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Responsive Design Greta Babarskaite


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Dedicated to Aigar, Ruta & Sigute

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Foreword This book is an account of my experience at the Advanced Design and Digital Architecture Master’s in 2012-2013.

Greta Babarskaite www.gretababarskaite.com

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Born in Lithuania, raised in Estonia, educated as an Interior Designer at Istituto Europeo di Design in Barcelona, Greta earned her Master’s degree in Advanced Design and Digital Architecture at Elisava School of Design and Engineering in 2013. If you have any questions feel free to contact her at: greta.babarskaite@gmail. com

About the book I began compiling this book during the master’s and finished it some months after the classes were done. With the benefit of hindsight I was able to reconsider some of the experiments that were done at the beginning of the course, because it takes time to shift ones mind from top-down design that derives from a moment of inspiration to learning how to think in an algorithmic way, using programming logic and relearning geometry and calculus. Unlike traditional design the starting point for these projects were weeks of research and data collection, followed by months of extracting the necessary information with the intention of using at an architectural scale, which was the most challenging part. That is why the final architectural proposals are only single instances of possibilities chosen to illustrate the idea, but they are not the only option for the situation.

Except where otherwise noted, this work is licensed under http://creativecommons.org/licenses/by-ncnd/3.0

Except where otherwise noted, this work is licensed under http://creativecommons.org/licenses/by-nc-nd/3.0/


In these projects I used a number of programs, but there were three that prevailed: (1) Rhinoceros 5 - accurate freeform modeling for Windows (http:// www.rhino3d.com/). (2) Grasshopper - Generative modeling for Rhino. For designers who are exploring new shapes using generative algorithms, Grasshopper® is a graphical algorithm editor tightly integrated with Rhino’s 3-D modeling tools. (http://www.grasshopper3d. com/). (3)Rhino Python - Cross platform scripting for Rhino. Rhino.Python™ is a powerful scripting language in Rhino 5.0 for 32 and 64-bit Windows and Rhino for OS X. rhino. Python is built for flexibility and clear syntax (http:// python.rhino3d.com/). Although these tools helped achieve a certain level of development in my projects, parametric thinking is not about any one piece of

computer software but about geometry, calculus, interaction and topology. Thus the goal is not to let the computer decide everything, rather use it as a tool to speed up our thinking. About Master’s in Advanced Design and Digital Architecture The master’s was created by Jordi Truco (architect, HYBRIDa partner). Since its inception the master’s has been successful at attracting a large number of international students coming from all around the world. It is divided into two parts - BioDesign Laboratory and Computational Design Laboratory. Laboratory studio feel allows for an easy exchange of ideas amongst the students. In 2010 ADDA were the first in Barcelona to build a parametric true scale prototype in Spain. It was a joint effort between the students of ADDA, professors and other professionals. Up to this day it is being exhibited in a number of places in Spain.

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table of contents biodesign laboratory Part 0. Essay Bottom-Up Emergence

100 100 010

Part I. Form Finding Essay: The Genius of Gaudi Research: In Gaudi’s Footsteps Conclusion

100 012 014 022 043

Part II. Geometry of Natural Patterns Essay: Patterns for Biomimetics Research: Biological System Research: Architectural Application Project Application: Iridescent Facade Conclusion

100 045 046 050 059 075 101

Computation design laboratory Part III. Essay Intelligent Architecture

100 100 104

Part IV. Data Scapes Research: the imperceivable WIFI Project Application: Digital Shelter

100 100 110 125

Part V. Annex Digital Fabrication CNC Guide: 2.5 axis and 3 axis

100 100 144 147

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BioDesign Laboratory Course Introduction

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“There is a growing interest in finding guidelines in living systems to help us understand new forms of designing. On occasion this interest makes the mistake of wishing to imbue designs with a veneer of new organic ways, imitating natural forms, perhaps unconsciously aided by the incredible digital modeling resources we are increasingly able to master. This could not be further from our intentions at the BioDesign Laboratory (ADDA). We focus our interest on observing how biological organisms achieve complex emergent structures from simple components. The structures and forms generated by natural systems are analyzed and understood as hierarchical organizations of very simple components (from the smallest to the largest), in which the properties

arising in an emergent manner are rather more than the sum of the parts. In our constantly developing society with its demanding market, the use of new production technologies in fields such as engineering is becoming more frequent, and research is conducted to create state-of-the-art materials, such as composites, which open up new possibilities of use and performance, and contain the logic of living materials. In the field of architecture, even more rightly, we are forced to regain this sensitivity in observation and research, and learn the lesson of nature on the act of formalizing and metabolizing. Our objective is to learn and explore this knowledge to then transfer it and apply it to the design process of architecture and spaces.� Jordi Truco

Source: Truco, J. (2013). ADDA student handbook . Barcelona, Spain.


Jordi Truco Architect, Partner HYBRIDa Director ADDA

Sylvia Felipe Architect, Partner HYBRIDa Geometry of Natural Patterns

Fernando de Lecea Architect Tutor - Grasshopper and Rhino

Feran Vizoso Architect Animal Architecture

Marcel Bilurbina Architect Tutor - RhinoPython

Sergi Valverde Computer Scientist, PhD Applied Physics Dynamics and Evolution of Complex Networks

Mike Weinstock Architect, Director AA Emergent Technologies & Design Architecture of Emergence Francisco Tabanera Architect Gaudi and the Intelligence of Nature

Achim Menges Architect, Director ICD Stuttgart Morpho-Ecologies Mireia Ferrate Architect and Philosopher Cybernetics

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bottom-up Emergence

Biodelab Essay

Steven Johnson uses the term emergence to describe complexity resulting from bottom up organization.

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This term is applied in many fields intelligence”, not only seen in ants, from natural sciences, to computer but also in beehives, bird flocks, and sciences and economics. The idea coral reefs. However this intelligence is that relatively simple elements “ordoes not stop there, ant colonies are ganize spontaneously and without able to learn over time. The ant colony explicit laws to give rise to intelligent changes with the time that passes and behavior”. Those simple elements can as it grows in size. An older colony is be ants, neurons or even humans, but more likely to avoid confrontation with they all base their behavior on these other colonies and adapt its food-collow level interactions without having lecting routes accordingly. That is the the knowledge as a whole. Rather reason why colonies can survive for than being engineered by a master over a decade, while the life-span planner, it is a bottom up behavior. of an individual ant is not more than Systems that at first glance appear twelve months. The colony behavior different, such as ants, cities and huemerges as an evolution over time. man cells all follow the same rules of Similarly cities show emergent emergence. behavior on a different scale. Cities Ant colonies played an important role in underrelatively simple elements “organize standing the characterisspontaneously and without explicit tics of a complex system. laws to give rise to intelligent behavior” At first glance it appears that ant queen orchestrates everything that happens in the complex network of ants, howself-organize themselves throughout ever her role stops with perpetuating the years. Although they are heavily the population. Instead the more imshaped by the top-down forces, such portant role is of the individual ants, as urban planning and certain laws, especially the interaction between ultimately bottom-up forces play a cruthem. For example, ant’s decision of cial role in the way cities are formed, what her job is depends on the frecreating demographic clusters and quency of contact with other ants in distinct neighborhoods. Neighborher surroundings, rather than any hoods are formed based on social other knowledge of what the whole interactions. Jane Jacobs calls it the colony is doing, because ants com“sidewalk” culture. She argues that municate through trails of pherosidewalks serve as a venue for social monones. Therefore many behaviors interactions between individuals. Beof the colony result from the “swarm cause these micro interactions shape


fig. 1

above fig.1 A. Ants in a pheromone trail between nest and food; B. an obstacle interrupts the trail; C. ants find two paths to go around the obstacle; D. a new pheromone trail is formed along the shorter path.

Sources: Johnson, S. (2001). Emergence. London.

Biodelab Essay

the macro behavior of a neighbora head and a tail. As soon as the emhood. The original order of the cities bryo reaches a certain size, cell “colcame from the improvised congregalectives” begin to form. Each cell has tions of people. That is why even now a purpose, whether to be the arm or a similar people cluster in different parts brain cell. However cells do not posses of the city, and one can identify disthe knowledge of seeing the whole, so tinct neighborhoods in each city. Like they turn to neighbor interactions and ant colonies, neighborhoods are “pattransmit molecular signals through the terns in time”. cell junctions. Although each cell has The emergent behaviors can be found on a molecular Each simple element is connected to the level too. Human cells follow other and alters its behavior in response the master plan of the genetic to the behavior of the network. code, but without the local interactions that would be useless. Humans start as a single-celled organism, but at the end of our devela complete DNA information, through opment we are composed of two hunthis low level interaction it is able to dred variations, all working together to generate coordinated global behavior. perform complex tasks. Two seconds Ant colonies, cities, cells are all exafter conception, single-celled embryo amples of emergent behavior. Each divides itself into two parts – head and simple element is connected to the a tail. Then in turn those ones develop other and alters its behavior in response to the behavior of the network. Through this feedback mechanism systems are able to provide more complexity than the sum of its parts. This means that cities are not just bigger towns, or denser suburbs. Emergence creates hierarchies, without outside instructions necessary.

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Form Finding

Biodelab

Form finding is described as a way to generate shapes by taking into account the way the material behaves.

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Form finding. When we apply external loads to a material this tends to react and make a new equilibrium configuration to balance these forces. Looking at different materials such as steel, wood, textiles, fibers or composite materials, can be recognized a change on their form when they are subject to forces of traction, compression or court. During the 20th century, numerous studies have been developed to exploit the understanding of these processes for the production of habitable spaces. A number of designers, architects and engineers among them Frei Otto, Pierluigi Nervi, Felix Candela, Antoni Gaudi, Miguel Fisac, Sergio Musmeci have committed to the development of alternative design strategies informed by material properties. The Multihall Mannheim or the Olympic Stadium in Munich developed by Otto, the Exhibition Hall in Tu-

rin and Aula Paolo VI of Nervi, the Sagrada Familia of Gaudi or the bridge over the River Basento of Musmeci are excellent examples of a different way to deal with the architectural design. Constant interaction between the designer, the processes of matter and of construction gave to those projects the exceptional richness of the “intelligence of material�.

Source: Truco, J. (2013). ADDA student handbook . Barcelona, Spain.

Form finding team: Cristina Centeno (Puerto Rico), Ives Eja Enriquez Silver (Puerto Rico) and Greta Babarskaite (Lithuania)

Architectural Form finding. The Integral envelopes project started with a one week workshop with Mike Weinstock (AA). Eventually the project lasted for a month, it was developed by teams of 3. Our choice of form finding investigation were the catenary curves. If a chain, rope, or other string-like object of uniform density is hung between two parallel points and allowed to reach static equilibrium it takes on a unique shape, called the catenary curve.


Biodelab Essay

fig. 2

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fig.2 - Antoni Gaudi’s - La Sagrada Familia Gaudi used form finding techniques to determine the load-bearing capacities of the towers in La Sagrada Familia and that is how we came up with the tree-like tilted columns.


the genius of gaudi

Biodelab Essay

Antoni Gaudi (1852 / 1926) was an architect from Reus, the head of Catalan Modernism.

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The Basilica and Expiatory Church of the Holy Family, Gaudí’s star project, started off in 1872 as an idea by a bookseller Josep Maria Bocabella after his trip to Italy. The church was planned to be built in one of the blocks of the new neighborhood designed by Ildefons Cerdà. The commissioned diocese architect Francisco de Paula Villar came up with a design for a neo-gothic church (fig.3). Neo-gothic style, popular between 1905 and 1930, was the choice for spiritual and traditional buildings since it was associated to monarchism and conservatism (fig. 4, 5). Strong vertical lines and a sense of great height, pointed windows, gargoyles and pinnacles characterized gothic revivalism. However Villas did not get to build his version of La Sagrada Família shortly after the construction had begun Villas fell out with the board and was fired. In 1883, at the age of 31, Gaudí stepped in. Before beginning his explorations Gaudí studied gothic churches in great depth, he was involved in the construction of the Cathedral in Mallorca and at that time had been

designing some neo-gothic buildings himself, like Casa Botines (fig.6) and Colegi de les Teresianes. However he saw the Gothic style as one with many unresolved issues. He disliked the fragile web of a Gothic church and the light roofs susceptible to fires, but what most worried him were the Gothic buttresses (fig.7). When Gaudí joined the project the construction of the apse (fig.8) and the crypt were already in progress, however when the moment was right he changed the design of the rest of the church and presented a much riskier version with 5 naves, a crossing arm, apse, an exterior ambulatory as a cloister, 3 facades and 18 towers. In order to reach his plans he first needed to resolve the problems he saw with the gothic tradition, especially the buttresses. He devised and studied a number of strategies that attempted to solve the problem of horizontal loads. The most prominent studies he made were of catenary curves while constructing the Colonia Güell church in 1898 (fig.9). A catenary is defined as a “curve that an ideal-

right fig. 3 - Francisco de Paula Villar’s, the original architect’s plan for the church. fig. 4 - Woolworth Building, New York fig. 5 - Palace of Westminster, London fig. 6 - Casa de los Botines, Leon


fig. 6

fig. 4

Biodelab Essay

fig. 3

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fig. 5


Biodelab Essay

fig. 9

fig. 11

fig. 7

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fig. 8


left fig. 7 - Gothic Flying Buttress fig. 8 - Image of the Apse fig. 9 - Colonia Guell fig. 11 - Funicular model of Colonia Guell

fig. 10

est (fig.13). The profiles themselves are based on two triangles for the 6-sided column, two squares for the 8-sided column and 4 triangles for the 12-sided column. Each column starts from a basis of a polygon profile, which is given a twist of a certain degree in a positive direction, then that same polygon from the original position is given a twist of the same degree in the negative direction. The second rotation is then superimposed on the first. This way the column goes from a polygon to a circle as many times as necessary according to the different levels of superimposition. The tree-like columns help distribute weight because each one is intended to reach for the center of gravity of each part of the vault. The twisted column total free height is double the number of points and to comply with these rules each

above fig. 10 - Catenary vs. Parabola

Biodelab Essay

ized hanging chain or cable assumes under its own weight when supported only at its ends” (fig.10). Through rigorous experimentations that involved hanging chain/rope (fig.11) he was able to figure out the inclination of the tree-columns (fig.12) thus optimizing the structural behavior to transmit loads not on to the typical flying buttresses on the side of the building but to the core bringing them down through the major interior pillars. Gaudí let the gravity do the hard work - determine the bends under pure tension using weights to mimic the shape of the vault. Gaudí’s belief was that since it works under tension, it must work under compression when inverted. With this confidence he went on to plan the towers, vaults and columns of the Sagrada Família. From the very beginning Gaudí knew that this church would not be completed in his lifetime. He needed to create a universal language that would aid next generations of architects to finish and add up to his ingenious design. Gaudí accomplished that by setting strict geometrical rules to guide the generation process. For example, he defined four different types of columns. The columns follow a series with 12-point base polygon being the widest, then the 10 point, 8 point and 6 point polygon being the small-

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Biodelab Essay

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type of column is made of a different stone to suit its mechanical properties of supporting load. The columns do not have points, they have a smooth surface, because they are two superimposed helical columns and GaudĂ­ used the continuous undulating look to his advantage to recreate the feeling of natural growth as observed in nature. Another rule in GaudĂ­an language was the use of straight lines. Through his experiments he discovered the magic of turning them into curves. He achieved that by using a variety of ruled surfaces (surfaces that have straight lines), especially hyperboloids (fig. 14), paraboloids (fig.15), helicoids and conoids. Those shapes can be constructed from straight lines, but they generate a double curvature that provides the necessary structural efficiency. Everything from the windows, to details (fig.16) , vaults (fig.17) and even the school next to the church (fig.18) are ruled surfaces . Those shapes can be constructed from straight lines, but they generate a double curvature that provides the necessary structural efficiency.

fig. 13

d.210

d.175

d.140

d.105

right fig. 12 - The leaning columns in Sagrada Familia above fig. 13 - Floor Plan with columns colored


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fig. 12

Biodelab Essay


To sum up, Gaudí had a way of approaching architecture from a holistic point of view. Every piece of La Sagrada Família emerged from his vision, from general dimensions of the church to the religious symbolism follow his harmonious idea. These details are the reason why The Basil-

fig. 14

Biodelab Essay

fig. 17

ica and Expiatory Church of the Holy Family is one of the greatest pieces of architecture of all time and takes hundreds of years and a team of architects to complete. That is the genius of Gaudí.

20 fig. 17

above fig. 14 - Hyperboloid fig. 17 - Vaults at Sagrada Familia


fig. 16

Biodelab Essay

fig. 15

fig. 18

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above fig. 15 - Paraboloid fig. 16 - Detail fig. 18 - Sagrada Familia School


in Gaudi’s Footsteps

Biodelab Research

Following Gaudi’s footsteps we decided to investigate catenaries. We divided the research in 4 parts.

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Investigating a net To get started we used a 45 cm by 45 cm mesh (17.7” by 17.7”) grid made up of a chain joint by plastic pieces. We used a benchmark that we built by laser cutting a larger piece of plywood and raising it using regular metal rods. The method was to hang the mesh taking into account the anchor points, or the coordinates of the points where the mesh is attached. By varying these coordinates during different experiments we were able to

achieve changes in volume and morphologies. Having done the experiments and then then having reproduced them as drawings on Rhino we identified different hierarchies of catenaries. In order to investigate them further we chose to look at them individually. Therefore abandoning the pre-determined grid.

Right Pictures were taken with our own personal camera. The diagrams bellow were reproduced using Grasshopper and Rhino 5, later transferred onto Adobe Illustrator and finalized.


Biodelab Research

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Volume - 10878 cm3 Footprint Area - 900 cm2

Corners out In this experiment we were looking at how the base of the catenary net influence the height. It is similar to the Sagrada Familia was created.

Volume - 2110 cm3 Footprint Area - 92 cm2


Biodelab Research

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Volume - 11584.4 cm3 Footprint Area - 576 cm2

Center point In this experiment we identified the mid-point of the grid and in consecutive steps we pulled it upwards to see the effect on the surface area.

Volume - 7732.7 cm3 Footprint Area - 576 cm2


Biodelab Research

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volume : 10405 cm3 Footprint Area : 576 cm2

Midpoint to corners In this experiment we identified the front mid-point of the grid and in consecutive steps pulled it to the corner point.

volume : 10160 cm3 Footprint Area : 576 cm2


Biodelab Research

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volume : 10405 cm3 Footprint Area : 576 cm2

Midpoint to center In this experiment we identified one of the points on the edge and moved it towards the center

volume : 10160 cm3 Footprint Area : 576 cm2


Biodelab Research

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volume : 7472.2 cm3 Footprint Area : 576 cm2

From corners to center This one breaks away from the square set anchor points and moves them towards the center.

volume : 4610.1 cm3 Footprint Area : 324 cm2


Biodelab Research

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Investigating paper-clip grids In the previous experiments we used a mesh net that we hung from the benchmark and by varying the coordinates of the anchor points we were able to get changes in morphology. In this second set of experiment we thought that by hanging individual paper-clip chain catenaries we can produce grids based on function. The process is to hang chains one by one and join them together. Now the grid

is a result of our experiments, not the starting point. Then the goal is to make them rigid by applying resin and invert them to get compression-stressed forms. After these experiments we were able to conclude that there are different hierarchies of catenaries. Specifically primary and secondary catenaries. Primary catenaries are the limits, while the secondary catenaries give the shape.

Right page Left hanging model Top right unfolded grid Bottom right inverted model


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20 16

volume 3435 cm3

16 1.6 4.8

16 6

This experiment combines 8 catenaries. The exterior ones (4) are the boundaries of the shape, while the other ones (4) make the shape. After the resin is applied to this hanging model and it is inverted, the compressed form gives a volume of 3435 cm3 (209.62in続).

Biodelab Research

6

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24

46

10

18

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volume 4339 cm3

Biodelab Research

17 24

30 10.5 17

This second experiment combines 12 catenaries. Again we consider the exterior catenaries (4) to give the boundary, while the rest, depending on their weight and length give the shape. After the resin is applied to this hanging model and it is inverted, the compressed form gives a volume of 4339 cm3 (264.78in続).


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20

46

24

volume 2150 cm3

12

Biodelab Research

20

31

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The previous experiment were rectangular. This one is triangular. It gives a shape that resembles a dome. Here 3 catenaries act as the boundaries, while the other 3 create the depth or the height of the shape. After the resin is applied to this hanging model and it is inverted, the compressed form gives a volume of 2150 cm3 (131.20 in続).


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12

14

20

14 26 22

17.5

Biodelab Research

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volume 5457 cm3

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12

22

16.5

The 5 catenaries that form the perimeter of the shape are the ones responsible for the flower-like shape found. Yet again, due to the circular arrangement of the anchor points the structure appears similar to a dome. After the resin is applied to this hanging model and it is inverted, the compressed form gives a volume of 2150 cm3 (333.01 in続).


Biodelab Research

33 Individual chains The first two sets of experiments showed us that each catenary has a role in the shape generating process. With this third set of experiment we were interested in hanging individual chains and determining families from them. This time to help us with the precision of the experiment we joined each paper-clip using little hexagonal pieces. We are using two type of paper-clip chains - 8 and 16 piece ones. After the completion of this experi-

From now on to mark the fixing points (or the anchor points) we use A for the primary anchor points and B,C,D for the ones that follow. This way they are marked in layers.

ment we can conclude that unlike in the previous experiments there are more families of catenaries, not only primary and secondary. Their definition depends on the fixing points Another conclusion is that the second family of catenaries act as weights to the first ones and they are deformed into triangles. This means that more fixing points equals less surface area. By adding more connections we could get same volume but less surface material.


Biodelab Research

A

A

area 336 cm2

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B

area 396 cm2

area 217 cm2

Family 1 - Two anchor points (refers to level A) Adding second layer of catenaries to the first one.

Adding second layer of catenaries to the first one.


area 100 cm2

b

area 84 cm2

Biodelab Research

A

A

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area 309 cm2

Adding second layer 2 - Three anchor points (refers to level A) of catenariesFamily to the Adding second layer of catenaries to the mid-points of mid points ofthethe first.first. Adding second layer of catenaries to the midpoints of the first.


Biodelab Research

A

A

area 47 cm2

b

area 36 cm2

area 110 cm2

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C

A B

area 36 cm2

area 110 cm2

Family 3 - Four Anchor points (refers to level A) Adding second layer of catenaries to the mid-points of the first. Adding third layer of catenaries to the mid-points of the second.

area 175 cm2


Biodelab Research

Adding weights In the previous experiment we learnt that the lower level of catenaries act as weights to the first layer of catenaries. In return this reduced the surface area while keeping a similar volume. In this last set of experiments we will add weights to reduce the surface area. We will again use 8 and 16 paper-clip chains but add different weights. As a conclusion to this experiment we can say that each chain needs a double of its weight to straighten itself out.

Adding a-B Curve to 0.25 of the A-A curve A

Adding a-B Curve to 0.25 of the A-A curve A B

A

adding a c-C curve to 0.25 of the B-A Curve

B C

the configuration above will be used for all the weight experiments

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area 242 (121+121) cm2

130 cm2

163 cm2

131 cm2

TOTAL AREA = 492 cm2

area 210 (105+105) cm2 121 cm2

98 cm2

120 cm2

Biodelab Research

area 220 (110+110) cm2

TOTAL AREA = 455 cm2

TOTAL AREA = 494 cm2

a

a

b c

b c

d

d e

area 260 (130+130) cm2

area 260 (130+130) cm2

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area 112 cm2 area 142 cm2

area 146 (73+73) cm2 TOTAL AREA = 662 cm2

112 cm2 142 cm2 141 cm2

area 146 (73+73) cm2 TOTAL AREA = 802 cm2


Biodelab Research

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Compressed models of the instances on the left


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Final Prototype The final prototype is a combination of different connections and weights seen on the previous page.


Sources The Genius of Gaudi http://www.sagradafamilia.cat/ Burry, M., Coll Grifoll, J., & Serrano, J. G. (2010). Sagrada Familia s. XXI. Barcelona: UPC.

Biodelab

Beukers, A., & van Hinte, E. (1998). Lightness. Rotterdam: 010 publishers.

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Bonet, J. (2001). The Essential Gaudi. Barcelona: ECSA. Burry, M. (2011). Scripting Cultures: Architectural Design and Programming . John Wiley & Sons. Illustrations fig.1 - Ant pheromone trails Source: http://www.funpecrp.com.br/gmr/year2005/vol34/images/wob09fig2.jpg fig.2 - Sagrada Familia Source: http://0.tqn.com/d/architecture/1/0/v/o/Sagradafamilia00002482731.jpg fig.3 - Villar’s Plan for Sagrada Familia Source: http://upload.wikimedia.org/wikipedia/commons/a/a0/Sagrada_Familia_%28Villar%29.jpg fig.4 - Woolworth Building, New York Source: http://www1.cs.columbia.edu/~sedwards/photos/misc2004/7.html fig.5 - Westminster Palace, London Source: http://en.wikipedia.org/wiki/Palace_of_Westminster fig.6 - Casa Botines, Leon Source: http://www.flickriver.com/photos/ mynth/2719539650/

Many other books, magazines and lectures served as references during these months of research, but not all of them were directly included in this book.

fig.7 - Flying Buttresses Source: http://www.columbia.edu/cu/gsapp/BT/EEI/MASONRY/14typgoth.jpg fig.8 - Picture of the Apse Source: http://www.wanderingmee.com/2013/05/stylized-jesus-at-la-sagrada-familia-barcelona/ fig.9 - Colonia Guell Source: picture from personal library fig.10 - Catenary vs. Parabola Source: http://www.quora.com/Christopher-Cuong-Nguyen fig. 11 - Funicular Model Source: http://www.whereisdarrennow.com/2010/07/ colonia-guell-church.html fig. 12 - Interior of the Sagrada Familia Source: picture from personal library fig. 13 - Columns Source: http://www.sagradafamilia.cat/docs_instit/arquitectura_d.php with personal color alterations fig. 14 - Hyperboloid Source: http://www.mathteacherctk.com/blog/2011/08/ one-sheet-hyperboloid/ fig. 15 - Paraboloid Source: http://commons.wikimedia.org/wiki/File:Hyperbolic-paraboloid.jpg fig. 16 - Detail Source: from personal library fig. 17 - Vaults Source: from personal library fig. 18 - Sagrada Familia School Source: from personal library

Any other images used in this chapter are from the master’s thesis research


Form finding process reveals the importance of understanding the innate capabilities of material and physics. There is a shift in architecture that prompts architects to change their way of thinking, especially of trying to impose a geometry to a problem. Instead through large-scale testing, material properties and thinking they could take advantage of the form-find-

ing process and achieve projects with the maximum efficiency in performance and minimal material usage. The experiments presented in the previous pages are only the first attempts of understanding this way of working. However these strategies have already been applied to architecture by Gaudi and Frei Otto.

Above Group photo after the Form-Finding workshop with Mike Weinstock, October 2012

Project Completed November 2012

Biodelab

Conclusion: form finding

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fig. 1

Biodelab Research


geometry of natural patterns

Biodelab

In this three month project we were asked to challenge the artificial distinction between skin and structure through the development of an envelope system that integrates structural and environmental performances

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In this context an envelope is not a threshold dividing inside and outside, but a filter that mediates between macro-environmental conditions and micro-environmental provisions. This project went through three stages of development. A very crucial one was the biological research part. Following the principles of biomimetics, we chose to research the iridescence in Peacock feathers. The point is to understand the way nature functions, because nothing in nature

is for the sake of beauty. It has gone through centuries of evolution to become the best it can be to achieve maximum efficiency. After having learnt a few things about the way nature achieves efficiency in the second part the goal is to adapt what we have learnt, understand what it is doing in nature and apply it to a real-life system without copying it directly. In the last step we apply our system to a real scale architectural project.

left fig. 1 - Peacock

Research team - Cristina Centeno (Puerto Rico), Ibrahim al Nemeh (Jordan), Marta Besalu (Spain), Greta Babarskaite (Lithuania)


patterns for biomimetics

Biodelab Essay

First examples can be seen from the iron age of Art Nouveau in the 19th century, all the way through to the more recent titanium fish shapes in the computer aided designs of architect Frank Gehry. However this design approach is form driven and offers only a superficial similarity to the natural world for decorative or symbolic effect.

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With the new available tools and cross-disciplinary collaborations it is possible to investigate the potentiality of biomimetics. Designers no longer need to investigate nature in terms of beauty, but instead in terms of performance in order to apply it in contemporary architecture. In order to understand biomimetics, one can investigate the physical and geometrical principals of morphogenesis. Morphogenesis is known as the process by which natural systems produce and organize configurations of matter in space and over time.

The restriction in many living things is that form is cheaper than material. It is cheaper to obtain strength properties through geometry or form, than through material itself. Therefore there is a variety not for the sake of beauty but because it is necessary in nature. The act of metabolizing nutrients into strong materials requires more energy, whereas the way in which these materials are arranged is cheaper. In nature geometry is more important. There are comparatively few materials that nature uses. In comparison to those that are available in the fig. 3

fig. 2

above fig. 2 - Electron microscope image of a spider’s silk spigots left fig. 3 - Spider Web

Variety of form that exists in nature is fascinating because of the way it organizes material. This auto-organization has not been designed, but it has emerged. The broad repertoire of shapes exists in nature, due to the basic necessity in nature to be efficient.

design community. In nature none of the biological substances can be classified as high performance materials, they are soft and do not have the properties of strength or hardness. They perform because of the way they are put in place. It is the way in which


matter is arranged that generates the variety of capacities that can be observed. The design of the material, how it is put is more important than the material itself. This has been studied in the biomimetics of the silk of the spider (fig. 2, 3). One could study this by examining the chemicals that spider uses and the other way is to understand how the spider ties the web. The shapes that are found in nature are diagrams of forces acting on organisms during a specific period in time. According to D’Arcy Thompson in On Growth and Form, organisms self-organize according to the forces to which they have to react. In general one could say that each type of stresses tends to produce a dominant pattern: natural organism must react to stress and self-organize when they are growing. Force of growth constrains and restricts the way the organisms are able to respond, to react to other forces that surround them.

Growth usually means a change of size and sometimes this change of size implies as well a change of form. There are organisms that grow in an isometric way, and there are organism that grow in allometric way. Humans fall in the latter category, because as they grow their size increases differently (fig.4). One of the main constraints of growth is the ratio of surface to body. The relation that exists between the surface that surrounds a given volume changes when the volume is made bigger. Something that is very small has less volume in relation to the surface, and something that is very big has too much volume in relation to little surface. This is a very important restriction in nature for things to be formed as they are. Therefore if one scales an ant 200 times the pressure that its legs need to bear will be 1400 times bigger. Increasing 200 times the size of an ant for each square meter of surface of their leg will have to bear much more volume and weight. The paradox is that if an ant is increased a certain size, but the material that it is made of stays the same, then the ant that is usually fast and agile will not be able to stand its own weight. The relevance of gravity is different depending on the size. When there is a very small size and weight, volume does not have so much relevance as shape and force in morphogenesis. Other forces become the modellers of small organisms. Gravity looses relevance in an exponential manner when the size becomes smaller. When things are smaller the most important shaping force is surface tension. Because the relation between the quan-

Biodelab Essay

fig. 4 - Human Allometric Growth

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Biodelab Essay

48

tity of volume of weight, the relation of the volume to the surface is less. Surface tension stresses are more important in the small sizes. The effect of the intermolecular forces is to pull into the interior of the nucleus. Intermolecular forces are like springs that keep molecules together, trying to achieve the minimum surface possible. For this reason they tend to generate spherical forms, because molecules do not want to be on the surface. For example, water has a relatively high value of surface tension. The effect of the surface tension can be observed in a drop of water. When a drop of water appears spherical it is a sign that is a very small drop of water, because it is not affected much by gravity. The effects of gravity as a modelling force decreases in an exponential way as size diminishes. A leaf uses this property to auto clean its surface. Surface tension keeps the drop as a sphere and the drop rotates and takes the dust and this way the leaf stays clean (fig.5). Multi-functionality is very common in nature, whereas in conventional engineering it is common to think that elements should be mono-functional. In conventional engineering separate optimum elements are designed, very efficient for one single function. Things are done this way, because we are generally able to calculate only simple things. However, nature deals

with complexity. In nature elements can be multifunctional, but they are not as optimum as efficient for one single thing. In conclusion, current architectural practices should learn from the systematic processes of organization in nature. We are currently faced with degradation of the environment and waste material, but there is no waste material in nature. In ecosystems every waste product becomes a raw material for another process. By learning that geometry comes before the material and that a shape is designed in order to achieve performance, a lot of the material could be reduced. It needs to be understood that designers do not simply create things. They have the responsibility because they act as initiators of systems of resource collecting, labor application, manufacturing, marketing, distribution, consumption and disposal. From an ecological point of view, there are no such things as finished objects: there are only systems.


Biodelab Essay

fig. 5

49

above fig. 5 - Auto-cleaning lotus leaf


biological system

Biodelab Research

By looking at a specific instance from the back of peacock’s head we learn a great deal about the way its feathers are layered and organized, the different typologies that peacocks have and the striking effect of the coloration.

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Peafowls are two Asiatic species of flying bird in the genus Pavo of the pheasant family best known for the male’s extravagant eye-spotted tail The male is called peacock, the female peahen and the offsprings peachicks. They are found in South Asia, Burma and Congo. Peacock forages and nests on the ground but roosts in the top of trees. During courtship,long ornate tail is fanned out and held erect. Types of tail feathers. The tail feather in peacocks protect the tail region and are supposed to provide stability during flight. In the vast majority of birds, the tail-coverts are small feathers, just a few centimetres long. However, some birds like the peacock have very large tail-coverts for decorative purposes. An adult peacock has an average of 200 tail feathers and these are shed and regrown annually. Of the 200 or so feathers, about 170 are ‘eye’ feathers and 30 are ‘T’ feathers. The ‘eyes’ are sometimes referred to as ocellations.

fig. 6

Geometry of the tail. Tail feathers form a semicircular fan over an angle of more than 180 degrees (fig. 7). The fan formation is very even because the axis of every feather can be projected back to an approximately common geometrical center. The radial alignment of feathers requires the root of each feather to be pointed with a remarkable degree of accuracy. All the eyes are visible because the feathers are layered with the short feathers at the front and the longer feathers at the back. The eyes have an even spacing because each feather has the right length. Displayed feathers are put into position by muscles in the peacock’s tail. Not only can the peacock deploy the feathers, but he can also make them vibrate and produce a characteristic hum.


not merely pigments. There is a nano-structure that produces an iridescent look. Structural Coloration can be observed throughout different species including beetles, snakes, Butterflies and Birds. The brightness of their color are not produced by the intensity of the pigment, but by the little nano-structures inside their wings on scales.

Biodelab Research

Function. Even though peacock is a bird and most birds can fly, peacock does not posses this function. It’s most well-known element - the feathers - do not lock and for this reason it cannot lift itself high in the air (fig. 8). Digging deeper into the composition of the feather we can see that there is a reason for this lack in function. The colors produced by those feathers are

51

fig. 7

fig. 8

left fig. 6 - Peacock above fig. 7 - Reproduction of peacock’s tail organization fig. 8 - The two type of barbules - flat (for non-flight feathers) and hooked (for flight feathers)


Biodelab Research

fig. 9

52

fig. 10

fig. 10

Butterflies the images above are examples of structural coloration seen in lepidapeae butterflies (fig.9). The black and white images are the microstrucutres observed at nanoscale (fig. 10). Lepidoptera’s anatomy is covered with microscopic scales. They allow heat and light to enter, and also insulate the insect. on the right is a colored scanning electron micrograph of one of the scales.


Visual signs Directionality & Conspicuousness bright splashes of color are used to direct signal at intended receivers such as rivals and prospective males. Many species have ultra-structural modifications that increase the directionality of iridescent signals. Animals usually have pairs of highly saturated iridescent colors that peak at different wavelengths to generate high contrast. Environmental variation Iridescent color hue variations are dependent on colors-producing nano-structures. Slight variations in these nano-structures alow some animals to change in response to the environment. Wavelength variation Iridescent signals provide animals with the ability to produce colors reflecting at different wavelengths. Long-wavelength colors allow animals to match the reflectance of their natural background, but short-wavelenth colors can be used as private communication channels if their predators lack UV vision.

the reasons for structural coloration vary depending on the type of animal.

Non - Visual Signs Thermoregulation The little structures that are responsible for structural coloration decrease the absorption of solar radiation and air spaces found between structures act as heat collectors used for warming. Friction reduction Some snakes have iridescent scales, those have regularly arranged micro-ridges that reduce friction. Similar structure can be seen in fossorial golden moles and in microsculpted cuticles in bettles. Water repellency The micro-ridges found in snakes, insect wings and birds reduce wettability. In the case of peacock their wings are hydrophobic, because water drops are stopped by the micro-structures. Strengthening Iridescent bird feathers are stronger than other feathers, because they involve melanin.

Biodelab Research

Reasons for Structural Coloration

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Angle of vision of the observer

Biodelab Research

Angle of light ray

Stem

Barbules

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Direction of feather

Mechanism of Structural Coloration

Structure of feather

External Factors There are certain factors that contribute to the colors that are observed on the peacock. Some of the external ones relate to the angle of sun that is reflected on the feather and the other is the point of view that the observer is taking. By changing that point of view we can see a subtle change of color.

Barb


loose barbs

Biodelab Research

close knit barbs

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Parallel alignment of the barbules

Macroscopic Structure Moving one scale down, the important factors that contribute to the appearance of the feather is the parallel alignment of its barbules. Since peacock feathers do not lock, because they are not used to fly, they organize themselves in a parallel matter. The other factor is how closely organized they are, that contributes to the intensity of color.

Distance between barbs


Biodelab Research

fig. 11

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Nano-scale Variables factors explained in the previous pages describe the visible factors, but what produces the variety in color are the variations in nano-structures that are found inside the smallest part of the feather - the barbule. Keratin surface covers the structure found below, it does not have color. It allows light to pass to the layers below. Biophotonic cortex is responsible for the color production. It is explained on the other page. Melanin core is the only pigment in the peacock feather. It acts as a backdrop for the structural coloration. Lack of this pigment explains the absence of color in albino peacocks.

top Keratin Surface middle Biophotonic cortex bottom Melanin Core


flat organization of the barbules

micrograph of the barb with barbules

Transverse Section surface

core

Biodelab Research

surface

cortex

cortex

57 three layers of the barbule

lattice design of a specific barbule

Longitudinal Section

fig. 12

parallel organization of the melanin rods with surface keratin layer removed.

air void melanin rod isometric diagram of the cortex layer

Barbule with its flat organization allows some frequencies of light to pass and others to be reflected. That happens due to the photonic lattice structure of found in the cortex. This period nanostructure is made up of cylindrical melanin rods that run parallel to the surface of the feather.


lattice constant shift the mid gap frequency of the photonic gap number of plane controls the production of additional colors and strength of iridescence.

Biodelab Research

Barbule section

spacing 140 nm

58 spacing 165 nm

periods 10

periods 6

Yellow barbule

Color production mechanism

Green and blue barbule

the color that is reflected depends on the number of planes & the spacing between them. that configuration allows some frequencies to pass and reflect a color that is perceived by the human eye. The main colors are yellow and green/blue


Architectural investigation

Biodelab Research

After having learned a few things about the way nature achieves time-tested efficiency in the second part the goal is to adapt what we have learnt, understand what it is doing in nature and apply it to a real-life system without copying it directly.

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Investigation I - Filtering light

We began by exploring different levels of porosity by creating cuts in rectangular PVC sheets and seeing the results. In this first benchmark model we were interested in creating different levels of porosity. We were trying to do that by cutting openings of different widths and placing them at various distances from each other.


Investigation II Receiving & Projecting

Biodelab Research

In this second phase of investigation we began thinking of a system that would receive input from the sun and project it to the interior of the space. In this second phase we were starting to use Rhino Python scripting to work with inputs and outputs as points. The points are what attract those planes. Varying the intensity of attraction, the readiness of the planes to deform and distance of the attractor point we can set up certain parameters to incorporate environmental input.

Top View

60 Front View

Sun Emitter

Top Layer [Outdoor Enviroment]

Perspective View Bottom Layer [Indoor Space]

Output B Projector

Output B Projector


Top Layer - angled top layer/one attractor in different positions

Biodelab Research

no. of generations = 35 scale = 1/(dist*20) curve degree = 2 max. distance = 20 no. of pts on curve = 10

61 Bottom Layer - angled bottom layer/three attractors with different positions no. of generations = 35 scale = 1/(dist*20) curve degree = 2 max. distance = 5 no. of pts on curve = 10

Investigation II - Receiving & Projecting


Biodelab Research

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Investigation II - Receiving & Projecting

Other instances of altering environmental conditions.


Biodelab Research

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Using attractor points means that this strategy can work on many different scales.


cnc tool

Biodelab Research

While preparing the prototype for the second investigation and the RhinoCam file for milling we were faced with limitations of the 3-axis CNC machine we were using. We were trying to mill a prototype that has negative angles, but we were able to overcome cnc tool this limitation by flipping the prototype during the milling process. To reach side 1 the smooth finish we had to remove it that from the stock and the sandhas it.area been cut

impossible to reach

side 1

side 2 area that has been cut

cnc tool

impossible to reach

side 2 area that has been cut now it can be reached

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Investigation II - Receiving & Projecting

cnc tool

Above Diagram of the negative-angle problem Below Images of the prototype making process

area that has been cut now it can be reached


Biodelab Research

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In this prototype we were hoping to represent one layer of the filtering system proposed on the previous page.


Biodelab Research

Investigation III - Layer & Density

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After having experimented with two layers we were interested in starting to achieve density with different layers because the nanostructures in peacock use layers to filter light into various colors. Method Using RhinoPython we can import certain rules for the parameters of our choice to get the desired results. Parameters Number of layers - define number of layers: 3 planes (p1,p2,p3). Planes work as a generic starting point that later can be adapted to the site. Distance - Define distance between each plane. Distances between planes would be set depending on the function we want each layer to have.

Density - Define density for each layer: number of lines in each plane. Density of lines would control the possible amount of connections between layers. Connection - Create in between planes to store attractor points. Positioning of atP planes in reference to our original layers would affect the angle created between layers. Attraction - Add attractor points to each atP (atP1 and atP2). Attactor points serve as the connections between layers. The more connections we have the stiffer the system would be and the less porosity it would have. If necessary repellers would be added to create voids. Deformation - in this step we deform density lines towards the attractor points.

During the experimentations the script will be fine-tuned and redefined to get desired results.


p1

p2

p3

Distance p1 p2

d1

Connection

p1 p2

atP1 d1

p3

atP2 d2

Density p3

Attraction

p3

den3=3

Deformation

p3

atPt1 atPt2 d1

p2

den1=6 den2=4

d2

p1 p2

p1

d2

Parameters that can be modified to get an interesting result.

p1 p2

atPt1

p3

atPt2

Biodelab Research

Number of layers

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Medium density

High density

Biodelab Research

Low density

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Investigation III - Layers & Density

Number of attractor points and density (20 attractor points + 2 layers) In these experiments we begin with a set of parallel lines, then set a number of attractor points and experiment with the connection distance between deformed lines to create density.


Medium density

High density Biodelab Research

Low density

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Number of attractor points and density (50 attractor points + 3 layers)


Medium density

High density

Biodelab Research

Low density

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Investigation III - Layers & Density

Number of attractor points and density In these examples the number of attractor points stays the same but the green connection distance changes. Decreasing the connection distance covers up the sample more.


Medium density

High density Biodelab Research

Low density

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Investigation III - Layers & Density

Number of attractor points and density


Medium density

High density

Biodelab Research

Low density

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Investigation III - Layers & Density

Number of attractor points and density these examples show good differences in density, but also create square-like shapes.


Medium density

Biodelab Research

Low density

High density

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Investigation III - Layers & Density

Number of attractor points and density here the number of attractors increase proportionally as the number of layers increase


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The examples above explore the nature of generative design.


Project application: Iridescent Facade After the experimentation we chose a site , Elisava School of Design and Engineering to make site specific developments in the proposed system.

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Elisava School of Design and Engineering is located in Barcelona, Spain. In this part of Europe sun is abundant throughout the year, but while in winter it can be an advantage, in summer it creates unbearable interior conditions. These conditions require high costs for a cooling system. With the school operating up until the end of july, weather temperatures get up to 30째C (86째F). These climate conditions

Location - Barcelona, Spain Climate - Mediterranean Building use - University Focus - South/East Facade

especially affect the southern facade of the building, because it stays exposed to the sun during the hotest hours, specifically from 11:00 am to 2:00 pm every day during the summer months. These conditions are unbearable for students that use those classrooms during July. plus it does not meet the modern energy efficiency standards, which urge buildings to be more naturally ventilated.


Biodelab Application

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Entrance

Balcony

High

Classroom

Medium

Computer room

Low

Facade Uses Analysis and Sun Requirements this is an elevation of the South East facade. It shows the general use of the rooms that have their windows facing to this facade. The one below shows the light necessity in each room.

Library


Biodelab Application

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Environmental Conditions

Facade analysis throughout the day To asses the real problem during the summer months we ran an Ecotect analysis and saw that this facade is exposed to sun mostly during the hottest hours during the day


Biodelab Application

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Environmental Conditions Analysis conducted DAY : JULY 1 TIME: 12:00

Sun analysis in Summer In order to asses the environmental conditions we did a sun analysis on the facade we are interested in. Since the heat problem is most prominent in Summer we picked a day in July. In order to use it in the further stages of the project low, medium, and high exposure zones are identified using Grasshopper plug-in.


Paths starting paths are defined manually keeping in mind the scale of the building same ones are used for interior and exterior deformations.

Biodelab Application

Points these so called attractor points represent the high intensity points of the sun.

Deformed paths the starting paths are deformed by the points

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Connections between paths Deformed curves that are closer together connect by straight lines, while those that are further apart stay open.

Architectural Facade Experiments

the proposal focuses on trying to remove the distinction between the outside and inside and to explore the very definition of a wall. this proposed facade attempts to combine the functionality of a passage, balcony and a classroom.


Biodelab Application

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Architectural Facade Experiments

A number of options were evaluated before the final option was chosen. We were looking for differences in density based on the facade use. This first example shows the effect if we would start with three layers of paths.


Biodelab Application

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In this example the starting paths start from the same point, but end with three end points. This specific outcome is too dense.


Biodelab Application

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Architectural Facade Experiments

In these examples we start using only one layer of paths that get deformed to different widths based on where the attractor points are placed. However the final result appears blocky in the high density areas.


Biodelab Application

83

In this example previous problem with the block appearance was getting diffused by introducing transitional connections in between the high density, medium density and low density areas.


Biodelab Application

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Final Proposal

After having gone to some attempts to integrate the solar analysis, translating it into attractor points we decided to use two layers. The exterior responding to the sun analysis, while the interior layer responding to the program of the school. The interior layer cuts through the floors and it is structural.


Biodelab Application

High intensity

Medium Intensity

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Paths, points & deformed paths

Exterior Deformation the exterior paths are deformed towards the outside to create depth & protect the building from exposure to sunlight.


Biodelab Application

High intensity

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Medium Intensity

Paths, points & deformed paths

Interior deformation the same strategy is deployed for the interior facade. More overal depth is created in the hotter areas, so the interior classrooms stay cooler throughout the day.


Biodelab Application

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Left Plan views of the facade intervention

right section shadowing


Biodelab Application

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Connections

The script connects curves based on the distance. Purple means that the curves are closer together while green shows that they are further apart. Curves connect based on a distance parameter.


Biodelab Application

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In the further development of the project these subtle color variations could represent change in material.


Biodelab Application

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EXTERIOR ELEVATION exterior

INTERIOR ELEVATION interior

facade intervention

above this image shows the elevation of the proposed intervention. We can see the differences in density based on the program. below the drawing below shows the interior part of the system. this is the one that runs throughout each floor.


The materialization of the project has been considered purelly on conceptual level. The proposed materials reflect the flexibility and functionality we were looking for they have to adapt to the double curvature and the irregularity of the shapes. There were three type of materials we were looking for - one structural material for the pipes. A transparent material for the “window-like� parts. And finally material for the colored connections. Structure the pipes that run throughout the building can be cut into smaller segments and fixed floor by floor. The material could be steel, it would support the load and can be assembled easily. In the further developement of the project this material should be reconsidered and composites could be introduced.

Due to the time limits of the project we were not able to develop the material selection.

Windows the traditional material for windows in glass. However in these type of non-standard architecture glass is both inefficient and difficult to install. For these reasons our proposal is ETFE material. Ethylene tetrafluoroethylene is a fluorine based plastic. It is lightweight, transparent, self-cleaning and flame retardant. Throughtout the past decade it has been used extensively in architecture, such as the Eden Project, Allianz arena. In those examples it has been filled with special gas. But it can be used without gas too, like in this proposal. Colored pieces in this proposal the colored pieces represent architectural louvers. Their exact material needs to be evaluated in the further development of the project.

Biodelab Application

Material selection

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ETFE Etfe

STEEL Steel

GLASS GlassRAIL rail RAISED FLOOR Raised floor Floor SLAB slab FLOOR BOLT Bolt

Biodelab Application

Lighting LIGHTING system SYSTEM

92 Corbel

CORBEL False FALSE CEILING ceiling

Section through the facade


Prototyping a piece of the facade

Biodelab Application

Preparing the stock MDF comes in 1-2 cm height pieces. However since we want to mill over 2 cm we had to stick some pieces together and leave them for some days to dry.

Milling When the stock was ready we prepared a RhinoCAM file with the 6 pieces that we were interested in milling. These are the first steps in the milling processes.

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Facing This is how the stock is after the material clean up process called facing.

Prototyping

we had chosen to do a 2:1 prototype from the exterior part of the proposed facade. One of the challenges we were faced with was the double curvature of each of the pipes and then the consequent placement of the sticks. We attempted to resolve these issues by splitting the pipes in half vertically, placing a digital file of each side on an MDF stock that we prepared and cutting each side on the CNC marking the placement of sticks for later reference. After the mold is cut, using it to pour resin, leaving it to dry. And after having erected it, gluing the sticks manually.


Finishing After some hours the milling process smooths the mold.

Biodelab Application

Mold is ready the previous process was repeated for both sides of the mold.

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Preparing mold for the resin In order to pour the resin we need to lubricate the mold using Vaseline, otherwise we would not be able to remove the mold afterwards. Wax is applied to both sides.

All the pictures were taken by the team’s personal cameras.


Left to harden We leave the resin in the stock for 24 hours. Then we opened it.

Biodelab Application

Resin Here the wax has been applied. Acrylic resin gets mixed and poured onto the stock

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Biodelab Application

Opening the mold while removing the sticks from the mold one was destroyed but five pipes remained.

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Erecting the prototype They were quite heavy to erect on the stand. But with some modifications in the stand they were able to stand up.


Biodelab Application

Placing the sticks sticks were cut on the laser cutter and placed in their places on the marks that were placed in the mold.

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Sources

Illustrations

Patterns for biomimetics

fig.1 - Peacock Source: http://funpoper.com/paon-bleu-pavo-cristatus. html

Lecture by Silvia Felipe - Geometry of Natural Patterns. October 2012 Thomson, W. D. (2011). On growth and form. USA: CreateSpace Independent Publishing Platform. Myers, W. (2012). Bio Design: Nature + Science + Creativity. New York: The Museum of Modern Art.

Biodelab

Biological system

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fig.2 - Electron microscope image of a spider’s silk spigots Source: http://science.howstuffworks.com/zoology/ insects-arachnids/spider3.htm fig.3 - Spider Web http://upload.wikimedia.org/wikipedia/commons/a/ab/ Spider_web_with_dew_drops04.jpg

Vukusic, P., & Stavenga, D. (2009, January 21). Physical methods for investigating structural colours in biological systems. Journal of the Royal Society .

fig.4 - Human Allometric Growth Source: http://vertpaleo.org/The-Society/blog-oldbones/ Old-Bones-Blog/December-2013/Growing-up-(and-out,and-sidways,-and-around)---.aspx

Blau, S. K. (2004, January). Light as a Feather: Structural Elements Give Peacock Plumes Their Color . Physics Today .

fig.5 - Lotus leaf Source: http://best-wallpaper.net/Lotus-leaf-ladybugdrops-of-water-insects-green_1920x1200.html

Jian Zi, X. Y. (2003). Coloration strategies in peacock feathers. (Y. R. Shen, Ed.) PNAS , 100 (22).

fig.6 - Peacock Source: Stock image fig.7 - Geometry of the tail Source: Thesis research

Kinoshita, S., & Yoshioka, S. (2005). Structural Colors in Nature: The role of Regularity and Irregularity in the Structure. Chemphyschem . Shinya YOSHIOKA, S. K. (2002). Effect of Macroscopic Structure in Iridescent Color of the Peacock Feathers. Osaka University, Graduate School of Frontier Biosciences , Osaka.

fig. 8 - Barbules Source: http://www.vcharkarn.com/uploads/229/229899. jpg fig.9 - Butterfly Source: http://avenger-blog-oo.blogspot.com/2011/12/ purple-butterfly.html fig. 10 - Blue morpho butterfly Source: http://www.sciencebuzz.org/blog/bursts/ cash-butterfly-biomimicry fig. 11 fig. 12 - Nanostructures Jian Zi, X. Y. (2003). Coloration strategies in peacock feathers. (Y. R. Shen, Ed.) PNAS , 100 (22). fig. 13 - Elisava Source: Picture from personal library

Many other books, magazines and lectures served as references during these months of research, but not all of them were directly included in this book.

Any other images used in this chapter are from the master’s thesis research


During these months researching for the Geometry of Natural Patterns I understood the importance of learning from nature, but not copying it. One of the most important observations about this project is that it can behave on different scales. It can be adapted to the necessities of the site. However due to the time limitations this project’s scope was limited to a certain level of development. But in the future there are certain areas that need to be re-examined. The focus should shift to the use of color on the facade.

What seems like a trivial outcome could contribute to a number of improvements in architecture. Color changing paint could be introduced to the facade which would change based on the weather influencing the mood of people inside. This type of improvement is relevant in the northern countries where sunlight is rare during the winter months. Furthermore the pieces could rotate, like the sun collectors, and change color with each angle. These type of decisions should come from more months of research.

Above Group photo after the final BioDeLab presentation

Project completed February 2013

Biodelab

Conclusion: Geometry of natural Patterns

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computational design laboratory Course Introduction

“The modern definition of artificial intelligence is “the study and design of intelligent agents.” We say that an intelligent agent is a system that perceives its environment and takes actions that increase their chances of success.

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In computer science, the “evolutionary computation” is a sub field of artificial intelligence. This is the general term for several computational techniques that are based in some way in the evolution of biological life in the natural world. Of course the future of computational processes will by fully involved on the “evolutionary computation”, for their clear utility in the selection and optimization processes.

But in the world of digital morphogenesis in fully process of exploration and development there are other automated processes to generate three-dimensional shapes and diagrams, included in the field of artificial intelligence such as intelligent agents, particle systems or networks and databases. In the “Design studio” we will be centered on these processes to achieve self-organization of systems, and generation of complex forms from simple rules. We will work with vector diagrams and volumes defined by polylines, and vectors. This will require working with programming and establish rules and digital algorithms. Therefore we will let them govern the systems to generate these results. To write these computational codes we will work on the programming environment such as python.” Jordi Truco

Source: Truco, J. (2013). ADDA student handbook . Barcelona, Spain.


Jordi Truco Architect, Partner HYBRIDa Director ADDA Fernando de Lecea Architect Tutor - RhinoCam Marcel Bilurbina Architect Tutor - RhinoPython Marco Verde Engineer, ALO architecture Tutor - Fabrication Pau Sola-Morales Architect, PHD Harvard Genetic vs. Generative

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Intelligent parametric Architecture

Codelab Essay

Parametric design is not new. Designing has become synonymous with computation. Every field from architecture to graphic design relies on the computer from the onset of the project up to its completion. Architects use computer-aided tools to build models, draft, and help them visualize ideas. These types of models are very static and require a great deal of detailed low-level manipulations to make modifications.

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Digital parametric design, introduced a few decades ago, allows designers to specify relationships among various parameters of their design model, so then after designer can make changes only on a few parameters and the remainder of the model reacts and updates.1 These changes are handled by the computer, but are based on the associative rules set by the designer. This type of generation of forms, geometries and buildings is not a new technique. It dates back to as far back as the 15th century. “The generative methodology consists of recombination of architectural elements and their recursive transformations: given one or more initial forms and a series of rules of transformation, new forms can be generated by successively applying rules to the initial (or intermediate) forms to produce the final forms.”3 According to Wittkower, who studied late renaissance architecture, Leon Battista Alberti used a formal grammar which allowed him to combine columns with entablature and pillars with arcs, but never the other way around; Also It was Wittkower who identified a

technique that Palladio used to generate floor plans for his villas, based on logical deduction he would start with a 9 square grid and combine it in proportional ways (fig.1). Also Colin Rowe in the Mathematics of the Ideal villa identified that Palladio’s Villa Rotonda (1550) and Le Corbusier’s Villa Savoye (1929) used different processes to arrive to the same simplicity, this way connecting contemporary architecture to the classical.2 In the 90s software from the automobile industry, aeronautics and cinematography allowed new ar- parametric design allows designers to chitects to take a specify relationships among various leap forward and parameters of their design model. generate innovative forms breaking away from the rationalist tradition4 (fig.2). More recently the widespread use of computers and especially the ever-increasing power of the computers to calculate lead to the introduction of new geometric tools such as meshes and nurbs as well as parametric scripting that allows designers to refocus their agenda towards one facing away from the grasps of modernism.


However this powerful freedom of representation has often been interpreted as a change of paradigm. We now often hear contemporary architecture being called digital, virtual or cyber. Some architects, like Patrick Schumacher are trying to introduce “Parametricism” as the next architecture style after modernism. There is some sort of vacuum following the death of modernism. There are some architects that are rigorously and systematically exploring new possibilities. But with the lack of boundaries others are accepting script as a style, which is far from the intentions. So we see a “mind-numbing image of complexity, falling short of its rich

potential to correlate multivalent processes or typological transformations, parallel meanings, complex functional requirements, site-specific problems or collaborative networks.”5 Although these trends represent post-modernism, there is no real breakaway from modernism. The computer enabled an exploration and an expansion of the theoretical space of formal system possibilities. At the end architectures of formal systems and the ones generated by computer follow the same pattern: “the use of generative grammars to transform arbitrary, axiomatic forms into new ones according to geometric rules of transformation.” 3 In fact, they accentuate the paradigm of modernity. In order to move even further away from modernism we need to look at architecture from a genetic perspective. In 1953 when the discovery of the DNA molecule gave a physical form to genes some scientists proposed the idea that there is an isomorphism between genes and appearance. This lead to the idea that there is a code of life that when applied determines the characteristics of a living being. But the process is not this direct, the transformation of information from DNA to production of proteins occurs in “a medium of molecular compounds that interact and feed off of each other in a complex, non-linear dynamic” thus influencing the final appearance3.

Codelab Essay

fig. 1

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fig. 2

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This brings us to the point that Greg Lynn brought up in the Animate Form: Traditionally, in architecture, the abstract space of design is conceived as an ideal neutral space of Cartesian coordinates. In other design fields, however design space is conceived as an environment of force and motion rather that as a neutral vacuum. Form can be shaped by the collaboration between an envelope and the active context in which it is situated. While physical form can be defined in terms of static coordinates, the virtual force of the environment in which it is

Sources Burry, M. (2011). Scripting Cultures: Architectural Design and Programming . John Wiley & Sons. 5

Jabi, W. (2013). Parametric Design for Architecture. Laurence King Publishing. 1

Lynn, G. (1999). Animate Form. Princeton Architectural Press. 4

Sola-Morales, P. (2013, April 27). Genetico vs. Generativo: de la generación automática de formas. Retrieved from Architecture, Information and Complexity: http://psolam.wordpress.com/2013/04/27/ genetico-vs-generativo-de-la-generacion-automatica-de-formas/ 3

designed contributed to its shape.4 With the help of associations between different elements designs can react to structural forces, material behavior, thermal and lighting variations as well as contextual conditions. Furthermore since these parametric models represent a construction logic of the structure, they can be translated into geometries that can be digitally fabricated. Like Gaudi said “It’s okay to be innovative in design, but you don’t need to be innovative in construction”. This way we will be designing a process not a static object.

Illustrations fig. 1 - Diagrammatic Analysis of Palladian villas by Rudolph Wittkower Source: http://www.virginia.edu/president/kenanscholarship/work/archive_files/penley_chiang/Images/Palladio/ Influences/Wittkower%20diagrams.htm fig. 2 - Greg Lynn (b. 1964) Embryological House, 19989, still frame from the design process. Source: http://ivc.lib.rochester.edu/portfolio/tasting-space-2/


Process: 1-call main() function which tells you to select a curve from rhino craved and number of curve divisions numCurves. 2-with that info main() runs a recursion definition called curveRecursion which requires crvID and numCurves to run. 3-curve recursion first calls a function to split the curves called GetSplitCurves and them curves, then it measures curve length with length. And says if length is less than something stop the function. For the length that is above the minimum length apply a transformation defined in GetNewCurveGeometry. “”” #function to split a curve def GetSplitCurves(crvId, numCurves): #divide curve pts = rs.DivideCurve(crvId, numCurves) #store t parameters of the division points in the curve t = [] for i in range(0, numCurves-1): t.append(rs.CurveClosestPoint(crvId, pts[i+1])) #split curve passing list of t parameters arrCrv = rs.SplitCurve(crvId, t, True) #return set of new curves return arrCrv #recursive function def CurveRecursion(crvId, numCurves): #call function to split curve curves = GetSplitCurves(crvId, numCurves) #calculate length of the splitted segments length = rs.CurveLength(curves[0]) #recursion condition #evaluate length: if length < value : get out of the function. Stop recursion if(length<0.02) : return #else: apply transformation to the splitted segments for i in range(0, len(curves)): #for each segment apply a transformation calling the function GetNewGeometry(crv) curves[i] = GetNewCurveGeometry(curves[i]) #call again the recursive function CurveRecursion(curves[i], numCurves) def GetNewCurveGeometry(crvId): #divide the first segment in two segments pts = rs.DivideCurve(crvId, 2) #Pts[0] #get the first point on the segment. That point will be the starting point on the curve.

Recursive Function

t0 = rs.CurveClosestPoint(crvId, pts[0]) #get tangency at the fist point vectorTanStart = rs.CurveCurvature(crvId, t0)[1] #Pts[1] #select the second pt, the mid pt t1 = rs.CurveClosestPoint(crvId, pts[1]) #get tangency at that pt vectorTanMidPt = rs.CurveCurvature(crvId, t1)[1] #get cross product between vectorTanMidPt and a coordinate vectorPerp = rs.VectorCrossProduct(rs.CurveCurvature(crvId, t1)[1], (0,0,1)) #Unitize that vector vectorPerp = rs.VectorUnitize(vectorPerp) #take the length of the segment, divide it by 4 length = rs.CurveLength(crvId)/4 #take that length value and scale the unitized vector by that value vectorPerp = rs.VectorScale(vectorPerp, length) #add a point at that vector, call it endPt endPt = rs.PointAdd(pts[1], vectorPerp) #draw a line from the middle pt of the segment pts[1] to the end pt rs.AddLine(pts[1], endPt) #create a vector from the endPt to the starting pt of the segment vecBisectorPt = rs.VectorCreate(endPt, pts[0]) #get the mid pt of that vector vecBisectorPt = rs.VectorScale(vecBisectorPt, 0.5) #add a point there BisectorPt = rs.PointAdd(pts[0], vecBisectorPt) #draw that point rs.AddPoint(BisectorPt) #store the starting pt, midpoint of the vector and end pt in a tuple crvPts = [pts[0], BisectorPt, endPt] #draw a curve using the values from the tuple above, using vectorTanStart tangency at the beginning of the curve and vectorTanMidPt tangency at the end firstCurveId = rs.AddInterpCurve(crvPts, 3, 0, vectorTanStart, vectorTanMidPt) #pts[2] # get the last pt on the segment t2 = rs.CurveClosestPoint(crvId, pts[2]) #get tangency at that pt vectorTanEnd = rs.CurveCurvature(crvId, t2)[1] #create a vector from endPt to pts[2] vecMidPt = rs.VectorCreate(pts[2], endPt) #get mid pt of that vector vecMidPt = rs.VectorScale(vecMidPt, 0.5) #mark a point there BisectorPt = rs.PointAdd(pts[2], -vecMidPt) #draw that pt

Recursion is a special case of repetition where a function calls itself for the next repetition. It is often used to model plant growth.

Codelab Essay

import rhinoscriptsyntax as rs “”” Recursive function. Iterating through curves

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segment 0 rs.AddPoint(BisectorPt) #store values for a curve crvPts = [endPt, BisectorPt , pts[2]] #use those values to draw a curve, passing tangency information secondCurveId = rs.AddInterpCurve(crvPts, 3, 0, vectorTanMidPt, vectorTanEnd) #join the curves curvesToJoin = firstCurveId, secondCurveId totalCurveId = rs.JoinCurves(curvesToJoin, True) return totalCurveId[0] #Main function def Main(): crvId = rs.GetObject(“select curve “) numCurves = rs.GetInteger(“select number of divisions “, 3)#typing a number CurveRecursion(crvId, numCurves) #call Main function

pt[1] pt[0]

curveId is divided into two segments.to get the vector for the starting pt of the curve, pt[0] is given the name t0. Tangent of the starting point is obtained by evaluating the curve at pt[0] using rs.curveCurvature, 3D vector for that point is returned.

pt[1]

Main()

pt[0]

Codelab Essay

pt[2]

pt[2]

vectorPerp

in order to get the tangent for pt[1] , information about curve at pt[1] is extracted and placed under the name t1. Tangent at that point is called vectorTanMidPt. then vector cross product is obtained (called vectorPerp) by multiplying vectorTanMidPt and coordinates (0,0,1).Results in a 3Dvector. That vector is unitized.

Visual Explanation of the script

original rhino curve crvId

108 number of segments = 3

crvId length divided by 4

pt[1]

pt[0]

vectorPerp * length

vectorPerp endPt

original rhino curve segment 0

segment 1

segment 2

to get the length of the mid point, you need to take the length of the segment (crvId) and divide it by 4, call that length. then scale the unitized vectorPerp by the length. Draw a point at the end called endPt.

pt[1]

original rhino curve segment 0

segment 1

check length

pt[2]

pt[0]

pt[2]

BisectorPt vecBisectorPt endPt

segment 2

to get the reference for the curve to draw it is necessary to get a vector between endPt and pt[0]. Then by scaling it 0,5 obtain the mid point. Add it, and draw it under the name BisectorPt. Store this information in a tuple called crvPts.


pt[2]

pt[1] pt[0]

Bisec

segment 0

pt[2]

pt[0]

torPt endPt

firstCurveId use the information about the three points stored in crvPts to draw an interpolate curve from pt[0], through BisectorPt, to endPt. Passing the tangency condition at the beginning of the curve (vectorTanStart) and at the end of the curve (vectorTanMidPt).

pt[2] Pt r cto t se Bi idP cM e v endPt

pt[0]

Bise

ctorP

t

firstCurveId

draw an interpolate curve passing through crvPts, using vectorTanMidPt tangency at the beginning of the curve and vectorTanEnd tangency information at the end. now repeat similar step to get the other half of the curve. get the tangency information from pt[2], store it in vectorTanEnd. then get the vector between endPt and pt[2], and draw a point at half vecMidPt, call it BisectorPt. store point information about endPt, BisectorPt and pt[2] in a tuple called crvPts.

pt[2]

pt[0]

firstCurveId

secondCurveId

firstCurveId join firstCurveId and secondCurveId. Call it totalCurveId.

Codelab Essay

pt[1]

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Data Scapes

Codelab Research

In this studio our goal was to explore the imperceivable. Human visual electromagnetic range is narrow and there are wavelengths that we cannot see with our eyes.

We are interested in collecting data about WIFI on our site. The site for data collection and the project was the patio of Elisava School of Design and Engineering. It stays open from 7 am

to 10 pm. It is mainly used by students to take breaks. The project was completed during the months of March to June 2013.

Data Scapes The project was completed during the months of March to June 2013. Team members - Seiichi Suzuki (Ecuador/ Japan) Ives Eja Enriquez Silver (Puerto Rico) and Greta Babarskaite (Lithuania).

Right Google image of the patio as seen from above.

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emitter

receiver

isp

modem

router

internet service provider

translates voltages into frequencies,classified by the amount of data it can send.

converts signal from modem & directs traffic

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+ penetrates through walls - same as bluetooth, cell phones, microwaves

WIFI

2.4 GHz

wireless adapter

motherboard

hardware that communicates with router

receives information in 0s & 1s

5 GHz

+ does not get interference from household appliances - shorter wavelength

Wifi stands for wireless fidelity. Wireless signals are sent to the receiver as a frequency. That same frequency is shared with microwaves.


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Method of Data Collection

We placed a physical grid on the patio and by walking around the patio we collected data with inSSider software twice a day.


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list of networks within range

Data rate how fast the bits travel Channel which range the router is emitting Channel 1 2.412 Mhz Channel 2 2.417 Mhz Channel 3 2.422 Mhz

Signal strength unit : dBm [measured power relative to one militwatt]

Time hour when the data was collected

the lower the value the better the signal

Channel 3 2.427 Mhz

Data Collection

the data collected from inSSider is exported and relevant information is extracted. We get information about all the routers that reach the patio, including the neighboring one. In fact sometimes there are more routers covering the patio that are not part of the Elisava network, which causes conflicts in the school network.


Codelab Research

115 grid coordinates

number of networks

signal strength [negative values]

From different instances of data collection we get some averages from different locations of data collection that we import into excel.

speed


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Physical Router Location

the results that we get with the digital data collection are influenced in part by the distance of each collection point from the routers.


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the closer you are to the router the stronger the signal. This means that there are some routers that have more influence on the patio.

However according to the results of the data collection all the signals reach the patio, therefore there is in general a lot of interference.


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step 1

step 2

step 3

step 4

Data Scape For the basic data visualization we were interested in representing signal strength in each data collection point and then show the effect that the distance to the router has.

Schematic explanation of the RhinoPython Script Step 1 - identify different router that can be accessed from the data collection point. Step 2 - identify vector to each router. Unitize that vector. Multiply by a coefficient of the distance. Step 3 - get the maximum and minimum average signal strength values in the patio. remap those values anywhere from 0 - 3 (height of our choice) in Z direction. Step 4 - the resulting vector between the one pulled by the router and the new z vector is drawn.


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Basic data visualization

Applying the logic of the script described on the left page we get this surface representing direct visualization of the signal strength in response to the emmiter. We can deduce from this diagram that most of signal comes from the front of the building, because the nose of the shape floats outside of the patio.


Codelab Research

import rhinoscriptsyntax as rs import xlrd

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class DataPoints: def __init__(self) position = rs.OpenFileName(“Open Data File”, “(*.xls)|*. xls||”) Excel = xlrd.open_workbook(position)# Values = Excel.sheets()[0] Data_Rows = Values.nrows Data_Cols = Values.ncols self.Pts = [] self.data = [] for i in range (1,Data_Rows,1): D = Values.row_values(i) x = Values.row_values(i)[0] y = Values.row_values(i)[1] z = Values.row_values(i)[2]#2 self.Pts.append((x,y,z)) self.data.append(D[3:8]) def Data(self): return self.data def Points(self): return self.Pts def DataVal(self): pt = self.Pts Num = len(pt) color=(0,0,0) size = 1 #1 self.ValueOption = rs.GetInteger(“Pick Data: 0_Number of Users , 1_Total Networks , 2_Elisava Networks , 3_Signal Average , 4_Speed , 5_users 6_Speed Average”,0,0,6) #values = self.Data[ for i in range(Num): line = rs.AddLine((pt[i][0]-size, pt[i][1], pt[i][2]), (pt[i] [0]+size, pt[i][1], pt[i][2])) rs.ObjectColor(line, color) line = rs.AddLine((pt[i][0], pt[i][1]-size, pt[i][2]), (pt[i] [0], pt[i][1]+size, pt[i][2])) rs.ObjectColor(line, color) line = rs.AddLine((pt[i][0], pt[i][1], pt[i][2]-size), (pt[i]

[0], pt[i][1], pt[i][2]+size)) rs.ObjectColor(line, color) for i in range (Num): text = self.data[i][self.ValueOption] Data_Value = rs.AddText(str(text), pt[i], 0.2) color = (0,0,0) rs.ObjectColor(Data_Value, color) def Surface(self): pt = self.Pts pts = [] for i in range (len(pt)): val = self.data[i][self.ValueOption] pts.append((pt[i][0],pt[i][1],val) self.srf = rs.AddSrfPtGrid((3, 3) , pts) #5,7 V1 = rs.SurfaceEditPoints(self.srf,False)[0] vector = rs.VectorCreate(pt[0],V1) #self.srf = rs.MoveObject(self.srf,vector) return self.srf def Contours(self): bBox = rs.BoundingBox(self.srf) contour = rs.AddSrfContourCrvs(self.srf, (bBox[0], bBox[4]), 0.2) for i in range(len(contour)): pt = rs.CurveStartPoint(contour[i]) val = i*2 #2 if val > 255: val = 255 color = ( 180-val/2,val/8, val) rs.ObjectColor(contour[i], color) return contour

def Main(): t = DataPoints()# t.DataVal() t.Surface() t.Contours() Main()

PythonScript the script takes information from the excel sheet, assigns it to each data collection point and then performs the actions described in the diagrams before


Negative Field The same data points are projected to 3 meter height. That is the height of our choice.

Codelab Research

Positive field the length of the vector is color coded - blue are closest to the router, while the red ones are furthest away.

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Negative Field From those green 3m points new vectors are drawn that are attracted to the end points of the positive side.

Generating a vector field

Each vector is attracted by the closest router and then scaled by the signal strength. They self-organize into clusters based on the proximity to the router.


Codelab Research

ective persp

122

t op

w vie

closest router section

blue vectors: closest to router

Data Scape wifi signal saturation

red vectors: far away from router

green vectors: closer to router

Vectors are attracted by the closest router and then scaled by the signal strength. Due to this vectors self-organize into clusters and leave an area of conflict in between them.


Codelab Research

Cluster 63.7 % number of vectors - 431

Cluster 8.7 % number of vectors - 59

123 Conflict zone area farthest from the routers

Cluster 9.0% number of vectors - 61

* resolution grid 25 by 25

This is the top view of the patio with the boundaries of the patio in place. We can see five significant clusters. Clusters are areas of intensity generated by the routerâ&#x20AC;&#x2122;s signal. They represent places where signal is strongest, however inside each cluster there is also a gradient of intensity - the bluer the closer we are to the router, the stronger the signal.

Cluster 10.9 % number of vectors - 74

Cluster 7.7 % number of vectors - 51


grid 10 x 08

grid 20 x 18

grid 40 x 30

Resolution study

Changing the resolution of the grid adds a higher level of detail. The resolution simply means the number of data collection points on the patio.

Codelab Research

grid 08 x 06

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Digital Shelter

The goal is to create interstitial connectivity spaces that allow students to move from space to space depending on their activity needs. Moving from highest level of connectivity spaces where the connection is at its best towards a level of no connectivity or Digital Shelter. With the data scape produced we were able to start extracting information that is most relevant for the project. We went through a number of

studies. Those can be categorized into 2 parts - path study and cluster study. Some of the trials are shows in the following pages. We interpreted WIFI signal as showing activity of the students at the school. Depending on how many devices you might use some activities are more digitally active than others. This can show how connected you want to be. interaction how likely you are to use a device that connects to the wifi

activities daily activities in the patio

conclusions how connected are you

studying

99%

chatting

66%

reading

66%

smoking

33%

drinking

33%

eating

33%

sleeping

0%

Concept: Gradient of connectivity and digital shelter Data Scape: Wifi signal saturation Argument: Patio is a place for relaxation

Codelab Application

Digital Shelter is a space where you can disconnect from the constant connectivity and take a break.

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Codelab Application

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Investigation I - Cluster Study Since the path is an area that is furthest away from all the routers, then the clusters are areas of intensity generated by the routerâ&#x20AC;&#x2122;s signal. The challenge here is to figure out how to handle the amount of data and turn it into information that would be relevant. In some of these examples we are dividing vectors into points and joining them, in others we are taking them as zones. Finally the logic that we found was to eliminate certain vectors based on their proximity to one another.

Cluster study Clusters are areas of intensity generated by the routersâ&#x20AC;&#x2122; signal


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Codelab Application


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1. The script searches for the largest cluster. 2. It takes the curves that are on the edge 3. You take 1 curve as an example. 4. It searches in 3 - 3.25 meter radius, as illustrated with the green circle. 5. It picks vectors that are inside that search area (the green area). 6. Some vectors, within a certain distance, join together into one node.

Structural logic

Eliminating some vectors based on their proximity to the router means that we take areas that are closest to the router as the ones with the most harm.


6

2 7

3 8

4

9

5

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1

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Structural Logic Trials

By manipulating some variables, such as the number of vectors in one trunk and the proximity of that trunk to others we can get different spatial configurations and densities.


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Codelab Application


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17a.7 3.7

1.9

1.5

4.4

2.5 3.58 2.26

5.4

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1.8 4.8

2.69

1.73

3.2 15.26

17.7

Areas of Interstitial Spaces

Depending on the size some areas have a weaker signal than other ones.

1.6 1.5 1.14 16.6


Codelab Application

16.54 1.99 1.19 1.23

10

30.78

133

3.9 9.5 16.54

21


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Investigation II - Path Conflict study

Codelab Application

The path is an area that is furthest away from all the routers. Above we see changes in the areas of conflict based on which routers are switched on. The one that we are using has all the routers in the school switched on.

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The argument is that a shelter is necessary from the exposure to frequencies. Best place for it is where there is no signal. Since the goal of a school WIFI network is to cover every single corner there are no gaps in it, therefore there are no natural places of â&#x20AC;&#x153;no-signalâ&#x20AC;?. Therefore we need to create these interventions ourselves. Our proposal is to consider areas that are far away from all the routers to be zones of protection. By enclosing those areas we get a place that signals cannot reach, that includes both mobile cell signals, WIFI and 3G. This becomes a shelter from the digital world.

Above Vector fields generated by taking into account the location of the routers and the signal strength. Each example is an instance of the changes seen when some routers are switched off or on.


join and others stay open. Then they are reparametrized (sharp angles disappear) and then curve organization runs that depending on some distance between these curves they are drawn to each other. Codelab Application

Explanation of the script The area that has least exposure to the wifi is the conflict zone. Thus we take a line of vectors that enclose that zone. Each vector is divided the same number of time. Then depending on the distance between vectors, some

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The script was written in RhinoPython.


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Path Conflict study

We take the vectors that enclose enclose the conflict path, reparametrize the vector and If they are a certain distance apart we join them. This gives us a tunnel-like enclosing that we would consider the shelter zone.


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Curve organization, the curve-like connections, respond to their proximity to other curves.


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Digital Fabrication

Codelab Digital Fabrication

Fabrication is an integral part of the parametric design process. At the university workshop I was introduced to a number of tools available from the manual ones to the digital ones.

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In the process of these projectsâ&#x20AC;&#x2122; development fabrication serves an important part due to the fact that it is crucial in testing the ideas. Like Gaudi showed, rigorous empirical experiments help derive solutions to design problems. We do not address design in the final stage as post design optimization, but we keep testing it throughout each step of the process. Three main available machines to be used were a 3 axis CNC router, laser cutter and a 3D printer (rapid prototyping). I will begin by exploring each one of the options finishing with a CNC guide, which serves as a cheat-sheet to operate a specific CNC machine. Laser cutting is a precise CNC process that can be used to cut, etch, engrave and mark a variety of sheet materials including metal, plastic, wood, textiles, glass, ceramic and leather. It focuses thermal energy on a spot of 0.1 mm to 1 mm wide to melt (or vaporize) the material. It operates on high speeds, has precise tolerances and produces accurate parts with an edge finish. In design it cuts most materials (especially thermoplastics) so well that they require no finishing. It is generally used to make small intricate details and can be used to raster en-

grave logos, pictures and fonts at different depths - most common uses in graphic types of design. Design considerations. The laser follows a series of lines from point to point. A vector-based file (usually converted from a CAD drawing) is loaded onto the machine. It is divided into layers, each layer specifies a different depth of the cut. It is important to join the lines in each layer so the laser cuts on a continuous path and remove any duplicates. Compatible materials. Can be used to cut a multitude of materials including timber, veneers, paper and card, synthetic marble, flexible magnets, textiles and fleeces, rubber and certain glasses and ceramics. Based on the type of laser cutter that you have available you must check the plastics that it can cut. Rapid prototyping is used to construct geometries by heating together very fine layer of powder or liquid. The process starts with a CAD model sliced into sections. Each of that section is mapped and fused together to produce the final geometry. There are 3 main processes: Stereolitography (SLA), Selective laser sintering (SLS) and direct metal laser sintering (DMLS). Generally rapid prototyping is used to produce full prototypes, but


CNC Milling. Using CNC machining CAD model data can be transferred directly onto the work-piece. It can mill, drill, engrave and cut out. And can produce a precise and high quality product. The number of axes that the CNC machine operates determines the geometries it can cut. A 5-axis has a wider range of motion than a 2-axis one. At ADDA we used CNC machin-

Source: “Manufacturing processes for Design Professional” by Rob Thomson (2007). “Así se hace : técnicas de fabricación para diseño de producto” by Chris Lefteri (2006)

ing for prototypes, whether making molds or scale models directly. These applications are only a small part of the ones outside of academic environment. Almost every factory is equipped with some form of CNC machinery. It is used for primary operations such as production of prototypes,toolmaking and carving wood and it is often utilized for secondary operations and post-forming, including removal of excess material and holes. Depending on the settings it may sometimes leave marks of the milling process. That can be reduced or eliminated by sanding. Almost any material can be CNC machined, including plastic, metal, wood, glass, ceramic and composites. Many different tools are used in the cutting process, including cutters (side or face), slot drills (cutting action along the shaft as well as the tip for slotting and profiling), conical, profile, dovetail and flute drills, and ball nose cutters (with a dome head, which is ideal for 3D curved surfaces and hollowing out). In most modern CNC machines tool changes are automated. The 3 axis CNC machine has a tool carousel with an array of cutting tools and drills, while the 5 axis machine uses 1 tool. That saves a considerable amount of time during the process. However at Elisava we changed tools manually.

Codelab Digital Fabrication

at the master’s it was never used to print out a design without analyzing it geometrically, but was used to print out joints or specific pieces. Conventional CNC machining operations remove material , whereas rapid prototyping builds only what is necessary. It produces accurate parts, but it is an energy intensive process. In terms of quality one can see subtle edges result of the layering. Therefore it requires smoothing when it comes out from the machine. The orientation of the parts can affect its mechanical properties. Design considerations. Depending on how the 3D printer works one may need to consider how the 3D model is built, sometimes it needs supports in some places to make sure that it is built correctly (they get removed afterwards). Other times the printer adds the necessary support itself. Nowadays the most common design restrictions is the size of the machine - usually not bigger than 400 x 400 x 400 mm.

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Advanced Design & Digital Architecture. Elisava. 2012-2013.

Responsive Design  

MA Thesis for Advanced Design and Digital Architecture

Responsive Design  

MA Thesis for Advanced Design and Digital Architecture

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