics. A typical commercial laser for cutting materials would involve a motion control system to follow a CNC or G-code of the pattern to be cut onto the material. The focused laser beam is directed at the material, which then either melts, burns, vaporizes away, or is blown away by a jet of gas, leaving an edge with a high-quality surface finish. Industrial laser cutters are used to cut flat-sheet material as well as structural and piping materials.
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Additive Manufacturing 3D Printer 3D printing, also known as additive manufacturing (AM), refers to processes used to synthesize a three-dimensional object in which successive layers of material are formed under computer control to create an object. Objects can be of almost any shape or geometry and are produced from digital model data 3D model or another electronic data source such as an Additive Manufacturing File (AMF) file.
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
Composite Prototypes First we started using Latex and cotton threads to create the prototypes but the final composite is created with epoxy resin and cotton threads. The fabrication process has been developed many times.
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01- Cotton thread with Latex
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Dipping a cotton thread pattern in latex.
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The result is a self organized pattern.
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Cannot predict the shape.
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The result is different every time the same process is repeated.
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The dipping process can work with small patterns but very difficult to repeat it with large patterns. The latex is not rigid.
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Dipping a cotton thread pattern in Resin. The result is a self organized pattern.
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The curves are lost and the shape of the pattern is different from the previous pattern.
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Cannot predict the shape. The result is different every time the same process is repeated.
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The dipping process can work with small patterns but very difficult to repeat it with large patterns. The Resin is rigid but the pattern is weak and not performing.
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
02- Cotton thread with Resin.
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03- Cotton thread with Liquid Plastic. smooth Cast 300 •
Dipping a cotton thread pattern in Liquid Plastic.
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Single cotton thread and double cotton thread.
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We noticed that the behaviour of the patterns is different when the cotton thread is doubled More rigidity and less flexibility.
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The curves are lost and the shape of the pattern is different from the first pattern with latex
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Cannot predict the shape. The result is different every time the same process is repeated.
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The dipping process can work with small patterns but very difficult to repeat it with large patterns The Plastic is very rigid.
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
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04- Cotton thread with Epoxy Resin. 2 layers. •
No more dipping or self organization.
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Double cotton thread.
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An attempt to get the curves but in a way that can be predicted.
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The result is the same when the same process is repeated.
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Apply resin on the pattern after pushing the pattern into the cones.
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The pattern is still weak.
05- Cotton thread with Epoxy Resin. 4 layers. •
No more dipping or self organization.
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The pattern is still weak.
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Four layers of cotton thread.
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An attempt to get the curves but in a way that can he predicted.
The connections between the threads are weak.
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The result is the same when the same process is repeated.
The resin is not well distributed on the pattern.
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The patterns neither horizontal nor vertical.
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Apply resin on the pattern after pushing the pattern into the cones.
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
Apply the epoxy resin now
More cotton thread layers
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06- Cotton thread with Epoxy Resin. 8 layers.
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Here we tried to solve all the problems we have faced before.
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First the weaving is more vertical, we weaved one layer from top to down and the other from down to top then we repeat this process many times till we have the desired number of layers for stronger connection between layers.
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
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Then we pushed the pattern over the cones to have the final pattern
We terminated the horizontal pattern and we developed only the vertical pattern.
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
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We developed this way to make bigger patterns So again the wet cotton thread with epoxy resin is woven in tension with wooden frame in layers and we repeated the same process with bigger dimensions
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
We repeat this process several times till we have 8 layers of wet cotton threads.
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We developed here the wooden frame, here it is movable so the cotton thread layers can be shrink during pushing down as a result of the tension loads added to the cotton from the cones. When the cotton threads become dry the composite is taken off the wooden frame.
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
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The final prototype is created the same way like the last prototype but here we used nails instead of cones. We draw circles instead of the cones and arrange them the same arrangements but here we have the flexibility to have bigger sizes of the pattern because it’s based on the diameter of the circles.
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
The Final Prototype:
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We put nails around the circles so we can weave the pattern around these nails.
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
We put another nails inside and outside the circles to weave the joints which will be used for the internal patterns in order to produce the local forces later.
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Then we start weaving in several layers. The black layer first then the red layer to make sure that the whole pattern is connected together.
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
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Here we waved only one row of the pattern
We repeat this process several times till we have a pattern with 8 layers of wet cotton thread
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
When the cotton threads become dry we remove the nails from the composite
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Robot Fabrication. Using Robot to weave the pattern in workshop
Length
Width
Robot has a limit to cover different directions and distances. We can fix width of the .system and continue weaving by using rail and then join strips together Maximum width : 2.5 meters 60
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
Create flat strips based on their limit and connect them in the workshop. Bend strips and fix them with the ground on the site
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Skin of the system During our form finding research we found that we can have several skins for our system. 1- To have more density weaving and then apply latex to cover the spaces between the cotton threads.
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
2- To have an ETFE skin for both sides of weaving which the system has and here the system will have two layers of ETFE with a space in between. This idea will lead us to more research to apply pneumatics to our system in the future.
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Boundary Condition To fix the system to the ground we will use the universal joint because we found that will allow the system to bend and responds to the sun real time. A universal joint is a joint or coupling in a rigid rod that allows the rod to ‘bend’ in any direction, and
These joints will be fixed to the ground by steel which is fixed to small concrete blocks.
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is commonly used in shafts that transmit rotary motion. It consists of a pair of hinges located close together, oriented at 90° to each other, connected by a cross shaft. The universal joint is not a constant-velocity joint.
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
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GRAPH THEORY
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
Graph Theory
Graph theory is the study of points and lines. In particular, it involves the ways in which sets of points, called vertices, can be connected by lines or arcs, called edges. Graphs in this context differ from the more familiar coordinate plots that portray mathematical relations and functions. Graphs are classified according to their complexity, the number of edges allowed between any two vertices, and whether or not directions (for example, up or down) are assigned to edges. Various sets of rules result in specific properties that can be stated as theorems.
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NFL Graph Theory Here’s a directed graph of the entire NFL so far this year with the cycle I described about highlighted in think black edges. Node size is proportional to the number of team wins, and the colored groups are the divisions Direction of the Edges shows which team won that game, for Example: New England beat Tennessee; Tennessee beat Detroit; Detroit beat Philadelphia
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
The Oracle of Bacon The example in popular culture surrounds the actor Kevin Bacon. An actor is considered to be linked to another actor if the actors have appeared in the same movie. An actor’s so-called Bacon Number is the distance of the actor from Kevin Bacon
Design a table to find a relation between members of the group can simplify the complexity of the system. By using numbers (0-1) we can figure out which members have relation with each other in different rows and columns.
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RESPONSIVE SYSTEMS
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
Responsive to Adaptive “Adaptation is the evolutionary process whereby a population becomes better suited to its habitat. This process takes place over many generations, and is one of the basic phenomena of biology.� –On the Origin of Species, Charles Darwin
Our lives are surrounded by constantly changing forces of nature and environment. Everything is in a constant state of flux, with varying degrees of dynamism. Our lives too, are always in motion. The spaces we inhabit are constantly changing as well, although the change is slow and occurs through non-physical conditions. The physical state of the inhabitable spaces are more or less constant and not in motion. A traditional building skin provides stability, regulates air pressure (fenestration) and protects the interiors from direct environmental factors (sunlight, rain and wind). Building skins are a vital component to resolve the issues of responsive architecture as they are a medium through which intelligence can be imparted to the building system to respond to an environmental stimulus. Thus key characteristic of an effective intelligent building skin is its ability to modify energy flows through the building envelope by regulation, enhancement, attenuation, rejection or entrapment. 75
The term ‘adaptation’ is commonly used in architecture in relation to the changing morphologies of the architectural artifact. These changing morphologies have been a result of timely changes and evolution of architecture as a social entity, technological product and as a practice. Through years of architectural evolution, changes have occurred in notions of how buildings are conceived and built. The architectural morphologies adapt to the time, in which they are conceived and realized. These adaptive morphologies are a resultant of changing times, social form, economic support, user needs and environmental effects. The environmental changes that occur in a given time, such as a day, can be a constant force of changes that need to occur in an architectural object, leading to local adaptations. The global climatic change, occurring over a course of time, creates forces for architectural object to change over the years, in order to survive and sustain itself. Aaptation in architecture is a long-term process that occurs with time and generations, where improvements in the technology, economic support as well as human thought-process, contribute to the adaptive response.
Responsive building skin designed for MACBA, Barcelona, by rat[LAB] – Sushant Verma & Pradeep Devadass in research adaptive[skins] carried out at AA London-Em.Tech.
Adaptation occurs through generations, with constant improvements, feedback evaluations, and survival of the fittest, based on certain fitness criteria. Many projects dealing with adaptive architecture can be sub-categorized adaptation as interactive, dynamic, kinetic or responsive architecture. Relationship of Adaptive Architecture to Responsive, Dynamic and Kinetic Architecture. (rat[LAB] project adaptive[skins] carried out at AA London-Em.Tech
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
Adaptation as a process has been conceived in various disciplines with similar approach and goals. This definition offers a direct translation into architectural conceptualization. We can consider the building to be a system which adapts its behaviour to information acquired about its users. Information external to the building (system) could also be integrated into the process, for example weather data, energy prices, demands of neighbouring buildings, etc. Adaptive Architecture thus has the capability to respond to a number of parameters with time. Time is an integral factor driving adaptation in architecture. Thus adaptive architecture can be said to be Responsive Architecture evolving with time.
Evolution of Responsive Architecture to Adaptive Architecture over a period of time, through many generations. (rat[LAB] project adaptive[skins] carried out at AA London-Em.Tech.
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Design Project Part 1 BIODESIGN LABORATORY
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MATERIAL INTELLIGENCE
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
Form Finding The design process by which the shape of form-active structures and systems is determined is widely called form finding. It’s finding an optimal shape of a form-active structure that is in (or approximates) a state of static equilibrium. A material system which can generate complex systems is developed and explored through a form finding process initiated based on the capabilities of self organization of the material system and following the emergence theory in nature, which is a process whereby larger entities arise through interactions among smaller or simpler entities such that the larger entities exhibit properties the smaller/simpler entities do not exhibit. Such a system is developed in a bottom-up controlled way which is a type of information processing based on incoming data from the environment to form a perception and the form is a result of a process with many inputs. It is the piecing together of systems to give rise to more complex systems, thus making the original systems sub-systems of the emergent system. The form finding experiments started with the self organizations of a fibrous system in latex which led us later to find a new composite which can generate complex forms when changing local forces in the system. The local force is a woven pattern which is responsive to the sun. 81
Fibrous composite
We created a composite with epoxy resin and cotton thread. The composite is flexible, can be bent and twisted and the woven pattern inside the composite would control this behaviour by creating tension stress which creates a reaction in the entire system’s behaviour and form. The composite has no joints or connections, the entire system is one piece consisted of small components fabricated together with one long cotton thread. The component size is 151 mm * 264 mm 82
We have three main pattern variations which controlling the behaviour of the system.
Horizontal
vertical
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
Topological Variation
45 degree
We further experimented the system with different patterns inside the components which form the composite. we used the main three patterns and mixed also different patterns together during the experiments. We noticed that each pattern creates different tension stress on the system generating different shapes. The experiments led us to more understanding of the material properties and system capabilities.
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Pattern Variation Study Horizontal weaving
With the vertical weaving the component’s bends up in the vertical direction a and the horizontal direction bends down at the same time
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
Vertical Weaving
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45 degree weaving
With the 45 degree weaving the component bends up in the vertical direction but the pattern but one side of the component moves right or left.
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
Vertical & horizontal weaving
Here we fix V dimension of the pattern and change only the H dimension.
V = 0.7, H = 0.8 87
V = 0.7, H = 0.7
V = 0.7, H = 0.6 88
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
Here we fix H dimension of the pattern and change only the V dimension.
V = 0.8, H = 0.6 89
V = 0.7, H = 0.6
V = 0.6, H = 0.6 90
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
The geometric principles of the component: We decided to use horizontal and vertical weaving together for more control on the system.
To control the component we first weave the vertical pattern.
Then we weave the horizontal pattern
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The horizontal weaving controls the shape of the component as mentioned before, it controls the bending direction as well. The red threads are flat and the green threads are curved. The bending direction is always towards the red threads.
The green threads are up and the red is down the component:
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
The red threads are up and the green is down:
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When we started the form finding research our aim was to understand the material capabilities and to explore it’s behaviour. The research led us to understand the local forces that where generated by the tension inside the components by the different patterns of the fibers. The form emerges from the local tension generated. The morphologies which are generated by this system is based on the tensions created by the patterns inside each component and the composite behaviour. The form is inherently linked to the patterns which is the clue of the existence of an emergent morphogenetic strategy.
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
Component Definition
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ALGORITHMIC SYSTEM
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Geometrical Principles Of The Component Horizontal pattern
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
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45 degrees pattern
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
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PARAMETRIZATION
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
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DIGITAL PROCESS
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According to our experiments about fibrous systems(Cotton threads – Eposy resin with Cones) we have to create an algorithm which can push threads where we have cone based on the size of them. Attaraction and repulsion in different parts of the pattern cause different shapes. We need to make an algorithm that can change the first pattern to the new one, according to the forces inside.
Processing We started working with Processing software to create an algorithm compatible with our system. The code which we used can understand the cones as some forces and apply them to the straight lines and shape it by using attraction and repulsion functions.
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
Digital Process
Divide straight curves into particles to be able to apply forces and change the shape of the pattern according to the physical models.
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Images below show the affection of the attraction and repulsion forces on the primitive patterns. We tried to test forces on different positions with different sizes.
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
Grasshopper After doing research on the behavior of the patterns based on the forces in processing software, We started figuring out the parameters which could help us to proliferate the system. The system has been proliferated in two directions. By reapting the cells, size of the cells could also change. In order to achieve this behavior we started working with Grasshopper.
The image shows the brief process of creating the pattern which we followed to design the definition in grasshopper.
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According to the definition of the grasshopper, we are able to change the size of the circles (Cones in the physical model) to change the size of the cells. Number of cells can also be changed to have more patterns in both directions.
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
The Grasshopper definition allows us to create different kind of patterns with different size of cells. The image bellow shows some of the variations which we can have based on the different parameters of the system.
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Python Script In order to apply another layer inside each cell to know the behavior of the system by having different type of weaving patterns inside, we preferred to start study each cell separately by adding new layer. To have more control on every parts of the pattern with different type of weavings, we used Python script in Grasshopper. Python gives us an ability to control the behavior of the cells based on the real physical model.
Apply different conditions on each pattern by using Python script will lead us to have a smart cell which can change the bahvior of itself according to the different weaving pattern inside.
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
We designed the grasshopper definition to be able to change the cell’s size and length by changing the length of the patterns inside. In order to understand the behavior and also follow the way of proliferation we started creating more than one cell and apply weavings to check the behavior of the system in different scales.
Using Artificial Intelligence in our code, helped us to test different conditions on more cells at the same time to check different morphologies. The code designed in the way that can adopt itself with different variations and show the result based on the real physical models.
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According to our experiments and tests with physical models, we found based on the length and the type of weaving inside each cell we can have different behaviors. We designed variations for each conditions to see the possibility of the morphologies based on the local changes o every parts and how they affect on the whole system. These images show how different variations in the code creates different morphologies in the whole system.
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
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RESPONSIVE ENVIRONMENTS WORKSHOP
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Responsive architecture aims to refine and extend the discipline of architecture by improving the energy performance of buildings with responsive technologies (sensors / control systems / actuators) while also producing buildings that reflect the technological and cultural conditions of our time. A real time communication between the digital system and the physical actuators is needed to create a responsive physical system, we use Arduino software to establish the communication between these systems.
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
RESPONSIVE SYSTEM
Responsive architecture measures actual environmental conditions via sensors to enable buildings to adapt their form, shape, colour or character responsively via actuators. Responsive architectures distinguish themselves from other forms of interactive design by incorporating intelligent and responsive technologies into the core elements of a building’s fabric. The term adaptation is used in biology in relation to how living beings adapt to their environments, but with two different meanings. First, the continuous adaptation of an organism to its environment, so as to maintain itself in a viable state, through sensory feedback mechanisms. Second, the development (through evolutionary steps) of an adaptation (an anatomic structure, physiological process or behaviour characteristic) that increases the probability of an organism reproducing itself (although sometimes not directly). Some artificial systems can be adaptive as well; for instance, robots employ control systems that utilize feedback loops to sense new conditions in their environment and adapt accordingly. 131
Our system responds to the sun. The components shrink or expand based on the amount of sunlight received by the sensors connected to them to allow only day light inside the building and prevent high radiations from entering the space inside. First we use ladybug for the sun analysis. The colour differentiation of the analysis controls the shape of the components.
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Position 1 is the minimum sunlight received.
Position 2 is the maximum sunlight received.
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
Position 01 Position 02
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Also the system has to respond also to the direction of the sun in order to control the temperature and light in the space inside.
So the components change their direction - Up or down - to tilt according to the sun.
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Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
The system can will respond to the location of the sun and will generate different forms depending on the location of the sun
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So now we know how our system controls the sun but in order to generate a responsive system we followed the following process:
• First we have to collect data from the environment using light sensor: 29875 LDR – 10K
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• Now we have grasshopper algorithm ready and Arduino code ready so we need firefly to connect both together in order to achieve a response. Firefly
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Firefly and grasshopper
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Firefly reads the information from the Arduino programming.
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The light sensors receives data every 10 seconds as programmed.
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Then we remap this data to values between 0 and 1, to be used as a multiplication factors to the operative parameters in the grasshopper algorithm.
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As the light sensor changing the operative parameters will change.
We will use ladybug environmental plugin for sun analysis to know the most efficient form which allows the minimum heat inside the space and the desired day light and we will use it.
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Design Project Part 2 ABIOTIC ARCHITECTURE
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NEW CENTRALITY - VALLCARCA
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Vallcarca i els Penitents is a neighbourhood in the northernmost part of Gràcia, a district of Barcelona. Locked between two hills, Putget and El Coll, it grew out of a few scattered settlements, namely L’Hostal de la Farigola, Can Falcó, Can Mas and Can Gomis. Vallcarca didn’t get the proper care, Barcelona progressed but vallcarca became an isolated area. Most of the inhabitants moved to other districts in Barcelona and many shops disappeared. The district became like a summer district where people come only wo or three weeks every year for nice breeze. The district lack a city centre, where commerce, entertainment, shopping and political power are concentrated.
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
VALLCARCA
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Vallcarca 1897
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After the form finding research we have noticed that that our system can easily work with different levels & contours and ALSO can control the sun light.
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
OPERATIVE CARTOGRAPHY
So we had to analyze these factors in order to find the main areas with proper contours and proper environmental conditions for our system. First we defined the available areas, then we categorized these areas based on the contours.
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Spaces of Opportunity for the Development of a Microcentrality
Our system works well with contours, so we will work with the following topography - Top priority:
We can work with this topography but not our priority:
We excluded the following topography:
Our system controls the sun, in the new centrality we need spaces with sun in winter and also we can control the sun in summer to afford pleasant spaces. So we excluded the spaces which don’t have enough sunlight.
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SYSTEM SITE CONTEXTUALIZATION
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System adaptation The system is working with levels to cover and connect different heights
Connecting different heights
No obstacle to close the view Ability to carry loads.people,plant
Java Code
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//Limitation for Distance = (3.5,20)
} else if((x>20 h>10.5)){
//Limitation for Height = (3.5,10.5)
if(x>20)
//Different Conditions if (x < 20 &&h <= 10.5 &&x< h*4){
{ println(“Distance is more than it’s Range”);
println(“We need only one layer”);
}if(h>10.5)
} else if (x < 20 && h <= 10.5 &&x >= h*4 &&x <=h*6)
{ println(“Height is more than it’s Ranget”); }
{ println(“Please Add another layer”);
println(“Please Start new System”); 1
Distance
Ratio between height and distance is more than its limit
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
Height
Add extra layer to support the whole system
Add layers on every level
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System site contextualization
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Lines
Divide by length
Contour lines
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If distance > Limit Jump to the adjacent point
Connect points
Jump to the adjacent point when the limit is reached
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
Connect points with line
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The very hot zones are excluded Change the width of the system in a very hot zones to have smaller spaces
View Analysis
Excellent view Good view No view
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Sun Analysis
Project: Fibers Adaptability // Master in Advanced Design and Digital Architecture
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Programmatic and Spatial Organization According to the system distribution which provides spaces on the levels with good access to each other, Pleasant sun and nice view to the hills and needs of the people in this zone which can be used as a central area, It can be shops. We can have horizontal and vertical access to each shops and also can connect two main streets in this area.
Horizontal access
Vertical access from different levels
These parts of the land include Very Hot and cold zones. It can be used as a landscape and garden which can provide shadow in summer and sun in winter. Use big holes on the system for the part which is cold, It would provide also sun in winter and pleasant shadow in summer . This part of the land is almost flat without good view. It can be used as a sport court because people here need an environment to do sports.
This part of the land has variation in height with good view to the garden in front. itâ&#x20AC;&#x2122;s very close to the sport court which we proposed and it can be used as a gym.
Pleasant sun with a variation in heights and levels with a nice view to the garden and landscape beside it. It can be as a restaurant and garden cafe. 168
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Programmatic and Spatial Organization Section Detail
Intersection between strips creates different access to different strips, and also can extend the spaces in the common places.
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Access to adjacent strips
Extended spaces between strips
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Prototype
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Prototype
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