Kinetic Architecture by cpr512

Kin netic Arch hitectture Mode eling de esign an nd beha avior Carlo Roussee euw

Thesis T vooorgedragen n tot het behale en van de graad van Master in de e ingenieurrswetensch happen: Arch hitectuur Bouw wtechnisch he Optie Pro omotor: P Prof. Vande e Moere Ass sessor: Prof. Van Broeck Begelleiders: Prof. Bo oeykens

Academi A ejaar 2010 – 201 11

Masterr in de in ngenieurrswetens schappe en: archi tectuur

Kin netic Arch hitectture Mode eling de esign an nd beha avior Carlo Roussee euw

Academi A ejaar 2010 – 201 11

© Copyright by K.U.Leuven Zonder voorafgaande schriftelijke toestemming van zowel de promotor(en) als de auteur(s) is overnemen, kopiëren, gebruiken of realiseren van deze uitgave of gedeelten ervan verboden. Voor aanvragen tot of informatie i.v.m. het overnemen en/of gebruik en/of realisatie van gedeelten uit deze publicatie, wend u tot de K.U.Leuven, Faculteit Ingenieurswetenschappen – Kasteelpark Arenberg 1, B‐3001 Heverlee (België). Telefoon +32‐16‐32 13 50 & Fax. +32‐16‐32 19 88. Voorafgaande schriftelijke toestemming van de promotor(en) is eveneens vereist voor het aanwenden van de in dit afstudeerwerk beschreven (originele) methoden, producten, schakelingen en programma’s voor industrieel of commercieel nut en voor de inzending van deze publicatie ter deelname aan wetenschappelijke prijzen of wedstrijden. © Copyright by K.U.Leuven Without written permission of the promotors and the authors it is forbidden to reproduce or adapt in any form or by any means any part of this publication. Requests for obtaining the right to reproduce or utilize parts of this publication should be addressed to K.U.Leuven, Faculty of Engineering – Kasteelpark Arenberg 1, B‐3001 Heverlee (België). Telefoon +32‐16‐32 13 50 & Fax. +32‐16‐32 19 88. A written permission of the promotor is also required to use the methods, products, schematics and programs described in this work for industrial or commercial use, and for submitting this publication in scientific contests.

Preface The idea for this research came to me when I was first introduced to the notion of Interactive Architecture: a new kind of architecture, previously unknown to me, but which grabbed my attention. Various projects in the current landscape intrigued me and caused me to dive deeper into this new and upcoming field. The main focus for me was to gain insights, information and to be able to pass this on to others too. This focus sometimes led to quantity over quality, which I am not ashamed to say. It is the intent of this research to draw the bigger picture and introduce this new skillset to all who want to know. It was never the intention to lure people into a narrow mindset, only to introduce them to this new sandbox where they can play themselves. Another difficulty for me personally was the absence of previous local research and the possible prejudices that others might have towards this research. This research did not take form as fast as I would have liked and was not easy to complete but the supervising professors were always positive and guiding, which allowed me to keep on going. A thanks goes out to people who inspired me, family and friends who supported me and helping hands that guided this research into the right direction. Carlo Rousseeuw

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Table of contents Preface .................................................................................................................................................... iii Table of contents .................................................................................................................................... iv Abstract ................................................................................................................................................. vii List of Figures ....................................................................................................................................... viii List of Tables ........................................................................................................................................ xiv Nomenclature ........................................................................................................................................ xv Chapter 1: Introduction ......................................................................................................................... 1 Interactive Architecture ................................................................................................................ 1 Physical Counterpart ..................................................................................................................... 4 Intelligence Counterpart ............................................................................................................... 5 Practical Knowledge ...................................................................................................................... 7 Motivation ...................................................................................................................................... 8 Objectives ....................................................................................................................................... 9 Significance ..................................................................................................................................... 9 Chapter 2: Background ........................................................................................................................ 11 2.1 Earlier Works ............................................................................................................................. 11 2.2 Literature study ......................................................................................................................... 12 2.2.1 Timeline ............................................................................................................................... 15 2.2.2 Project Location .................................................................................................................. 16 2.2.3 Project Mechanism ............................................................................................................. 16 2.2.4 Project Typologies .............................................................................................................. 18 2.2.5 Project Application Kinetics............................................................................................... 18 2.2.6 Project Timespan ................................................................................................................ 19 2.2.7 Project Structural behavior ................................................................................................ 20 2.2.8 Project Intelligence ............................................................................................................. 21 2.2.9 Project Sensor values ......................................................................................................... 21

2.2.10 Web‐Based Literature ...................................................................................................... 22 Chapter 3: Methodology & Results ..................................................................................................... 23 3.0 Methodology .............................................................................................................................. 23 3.0.1 The Simulation Software, Grasshopper ............................................................................ 23 3.0.2 The microcontroller, Arduino ............................................................................................ 26 3.1 Simulating design ...................................................................................................................... 28 3.1.1 Simulations, Case Studies ................................................................................................... 28 3.1.2 Numerical Validation .......................................................................................................... 41 3.1.2.1 Default Scenario Results ................................................................................................. 42 3.1.2.2 Actuated Scenario Results............................................................................................... 43 3.2 Simulating behavior .................................................................................................................. 44 3.2.1 The Simulation Software .................................................................................................... 44 3.2.2 Linking Data Methods ........................................................................................................ 45 3.2.3 Simulations .......................................................................................................................... 46 3.2.4 Emotive behavior ................................................................................................................ 53 3.3 Design Issues .............................................................................................................................. 55 3.3.1 Joints .................................................................................................................................... 56 3.3.2.1 2D Joint ............................................................................................................................. 56 3.3.2.2 3D Joint ............................................................................................................................. 58 3.2.1 Members .............................................................................................................................. 61 3.3.2 Cladding ............................................................................................................................... 62 3.3.3 Actuator design ................................................................................................................... 67 3.3.5 Prototype Design ................................................................................................................ 74 3.3.5.1 Introduction ..................................................................................................................... 74 Flexible Skin ................................................................................................................................. 74 Biomimicry ................................................................................................................................... 75 3.3.5.2 Results .............................................................................................................................. 76 Design ........................................................................................................................................... 76 Polyp ............................................................................................................................................. 78 Truss ............................................................................................................................................. 80 Cladding ........................................................................................................................................ 83 Behavior ....................................................................................................................................... 86 Chapter 4: Evaluation & Discussion ................................................................................................... 90 4.1 Evaluation & Discussion Simulating Design ............................................................................ 90

4.1.1 Simulation Case Studies ..................................................................................................... 90 4.1.2 Numerical validation .......................................................................................................... 92 4.2 Simulating behavior .................................................................................................................. 94 4.3 Design Issues .............................................................................................................................. 96 4.3.1 Joints .................................................................................................................................... 96 4.3.2.1 2D Joint ............................................................................................................................. 96 4.3.2.2 3D Joint ............................................................................................................................. 97 4.3.3 Members .............................................................................................................................. 98 4.3.4 Cladding ............................................................................................................................... 99 4.3.5 Actuator design ................................................................................................................. 100 4.3.6 Prototype Design .............................................................................................................. 102 Design & Polyp ........................................................................................................................... 102 Truss & Cladding ........................................................................................................................ 104 Behavior ..................................................................................................................................... 106 Chapter 5: Conclusion ....................................................................................................................... 108 5.1 Simulating Design ................................................................................................................ 108 5.2 Simulating Behavior. ........................................................................................................... 110 5.3 Practical Issues .................................................................................................................... 111 5.3.2 Cladding ............................................................................................................................. 112 5.3.3 Actuator Design ................................................................................................................ 113 5.3.4 Prototype ........................................................................................................................... 115 Appendices ......................................................................................................................................... 118 Appendix A ..................................................................................................................................... 119 Appendix B ..................................................................................................................................... 123 Bibliography ....................................................................................................................................... 127 Fiche Masterproef .......................................................................................................................... 131

Abstract The way we use and experience objects in our daily lives is constantly being improved with increasing user‐interactivity. From our cars which are filled with sensors to enrich our driving experience to the automated shading of our windows which disappears when we need to get out of bed in the morning. Architecture today on the other hand is static, its structural form does not interact with its users or its changing environmental factors. Instead of shielding the inhabitants from these factors, these factors can be responded to and interacted with to change the inhabitant’s perception of this new space, Interactive Architecture. In the design of interactive architecture with structural kinetic changes, Kinetic Architecture, the simulation of a structure and its behavior plays a valuable role in its overall design and production. Being able to connect a wide range of sensor data with this design‐software we cross the bridge necessary for completely simulating interactive architecture, which in turn has an effect on the final design. Recent developments and community efforts in plugins for drawing software like Grasshopper for Rhinoceros have given us these abilities. Every project is unique by its own context and usage and therefore unique by its means to interact. This thesis simulates different existing structures in the current landscapes and tests the scope of current simulation packages and their use to designers with regards to Kinetic Architecture. Also the intelligence which controls this Kinetic Architecture and the different kinds of data streams are addressed together in the context of the simulation software. Besides the research in terms of simulation, this thesis also discusses practical issues of Kinetic Structures in a general way before building a working prototype. This research will act as a catalyst to provide architects with the necessary skillset to develop and design interactive architecture but also to provide a mutual goal for other disciplines like robotics and material engineers to form and research different end products with enhanced user interactivity which could be used in this new breed of Interactive Architecture.

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List of Figures

Figure 1: Burble at the Singapore Biennale (Haque 2006) ............................................................................... 2 Figure 2: Interactive Wall (Festo Corporate 2009) .......................................................................................... 3 Figure 3: Tesselate (Lab[au] 2010) ............................................................................................................................ 3 Figure 4: Fabric Dome (Hoberman 1997) ............................................................................................................... 4 Figure 5: Pneumatic Muscle ........................................................................................................................................... 4 Figure 6: Visualizing Wifi Strength, Immaterials (Arnall et al. 2011) .......................................................... 5 Figure 7: Pixelskin 2.0 (Orangevoid n.d.) ................................................................................................................. 5 Figure 8: Flock of birds (National Geographic n.d.) ............................................................................................. 6 Figure 9: High Tech Teamwork of swarm robots (National Geographic n.d.) .......................................... 6 Figure 10: Ball Joint, 3D‐Print ....................................................................................................................................... 7 Figure 11: Stiff Cladding Connection ......................................................................................................................... 7 Figure 12: Ernsting Warehouse Gate, Santiago Calatrava, 1983(Tzonis & Lefaivre 1997) ............. 11 Figure 13: Scale Model, Santiago Calatrava (Tzonis & Lefaivre 1997) ..................................................... 11 Figure 14: Interactive Architecture Categorization + Dissertation ............................................................ 14 Figure 15: Time versus Book Contents .................................................................................................................. 15 Figure 16: Location versus Book .............................................................................................................................. 16 Figure 17: Mechanism versus Book ........................................................................................................................ 17 Figure 18: Typology Categorization ........................................................................................................................ 18 Figure 19: Application Categorization ................................................................................................................... 19 Figure 20: Load Bearing categorization ................................................................................................................ 20 Figure 21: Intelligence Categorization ................................................................................................................... 21 Figure 22: Sensor Values Categorization .............................................................................................................. 21 Figure 23: Interactive Architecture dot org, Wordle (Glynn 2005) .......................................................... 22

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Figure 24: Actuators, Spring Implementation ..................................................................................................... 24 Figure 25: Truss member, Spring Implementation .......................................................................................... 24 Figure 26: Kangaroo Components in Grasshopper ........................................................................................... 24 Figure 27: Grasshopper Environment .................................................................................................................... 25 Figure 28: Testing the Arduino, LED‐bar .............................................................................................................. 26 Figure 29: Scale model Type 3 (D’Estree Sterk 2003) ..................................................................................... 28 Figure 30: Simulation Actuated Tensegrity Type 1 .......................................................................................... 29 Figure 31: SimulationActuated Tensegrity Type 2 ........................................................................................... 30 Figure 32: Simulation Actuated Tensegrity Type 3 .......................................................................................... 30 Figure 33: WhoWhatWhenAir, Flexible Tower (Kilian et al. 2006) ........................................................... 31 Figure 34: Muscle Tower II, Hyberbody (Oosterhuis 2000) ......................................................................... 31 Figure 35: Simulation Flexible Tower .................................................................................................................... 32 Figure 36: TESSEL (Lab[au] 2010) .......................................................................................................................... 33 Figure 37: Robotic Membrane (Orangevoid n.d.) .............................................................................................. 33 Figure 38: Simulation Robotic Membrane ............................................................................................................ 34 Figure 39: Excerpt from dissertation, Responsive Actuated Truss (Merali & Long 2009) .............. 35 Figure 40: Simulation Actuated Responsive Truss ........................................................................................... 36 Figure 41: Simulation Kinetic Circle ........................................................................................................................ 37 Figure 42: Expanding Geodesic Dome (Hoberman 1997) ............................................................................. 38 Figure 43: Strata Module(Adaptive Building Initiative 2006) ..................................................................... 38 Figure 44: Simulation of the Expanding Geodesic Dome ................................................................................ 39 Figure 45: Adding a color scale in Grasshopper ................................................................................................. 41 Figure 46: Simulation Grashopper, 5kN, Not Actuated, Deformation Scale 1:1 .................................... 42 Figure 47: Simulation ANSYS, 5kN, Not Actuated, Deformation Scale 1:1 .............................................. 42 Figure 48: Simulation Grasshopper, 0kN, Actuated, Deformation Scale 1:1 .......................................... 43 Figure 49: Simulation ANSYS, 0kN, Actuated, Deformation Scale 1:1 ....................................................... 43 Figure 50: Arduino Send/Receive implementation in Grasshopper ......................................................... 44 Figure 51: Manipulating and visualizing Sensor Data in Grasshopper ..................................................... 45

Figure 52: Optimization, Kinetic Arch towards point ...................................................................................... 46 Figure 53: IR sensor connected to the Arduino .................................................................................................. 47 Figure 54: Manipulating & visualizing Sensor Data in Grasshopper ......................................................... 47 Figure 55: Push sensitive sensor connected to the Arduino ......................................................................... 48 Figure 56: Implementing Sensor Data .................................................................................................................... 48 Figure 57: Optimization, Kinetic Arch minimizing stresses .......................................................................... 49 Figure 58: Pachube receive implementation in Grasshopper ...................................................................... 51 Figure 59: Pachube, Live sensor streaming and stream information ....................................................... 51 Figure 60: Fiducial implementation in Grasshopper ....................................................................................... 52 Figure 61: Sensors .......................................................................................................................................................... 53 Figure 62: Grasshopper/Kinect Sensor (Andy Payne et al. 2010) .............................................................. 53 Figure 63: Dune 4.0 Maastunnel(Roosegaarde 2011) ..................................................................................... 54 Figure 64: Laser‐cutting and engraving a sheet of MDF ................................................................................. 55 Figure 65: 2D Turning Joint, with eccentricity ................................................................................................... 56 Figure 66: 2D Turning Joint, without eccentricity ............................................................................................. 56 Figure 67: 2D Joint Unstable ...................................................................................................................................... 57 Figure 68: Intersecting 2D joints, Snap‐Fit ........................................................................................................... 57 Figure 69: Parametrical Model Universal Joint 2 ............................................................................................... 58 Figure 70: 3D‐print Universal Joint 2 ..................................................................................................................... 58 Figure 71: Cardboard Space frame; Ring Pass, Delft (Octatube 2010) ..................................................... 59 Figure 72: Parametrical Ball Joint ............................................................................................................................ 59 Figure 73: Section Parametrical Ball Joint ............................................................................................................ 60 Figure74: 3D Printed Ball Joint ................................................................................................................................. 60 Figure 75: 3D printed Ball Joint, Section ............................................................................................................... 60 Figure 76: Truss Member ............................................................................................................................................ 61 Figure 77: Truss Member ............................................................................................................................................ 61 Figure 78: Textile membrane, Unstretched ......................................................................................................... 62 Figure 79: Textile membrane, Stretched ............................................................................................................... 62

Figure 80: Kinetic Box, Default Scenario ............................................................................................................... 64 Figure 81: Kinetic Box, Scenario 1 ........................................................................................................................... 64 Figure 82: Kinetic Box, Scenario 2 ........................................................................................................................... 64 Figure 83: Expansion joint Wooden cladding ..................................................................................................... 65 Figure 84: Ball joint (Kejia Industry n.d.) .............................................................................................................. 65 Figure 85: Living Glass (The Living n.d.) ............................................................................................................... 66 Figure 86: Xeromax Envelope (Future Cities Lab 2010) ................................................................................ 66 Figure 87: Rectangle, Diagonal Actuation ............................................................................................................. 67 Figure 88: Muscle Wire Actuation ............................................................................................................................ 68 Figure 89: Screw Linear Actuator ............................................................................................................................ 69 Figure 90: Crankshaft Linear Actuator .................................................................................................................. 69 Figure 91: Gear‐Pinion Linear Actuator ................................................................................................................ 69 Figure 92: Muscle Project (Festo Corporate 2009)........................................................................................... 70 Figure 93: McKibben Principle (Daerden & Lefeber n.d.) .............................................................................. 70 Figure 94: Test Setup ..................................................................................................................................................... 71 Figure95: McKibben air muscle setup .................................................................................................................... 71 Figure 96: 3/2 Air Valve Festo ................................................................................................................................... 72 Figure 97: Arduino Controller ................................................................................................................................... 72 Figure 98: Elongation/Original Length [%] ......................................................................................................... 73 Figure 99: Underwater Polyps (National Geographic n.d.) ........................................................................... 75 Figure 100: Axonometric View Prototype ............................................................................................................ 76 Figure 101: Prototype, 3D Sketch ............................................................................................................................ 77 Figure 102: Scotch Yoke Mechanism (Mechanisms 101 n.d.) ...................................................................... 78 Figure 103: Polyp Actuation, 3D Sketch ................................................................................................................ 78 Figure 104: Polyp Actuator ......................................................................................................................................... 79 Figure 105: Polyp, Upper node connection .......................................................................................................... 79 Figure 106: 2D Simulation, Design 1 ....................................................................................................................... 80 Figure 107: 3D simulation, Design 1 ....................................................................................................................... 80

Figure 108: 2D simulation, Design 2 ....................................................................................................................... 81 Figure 109: 3D simulation, Design 2 ....................................................................................................................... 82 Figure 110: Truss assembly ........................................................................................................................................ 82 Figure 111: Lasercut Vacuum Forming Molds .................................................................................................... 83 Figure 112: Vacuum Former with mold ................................................................................................................ 84 Figure 113: Vacuum forming result with high mold ........................................................................................ 84 Figure 114: Cladding, Upper View ........................................................................................................................... 85 Figure 115: Cladding, Lower View ........................................................................................................................... 85 Figure 116: Built‐In Opto‐Resistor .......................................................................................................................... 87 Figure 117: Built‐In Piezo Element ......................................................................................................................... 87 Figure 118: Built‐in IR Sensor ................................................................................................................................... 87 Figure 119: Prototype Side‐View ............................................................................................................................. 88 Figuur 120: Prototype Side‐View ............................................................................................................................. 88 Figure 121: Prototype Perspective View ............................................................................................................... 89 Figure 122: Prototype Upper View .......................................................................................................................... 89 Figure 123: Simulation Flexible Tower .................................................................................................................. 91 Figure 124: Simulation of the Expanding Geodesic Dome ............................................................................. 91 Figure 125: Simulation Grasshopper, 0kN, Actuated, Deformation Scale 1:1 ....................................... 93 Figure 126: Simulation ANSYS, 0kN, Actuated, Deformation Scale 1:1 .................................................... 93 Figure 127: Optimizatin, Kinetic arch moving towards points .................................................................... 94 Figure 128: 2D Turning Joint, without eccentricity .......................................................................................... 96 Figure 129: 2D unstable joint .................................................................................................................................... 96 Figure 130: 3D‐print Universal Joint 2 ................................................................................................................... 97 Figure 131: 3D printed Ball Joint, Section ............................................................................................................ 98 Figure 132: Truss Member .......................................................................................................................................... 98 Figure 133: Kinetic Box, Scenario 2 ......................................................................................................................... 99 Figure 134: Expansion joint Wooden cladding ................................................................................................... 99 Figure 135: McKibben air muscle setup ............................................................................................................. 100

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Figure 136: Elongation/Original Length [%] ................................................................................................... 101 Figure 137: Sketches Polyp, Design 1 .................................................................................................................. 102 Figure 138: Polyp Actuator ...................................................................................................................................... 103 Figure 139: Prototype Perspective View ............................................................................................................ 103 Figure 140: Cladding Hinge, Truss member connection ............................................................................. 104 Figure 141: Vacuum Forming results with high mold .................................................................................. 105 Figure 142: Arduino powered by USB and 9V battery ................................................................................. 107 Figure 143: Simulation Grasshopper, 0kN, Actuated, Deformation Scale 1:1 .................................... 109 Figure 144: Simulation ANSYS, 0kN, Actuated, Deformation Scale 1:1 ................................................. 109 Figure 145: Central Intelligence versus Swarm intelligence, Simulation 1 ......................................... 110 Figure 146: 3D printed Multiple member Ball joint ...................................................................................... 111 Figure 147: Kinetic Box, Scenario 2 ...................................................................................................................... 112 Figure 148: Expansion joint Wooden cladding ................................................................................................ 112 Figure 149: Linear actuators, Shrink Rate ......................................................................................................... 113 Figure 150: Air muscle, Elongation rate [%] .................................................................................................... 114 Figure 151: Prototype, Perspective view ........................................................................................................... 115 Figure 152: Prototype Upper View ....................................................................................................................... 116 Figure 153: Prototype Side view ........................................................................................................................... 116 Figure 154: 3D Truss Simulation ........................................................................................................................... 117

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List of Tables

Table 1: Legend Time versus Book Contents ...................................................................................................... 15 Table 2: Legend Books .................................................................................................................................................. 16 Table 3: Error Margin %, Default 5kN Table 4: Error margin %, Default 10 kN ................................................................................................................ 42 Table 5:Error Margin %, 0kN Table 6:Error Margin %, 5kN ..................................................................................................................................... 43 Table 7: Intelligent‐ versus Swarm Behavior ...................................................................................................... 47 Table 8: Comparison Different iteration processes .......................................................................................... 49 Tabel 9: Linear Actuators, Shrink Rate .................................................................................................................. 69 Table 10: Muscle Elongation [%] .............................................................................................................................. 73 Table 11: Polyps Behavioral Scheme ...................................................................................................................... 86 Table 15: Error Margin %, Default 5kN Table 16:Error Margin %, 5kN .................................................................................................................................. 92 Tabel 17: Optimization results versus swarm implementation, Simulation 1 ...................................... 95 Tabel 18: Optimization results, Simulation 2 ...................................................................................................... 95 Tabel 19: Shrink Rates of different actuators................................................................................................... 100 Table 20: Muscle Elongation [%] ........................................................................................................................... 101 Table 21: Error Margin %, Default 5kN Table 22:Error Margin %, 5kN ............................................................................................................................... 109

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Nomenclature IA Interactive Architecture KA Kinetic Architecture FE Finite Elements KDG Kinetic Design Group F Force E Young’s Elasticity modulus x Displacement in x Direction y Displacement in y Direction k (Elasticity) Stiffness GH Grasshopper FF Firefly KG Kangaroo

Chapter 1: Introduction Interactive Architecture Architecture today is monotone and static. Imagine architecture however to be alive, to be able to partake in a discussion with its inhabitants or the environment in which it has been placed. These inhabitants and environmental factors, like sunlight and wind, are dynamic: they are not static or monotone and they deserve to be acknowledged and interacted with. When reacting and interacting with these factors, architecture changes the inhabitant’s perception of space and lets them live in symbiosis with architecture rather than only inhabiting architecture. This new kind of architecture has to be dynamic, responsive and interactive. “One way to begin exploring the dynamics is through rethinking architecture beyond conventional static and single‐function spatial design.”(Fox & Kemp 2009) Let us for example think of a pavilion, a pavilion that can change its shell form to automatically use the best form for minimizing the displacements or stresses in its structure. A pavilion that can brace itself for the incoming impact of an earthquake or a pavilion that breathes, ventilates, and catches renewable resources for its inhabitants and their current activity. Buckminster Fuller even coined this as “Ephemeralization”(Fox & Kemp 2009), being able to build a stronger form with minimal material using active measures, similar to the human body where a fixed amount of muscles and bones can provide various stances for various positions and actions. “Perhaps the most applicable research to draw upon in designing intelligent systems lies in an area of study called active control research, which focuses on the use of active control to modify the structural behavior in a building”(Fox & Kemp 2009)

Usm man Haque,, founder of f Haque Desiign + Research, specializes in the ddesign and ressearch of theese interactive architeccture system ms. Togetherr with his enntourage he dessigned and cconstructed d various intteractive insstallations o on various s cales, including Burb ble, a massiv ve installati on consistin ng of multip ple balloons embedded witth lights and d infrared rreceivers be ing able to rreceive sign nals from a ssimple teleevision rem mote used by y the peoplee who came to see the in nstallation. With rregards to IA A, Usman Haqque states: ““Such system m must utilizee a definition of interaction n as circularr, or they aree merely “rea acting” and n not “interaccting”. As peo ople interact with arch hitecture they ey should nott be thoughtt of as “userss” but instead d as “particip pants”.” (Foxx & Kemp 20 009)

Figu ure 1: Burble at the Singap pore Biennale (Haque 2006 6)

Ressearch invollving IA can n be approacched throug gh different viewpoints,, such as the e socciological asspects, change in social behavior an nd the perce eption of sppace but also o in a m more practiccal way of bu uilding, mod deling and ssimulating IA design to gain practiccal kno owledge. que is an exaample of ressearching so ociological aaspects and d Thee Burble by Usman Haq soccial behavior through IA A. His Burblle and Sky E Ear projects made a varriety of peop ple leavve their hom mes and poiint their teleevision rem mote control in the sky tto interact w with thiss new kind of architecture. Thiis research h however ad ddresses thee more practtical issues such as sim mulating IA, buiilding jointss and buildin ng a prototyype. This is a common rresearch meethod where e buiilding and experimentin ng on a smaall scale gain ns practical insight but is not intrroduced as a social exp periment. Foor example tthe interactive wall creaated by the Fessto Corporattion or the T Tesselate prroject by lab b[au] are both installatiions in a con ntrolled env vironment w with minimaal documenttation involv ving their efffect on sociial inteeraction. The physical architecture can be useed to include or exclude p people from one anotherr, to “T facilitate, d dissipate, or ffocus crowdds of people. In this way, in the realm m of the physsical world, interractive publiic spaces can n have a proffound spacee effect on social intera actions.”(Foxx & Kemp 20 009)

Figu ure 2: Interacttive Wall (Fessto Corporatee 2009)

Figu ure 3: Tesselaate (Lab[au] 20 010)

To guide tthe reader in n this researrch, IA is cutt up into twoo counterpa arts: “The curreent landscape of interacttive landscap pe or interacctive space is is built upon the conveergence of em mbedded com mputation (iintelligence)) and a physsical coun nterpart(kin netics).” (Foxx & Kemp 20 009)

Phyysical Coun nterpart Thee physical counterpart nowadays is that of kinetics. We therefore uti tilize the nam me Kin netic Architeecture (KA) to depict IA A that utilizees kinetics a as a physicaal counterpa art. Kin netic structu ures can be categorized d by their “w ways” and “m means”. (Foxx & Kemp 200 09) The “waays” of a kin netic structu ure can be th he various m methods of sspatial chan nge in b both size an nd shape like e folding, exxpanding orr sliding. The Hobermann dome for exaample can exxpand its sttructure usin ng a scissorr mechanism m and the Errnsting Waarehouse gatte by Santia ago Calatravva opens witth a linkage mechanism m1. Thee “means” o of a kinetic sstructure is formulated as the driviing mechan ism(s) behind thee “ways” of tthe kinetic sstructure. Th hese are alsso named acctuators in th the scope off thiss thesis. Acttuators can be mechaniical, pneumaatically, natu urally, chem mically or maagnetically d driven. The p pneumatic m muscle reseearched in th his thesis is an example e of a pneumaticallly driven acctuator. Botth categoriees are necessary when ttalking abou ut the kinetiic counterpaart. This the esis sim mulates diffeerent kineticc mechanism ms, ways, du uring a case e‐study, to fiind the scop pe of p present toolls but also fa abricates lin near actuato ors to gain insight into the differen nt meeans of kinettic structure es.

Figu ure 4: Fabric D Dome (Hoberman 1997)

Figu ure 5: Pneumaatic Muscle

1 Liinkage Mech hanism: “A sseries of rig id links con nnected with h joints to foorm a closed d chaain.” (Wikipedia 2011a))

Inttelligence C Counterparrt Thee second counterpart o of IA is intellligence under the form of embeddeed com mputation. T The intellige ence of a strructure is th he central nervous systeem that opeerates our K KA. mputation iss like a body y without a bbrain: incapa able “A kinetic envirronment witthout the com of m moving.”(Foxx & Kemp 20 009) mbedded com mputation iss the term tthat depicts the numero ous microcoontrollers orr Em electronic com mponents that are embeedded, impleemented, in n today’s eleectronic o only a coup ple of dediccated functio ons. In IA thhese are devvices and arre able to do miccrocontrolleers that enable the buil ding to receeive, process and act uppon incomin ng datta. Thee intelligencce of IA is de efined as th he programm ming, that under the inffluence of data con ntrols the acctuation of tthe kinetic ccounterpartt. These stre eams of dataa can vary from pragmatiic data to hu umanistic daata. der pragmaatic data fall values such h as the day ylight level, w wind speed or a wide Und varriety of dataa that is tang gible in num mbers. Projeects such as “Painting W Wifi”, which meeasures WIF FI strength in n the field, oor “Pixelskin n” by Orang gevoid, whicch is an inteeractive shaading reacting to dayligght levels, arre examples of using prragmatic datta. otions howeever cannot be measure ed in numbeers. These arre Human behaviior and emo callled humanistic data, wh here pragm matic sensorss are already available oon a wide scaale. Sensors which can a accurately ssense human n movement or emotionn however a are nott yet availab ble on a larg ge scale. Thiss research w will addresss both data ttypes and how to iimplement tthem in the simulation of KA.

Figu ure 6: Visualizzing Wifi Stren ngth, Immateerials (Arnall e et al. 2011)

Figu ure 7: Pixelskiin 2.0 (Orange evoid n.d.)

In tthis research there is a difference b between sw warm intellig gence and ceentral inteelligence. Both of these e are addresssed here an nd compared d to each otther using a bassic numericaal comparisson. Thee term swarrm intelligen nce is used in this thesiis when a sttructure is ccomprised o out of d different cellls. Cells wh hich have theeir own sen nsors but can n also only aactuate theiir ow wn actuators, meaning th heir sensoryy environment is equall to their acttuating envvironment. P Projects succh as the “Piixelskin” sollar shading are comprissed of these e cellls which actt on the specific value ggiven to them m by their o own sensor. Swarm inteelligence is also directly y linked to tthe behavio or science off swarms likke bees, antss and d flocks of b birds. Cen ntral intelliggence is the opposite off swarm inteelligence an nd works muuch like the hum man brain. W When a hairr particle seenses vibrattion our braiin is alertedd which allo ows us to use our o other musclles to act. H ence the sen nsory environment is nnot the same e as tthe actuatin ng environm ment. Physiccally this meeans all of th he sensor daata from the e cellls or even off‐site data can be used d to actuate the entire sstructure ussing a coo ordinated acct. A practical example can be a strructure whe ere minimal stresses are min nimalized fu urther. This structure n not only meeasures the fforce applieed to a node e butt collects thiis data to an nalyze and actuate acco ordingly with its entiree structure. “The benefit of an a active sustainnable system m is that it ca an intelligenntly combine the systems so thhat when wo orking togeth her, the indivvidual elemeents ressources of a number of sy or systemss achieve moore than the sum of theirr parts.”(Foxx & Kemp 20 009)

Figu ure 8: Flock off birds (National Geographhic n.d.)

Figu ure 9: High Te ech Teamwork k of swarm roobots (National Geographicc n.d.)

Praactical Kno owledge “Architects need not become speciaalists in this a area but sho ould clearly understand the pootentials of h how this new w area of dessign could im mpact and/or enhance thhe projects tthey are designing.”(Foxx & Kemp 20 009) Thiis research w will use a bo ottom‐down n approach where an id deal kinetic structure iss bro oken down iinto variouss parts such as cladding g, connecting members,, actuators, etc. and researrched as succh. At first in n a general w way before using this kknowledge tto phyysically buillt and assem mble a protootype of a co onceptual de esign. Tecchniques used in this th hesis are 3D D printing, laaser‐cutting g, computer numerical con ntrol (CNC) milling and vacuum forrming. It is tthe writer’s opinion thhat these too ols willl keep imprroving durin ng the upcom ming years, so that the ey will eventtually be used in tthe production of building compon nents suitab ble for carry ying the calcculated load ds. Thiis however iis not the ca ase at the m moment of th his research.

Figu ure 10: Ball Jo oint, 3D‐Print

Figu ure 11: Stiff Cladding Connection

Motivation “The use of tools with real‐time feedback for prototyping behaviors can greatly influence the overall process of design and have a profound effect upon the final end product.” (Fox & Kemp 2009) Trying to visualize a KA design, the designer needs the tools to simulate, calculate and animate the movement of its structure. The 2D or 3D drawing software commonly used are not yet ready to generate this for him. They deliver, just like our current perception of architecture, static drawings. Design tools for kinetic systems do exist in specialized software packages (Fotiadou 2007), designed for mechanical engineers and animators in the media or entertainment sector. They utilize “skeleton” tools to simulate their design based on stiff members and actuators that bring movement in the system. But even when software that can handle skeleton animation is available we lack easy‐to‐use real‐ time calculation of stresses and displacements in the structure during its animation. What we gain in simulation of the kinetics we lose in structural insight of the global structure. Does the kinetic structure for example decrease its internal forces by moving in that specific stance or does it increase them ? Even when talking about smaller scale kinetic structures without simulation tools a thorough knowledge and structural insight is needed to notice problematic points in the entire structure. “The integration of computational tools, such as 3D modeling software for real‐time simulation and actual physical testing into the process of designing also allows designers to confront and anticipate many of the issues that occur when building at full scale.” (Fox & Kemp 2009) Designing and constructing IA also involves a specific skillset in microcontrollers, sensors and actuators to make the design come to life. This skillset is not part of the basic curriculum of an architect. But without a basic notion of these skills, the architect cannot construct KA. These simulation tools and specific skills do not exist because KA exists but because they will complement each other to produce better (and parametrical) KA when introduced in an early phase of design. “When the tools evolve with the design, the heuristics are facilitated by the tools, and not necessarily limited by their parameters. The design processes associated with interactive systems design are constantly evolving and are fostered by the consequent development of new tools.”(Fox & Kemp 2009)

Objectives The aim of this research consists of researching today’s simulation tools to simulate the physical counterpart, researching the various sensors and actuators while also linking them to our simulation and gaining practical knowledge in this field by addressing different general solutions and constructing a working prototype. When researching the chosen simulation software, its working range is found by implementing different case‐studies and documenting where the simulation software experiences problems. The simulation software is also validated by comparing it numerically to a common FE software package. Various sensors and actuators are researched to gain practical knowledge on how to operate and implement them but are also linked to the simulation software to test its range again in this aspect. Design issues when physically building KA are addressed using a bottom down approach involving different general aspects like actuation, cladding and nodes, but also by building a prototype.

Significance “Architects are eager to embrace technology that can increase optimization through adaptation with respect both to the environment and user needs, yet they must learn to recognize the interdisciplinary needs that such technologies have ensnared.” (Fox & Kemp 2009) This research is going to act as a catalyst to inspire new designs or research in the multidisciplinary field of IA. It will provide the necessary skills for architects together with means to begin simulating and designing KA. But will also provide the concept of IA in the form of Ephmeralization to structural engineers who can produce further calculations and can thus develop lighter and stronger structures using active control measurements. Engineers studying the indoor building climate can develop strategies that form the basis for architects and their designs for interactive façades2.

2 Interactive Facades: Interactive components embedded in a larger structure (façade) interacting with building physics behavior and appearance. These include sunlight, temperature, ventilation and also appearance in all kind of forms.

Mechanical, chemical and electrical engineers can also find inspiration for new mechanisms, smart materials or electronics to upgrade current versions of IA, like actuators that are powered by the sun or textile membranes that can change color like a chameleon. This common goal is the complementary inspiration for both parties for designing and discovering new applications. Even social sciences can observe prototypes of IA in a social context to see what kind of impact it has on human and social behavior, which in return forms the basis for architectural critique and the branching out of IA in different directions. Not only can they observe direct confrontation between the built environment and their users but they can also interpret the vast stream of pragmatic and humanistic data that will soon be available from every corner of this new sentient city, comprised of Interactive Architecture.

Chapter 2: Back kgrou und 2.1 1 Earlier W Works Thee concept off Kinetic Arcchitecture iss a young co oncept. Lesss than a hanndful of most arcchitects havee incorporated KA in th heir own oeu uvre before 1990. The m pro ominent figu ure of them is Santiago Calatrava (Calatrava n.d.). He has designed a cou uple of kinettic projects which conttain linkage systems witth a set of nnon‐bearing beaams where tthe kinetics could still b be calculateed by hand. F For examplee his Ernstin ng Waarehouse Gaate and the d design for th he Milwaukeee Art Muse eum. It is thee writer’s opiinion that th his is directlly linked to the absencee of more co omplex simuulation tools at thaat time. dependent w work of Calaatrava, a ressearch group at the Masssachusettss Bessides the ind Insstitute of Tecchnology wa as commisssioned aroun nd 1995. Th he Kinetic D esign Group p (Fo ox 1995a) caategorized d different intteractive strructures tha at had been cconceived u up to tthen by theiir mechanism(s) and is thus a greaat way of cap pturing mosst of the earrlier works.

Figu ure 12: Ernstin ng Warehouse Gate, Santiaago Calatrava a, 1983(Tzoniss & Lefaivre 11997)

Figu ure 13: Scale M Model, Santia ago Calatravaa (Tzonis & Leffaivre 1997)

2.2 Literature study From the earlier works up to 1990 there was still no large scale interest in interactive architecture. The background works of William J. Mitchell (Mitchell n.d.) were the only ones published until the 21st century. These paved the way for IA by introducing the bigger picture regarding the changing social roles thanks to upcoming phenomena at that time such as the internet and the digital realm. Around 2000 different architects and architectural firms began to experiment with and document IA: A new generation who now had the means and skills to do so. The magazine iA for example was published by Kas Oosterhuis who is still the current director of the Hyperbody workgroup (Oosterhuis 2000) at the Technical University of Delft. These magazines therefore consist of many student projects and prototypes together with parts of theoretical theory. Around 2009 an elaborate work of Michael Fox and Miles Kemp titled “Interactive Architecture” was published. Michael Fox, founder of the Kinetic Design Group at MIT can be considered as the person with the largest historical experience in the field and makes the book “Interactive Architecture”(Fox & Kemp 2009) a prominent piece in this literature study as well as the entire field of IA at the moment of writing.

The following books regarding IA were taken into account while conducting this literature study: 1. W. J. Mitchell, City of Bits, Space, Place and the Infobahn, MIT Press, 1996, pp.224 (Mitchell 1996) 2. W. J. Mitchell, e‐topia, Urban Life – But not as we know it, MIT Press, 2000, pp.184 (Mitchell 2000) 3. W. J. Mitchell, ME++, The Cyborg Self and the Networked City, MIT Press 2004, pp.259 (Mitchell 2004) 4. K. Oosterhuis; X.Xia, iA n°1 –Interactive Architecture, Jap Sam Books, 2007, pp.96 (Oosterhuis & Xia 2007) 5. K. Oosterhuis; X.Xia, iA n°2 –Interactive Architecture, Jap Sam Books, 2008, pp.112 (Oosterhuis & Xia 2008) 6. M.Fox; M.Kemp, Interactive Architecture, Princeton Architectural Press, 2009, pp.225 (Fox & Kemp 2009) The following magazines have been read but in the opinion of the writer they do not fit inside the category of KA since most of the projects in these magazines have no kinetic counterpart in their interactive design. Nonetheless these projects are part of the current interactive project landscape and form a source of inspiration and knowledge. 7. K. Oosterhuis; X.Xia, iA n°3 – Emotive Styling, Jap Sam Books, 2010, pp.128 (Oosterhuis & Xia 2010) 8. Lucy Bullivant, 4Dspace – Interactive Architecture, Academy Press, 2005, pp.128 (Bullivant 2005) 9. Lucy Bullivant, 4Dsocial – Interactive Design Environments, Academy Press, 2007, pp.127 (Bullivant 2007)

Build Projects

Background

Simulation

Theory

Protype K. Oosterhuis, IA nr3

Figure 14: Interactive Architecture Categorization + Dissertation

The entire written IA landscape has been split up into different categories by the writer. Abstracting their quantity, each of these categories contribute to the domain of IA. Each book has been mapped on its categorization in relationship to the other categories, most fitting for its content in the opinion of the writer. The contents of this dissertation have also been categorized to visualize the content in relationship to the existing landscape. This study also states that simulation tools are still not yet widely documented or actively used. Except for some projects in the magazine iA, KA and IA in general are not simulated in current projects. The majority of the project landscape arise from a practical knowledge and heuristic production methods of building prototypes and scale models. The majority of the projects in the above books have been documented3 and categorized in the following sections. By doing this, the research compares the books based on their vision on the current IA landscape/projects. 3

Appendix A: Project Landscape Raw Data

2.2 2.1 Timelin ne To visualize th he changing roles of theese categoriees inside the IA landscaape each book was roughly diivided by th he writer intto percentag ges and plottted on a tim meline. The sum m of the cateegories at any one timee is thereforre 100% and d thus will nnot take into o acccount the am mount of lite erature at an ny one timee. It is obvious to see thhat after the e trillogy of W. J. Mitchell the e overall bacckground disappears and the IA thheory takes oveer together w with a boom m of prototyypes and sim mulations in n the projectt landscape.. Ano other remarrk is the small rise in siimulation projects rather than reall projects an nd pro ototypes, meeaning that the simulattion packagees are relatiively new annd have mad de theeir way into some specific works.

ure 15: Time vversus Book C Contents Figu

Back kground IA Theory Simu ulations

Kas Oosterhuis, IA nr2 Kas Oosterhuis IA nr2

Fox&Kemp, Interactive Architecture

Kas Oosterhuis, IA nr1

W.J. Mitchell, ME++

W.J. Mitchell, E‐topia W J Mitchell E‐topia

W.J. Mitchell, City of Bits

Prototype es Real Life Projects

Tab ble 1: Legend TTime versus B Book Contentts

2.2 2.2 Project Location

Figu ure 16: Location versus Boo ok

IA n°1(O Oosterhuis & Xia 2007))

IA n°2(Oosterhuis & Xia 2008))

Interactiv ve Architectture(Fox & Kemp 20 009) Kinetic D Design Groupp Matrix(Fo ox 1995a)

Tab ble 2: Legend Books

Cattegorizing th he exampless found in lliterature peer book and d geographicc location it is notticeable that the magazzine iA main nly depicts n national worrk. The bookk Interactiv ve Arcchitecture h has a wider scope, not only showin ng national projects buut conceptua al pro ojects in Western Europ pe as well. Thee earlier wo orks, as categorized by tthe KDG, orriginated fro om the homee countries of pro ominent figu ures like San ntiago Calattrava and Ottto Frei. Altthough the ssize of their resspective pie charts tells us that new wer projectss are more p present in quuantity.

2.2 2.3 Project Mechanism m Bassed on a cattegorization n in mechaniisms made b by the KDG at MIT (Foxx 1995b), all of thee aforementioned projects are put iinto groupss while abstrracting theirr absolute value but show wing their re espective boook in a staccked column n. Keeping iin mind the me color cod de is used fo or the respeective bookss as the geog graphic locaation. sam It iss shown thaat the KDG h has made an nd documen nted a varietty of mechannisms. New wer pro ojects tend tto avoid the earlier linkkage systems or Nurnbe erg scissors mechanism ms wh hich are interesting but only have aa limited sco ope of usability and a prredetermined end d‐ and start point. Theese mechan nisms are the same cateegories as th he aforemen ntioned “meeans” of the kin netic structu ures. The “w ways” have n not been doccumented siince the amoount of cattegories wass too high, o only provingg the enormous amountts of actuatoors available e.

Figu ure 17: Mechaanism versus Book

2.2 2.4 Project Typologiess In tthe book Intteractive Arrchitecture ((Fox & Kemp 2009) the e authors elaaborate the kin netical countterpart in different typ ologies. Thee following categorizatiion puts the e maajority of pro ojects found d in the literrature into o one of three e types: Depployable, Dyn namic or Em mbedded. Dep ployable strructures are e conceived as structurees with a sm mall setup tiime. These include militarry, non milittary and crissis relief ten nts: very kin netic system ms during settup but the eend position n of the builldings is stilll static. namic systeems are systtems that arre interactiv ve and have a physical ccounterpart, Dyn butt who are sttill only a pie ece of a biggger system. These inclu ude solar shhading, ven ntilation sysstems, etc. Em mbedded sysstems are lik ke dynamic systems but form an in ntegral part of the stru ucture and space. It can n be seen th hat the neweer projects ttend towardds dynamic and d embedded d structuress instead of tthe earlier d deployable sstructures.

Figu ure 18: Typolo ogy Categorization

2.2 2.5 Project Application Kinetics Ano other catego orization also coined byy the authors of Interacctive Archittecture(Fox & Kem mp 2009), is that of the e application n of kinetic systems. What is a projject used for ? Con ntextual Adaaptability in ncludes stru uctures reaccting to our changing ennvironmentt, solar position, wind veloccity on the sccale of our b building. Mu ulti‐function n design functions on an n interior sccale: Positioning of movvable dividin ng walls or multi‐‐function furniture. Spaatial optimizzation seekss to optimizze the structture to its usage. Whethher a bassketball gam me is being p played in a sspace or ourr offices are e placed therre, the space willl optimize aacoustics an nd lighting tto our chang ging needs.

Figu ure 19: Appliccation Categorization

2.2 2.6 Project Timespan Wh hen dividingg each project by the sp peed of theirr movementt, there was no differen nce to b be seen. Eveery project’ss timespan w was direct, iimplying miinutes. Thiss means therre hass been very few or even n no projectts or designeers prototyp ping this biggger picture e in theeir work. Thee concept off time is nott yet widely y documenteed and taken n into accouunt in the currrent IA project landsca ape. It is for this reason n that the wrriter expliciitly takes intto acccount three levels of intteractivity in n time: Direect, Medium and Long ti timespans. Dirrect interacttivity involv ves stimuli liike daylightt levels, soun nd levels annd the presence of o objects or people. A buiilding can foor example change its sskin, thickenning it wherre theere is a lot of noise to m maintain an ooptimal spaace for the occupant to rread its boo ok. Or it can even change the shape of wiindows so th hat the spacce is equallyy lit and no glare or overheeating will o occur. Stim muli over w weeks can be e phenomen na such as ch hanging win nd patterns or geologiccal con nditions likee rising wate er levels. Th hese invoke a change in n the appliedd loads on the stru ucture and w will therefo ore change th the structuree’s optimal form versuss internal streesses and displacements. more human nistic valuess can changee. Like the a average amoount of visittors Oveer months m in aa certain resstaurant so it can adjusst his spatial configurattion. Or playygrounds can chaange their siize accordin ng to the am mount of chilldren betwe een the age of 3‐15 whiich aree staying in tthe vicinity.. It iss the writerr’s opinion tthat differen nt levels of interactivity y cannot alw ways be incorporated in each othe er on a techn nical scale. F For example e the inhabi tant’s need for dayylight and veentilation ca annot coinccide with op ptimal structtural behaviior. “Perhaps th he most impo ortant goal of an interactive system today shoulld be to act a as a moderator responding g to change between human needs a and externall environmen ntal cond ditions.”(Foxx & Kemp 20 009)

2.2 2.7 Project Structural behavior Thiis thesis maade a divisio on in variouss timespanss of IA. By do oing so the w writer impllies thaat these leveels cannot be put togeth her in a sing gle working mechanism m. Different levvels react to different da ata, thereforre the actuaation cannott couple thesse two levells. ver also imp plies that for example in nteractive fa facades shou uld Thiis categorization howev nott be able to be load bearing; structtures interaccting with applied load d should be. picts kineticc structures which are lload bearingg and able tto Higgh structuraal ability dep carrry loads on a large scalle. These incclude domee roofs or mo oving floorss. eans the prooject is prob bably combin ned with sm mall scale No structural ccapacity me inteeractivity lik ke interactiv ve facades oor installatio ons. ural capacity implies a normal resiistance to en nvironmenttal factors like A small structu win nd, snow an nd rain. Thosse structurees could be h high load be earing if theey were rein nforced eno ough.

Figu ure 20: Load B Bearing categorization

2.2 2.8 Project Intelligencce

Sw warm

Ce entral

Figu ure 21: Intelliggence Catego orization

Thee first part o of IA in the d definition oof the book IInteractive A Architecturee was that o of inteelligence. In ntelligence ccan follow d different patths to achiev ve its goal. CCentral inteelligence im mplies a centtral microcoontroller an nd extensive programmiing whereass swaarm behavio or implies lo ocal microc ontrollers w with simple programmiing. Exaamining all of the litera ature projectts we noticee an equal d distribution of 8‐6‐10 as dep picted in thee above Ven nn Diagram.

2.2 2.9 Project Sensor values Cattegorizing th he above prrojects by th heir sensor v values we have two exttremes. Praagmatic valu ues are values like temp perature, prroximity or llight level. H Humanistic values are valu ues that are able to sen se a person’s behavior, mood or acctivity and a act acccordingly. W We notice tha at pragmaticc sensors arre widely av vailable but humanistic sen nsors are no ot yet availab ble on a largge scale. It is the writer’s opinion however that thiss will changge drastically in the nexxt decade. Th he scale of tthe distribuution is 18‐4 4‐1.

Praggmatic

Figu ure 22: Sensor Values Cate egorization

H u m a n i s t i c

2.2 2.10 Web‐B Based Litera ature Beccause of thee nature and d age of IA aand KA, a lott of the literature can allso be found d thrrough variou us website’ss. These can n provide a d database containing diffferent pro ojects or aree from architectural praactices reseaarching IA. Mo ost of them aare addresse ed through the bibliogrraphy and illustrations.. However the oth her part of th he web‐based literaturre is not disccussed in this literaturee study, beccause of its llarge extentt. Thee exception is the follow wing visualiization, which was mad de based on the website e “Interactive Arrchitecture d dot org”, an independen nt blog desccribing varioous projectss in thee current IA landscape. The visualizzation show ws the relationship of keeywords of all thee posts and aarranges them by quan ntity. Surprissingly enoug gh keywordds such as “research” and d “students” have an acttive role in tthis curriculum, provinng the youth h of Interactive Arcchitecture at the time oof writing.

Figu ure 23: Interaactive Archite ecture dot orgg, Wordle (Glyynn 2005)

Chapter 3: Methodology & Results 3.0 Methodology Before talking about the different packages of the methodology this thesis will first elaborate on the used simulation software, Grasshopper, and the used Arduino microcontroller.

3.0.1 The Simulation Software, Grasshopper Research in simulation software led to a growing user community involving the add‐ on “Grasshopper”(Davidson n.d.) for Rhinoceros 4 SR8. The grasshopper add‐on gives us a visual coding environment where parametrical design is the main topic. Rhinoceros is not developed for skeleton structures though. The community groups have developed pieces of code, visualized as “components” in Grasshopper, which allow us to simulate real physical behavior. After reading a comparison thesis on commercial skeleton tools (Fotiadou 2007), together with the documentation on Rhinocerus + Grasshopper (Davidson n.d.), Kangaroo(Piker 2011b) and Firefly (Andy & Johnson 2010), this research has taken Grasshopper as primary simulation tool. This is mainly because of the available components, Firefly and Kangaroo, which allow us to manipulate data and simulate kinetics, the two basic needs in this IA research. Kangaroo is a physics engine based on the use of a particle‐spring system. For a better understanding of the system and its implementation we refer to the Kangaroo Manual (Piker 2011c). But this basically means that in this thesis structural nodes will be modeled as particles and interconnecting beams or truss members will be modeled as a “spring” connection between two particles. These springs have a certain stiffness defined by following formulas of general structural engineering, in accordance with their compatible units: ∗

Lin near actuato ors, an integral part of K KA, are how wever being iimplementeed in a diffferent way tthan the stifff beams. Acctuators aree implementted as springgs with a varriable rest leength. Varia able length w which is link ked to the sttroke of thee specific acttuator that ccould be use ed in realityy. The resultt of a successful simulattion will hav ve adjustable slid ders which ccan be used to control tthe stroke of every singgle actuator, we adjust th hese parameeters we adjust the lenggth of the just like in reality. When w acttuator and simulate the e kinetics of the structure, which th his researchh is looking ffor.

Figu ure 24: Actuattors, Spring Im mplementatioon

Figu ure 25: Truss member, Spring Implemenntation

Figu ure 26: Kangaaroo Compone ents in Grasshhopper

Figu ure 27: Grassh hopper Enviro onment

3.0 0.2 The miccrocontroller, Arduinoo Forr receiving aand sending g digital and d analog sign nals this ressearch uses an Arduino Duemilove miccrocontrolle er. The Ardu uino was dev veloped as p part of a stuudent projecct devveloping Op pen‐Source h hardware. Itt can be pro ogrammed u using the Ardduino pro ogramming language ba ased on Pro cessing. The Arduino h has the abilitty to receive e anaalog and diggital signals but is also aable to send d digital sign nals to actuaators like ligh hts or motorrs. Differentt models difffer in the am mount of po orts as well as having an Eth hernet connection port.. The latter is not impleemented on the Duemillove and thu us nott researched d/used in th his thesis. “Arduino is a an open‐source electronnics prototyp ping platform m based on flflexible, easyy‐to‐ use hardware and softtware. It's in tended for a artists, design ners, hobbyiists, and anyyone i interested in n creating in teractive objjects or enviironments.“ ((Arduino 20 005)

Figu ure 28: Testin ng the Arduino o, LED‐bar

To tackle the subject spoken of in the introduction it has been broken down into three packages: 1. Simulating Design The first package is a compilation of different case studies. These involve practical cases which can be found in the current KA landscape. An information‐orientated sampling has been used to find different atypical designs to test the abilities of the simulation software, Grasshopper. This package will also contain a comparison study between Grasshopper and a Finite Elements‐software package, ANSYS, for numerical validation. 2. Simulating Behavior The following package will implement different low cost, highly available sensors in some of the previous case studies. This again to test the abilities of the simulation software, Grasshopper and to find the scope of its ability to link the physical sensory environment to the simulation. Not only the pragmatic but also humanistic sensors will be addressed here, together with the numerical differences of swarm and central intelligence. 3. Practical Design Issues In the practical design package, an ideal kinetic structure will be broken down into its different parts like cladding, connecting members, actuators, etc. Different general solutions will first be analyzed and produced in a practical study of building and using. The end of this package will contain a working prototype of a conceptual KA design.

3.1 1 Simulatiing design n 3.1 1.1 Simulattions, Case Studies 1. ORAMB BRA, Tristan n D’Estree SSterk a. Introductio on Thee Office for Robotic Arcchitectural M Media & Burreau for Ressponsive Arcchitecture, o or in sshort ORAM MBRA was fo ounded by T Tristan D’Estree Sterk. T This small bbureau is inteerested in “rethinking tthe art of coonstruction alongside th he emergennce of ressponsive sysstems”.(D’Esstree Sterk 2 2003) one of his first publicattions he setss up a basic actuated te ensegrity moodule (type 1) In o ablle to multiplly in differen nt fashions (type 2&3). Actuators a are shown iin his illu ustration as elastic mem mbers.

Figu ure 1: Actuate ed tensegrity:: Type 1,2,3 (D D’Estree Sterkk 2003)

Figu ure 29: Scale m model Type 3 3 (D’Estree Steerk 2003)

b. Simulation ns

Figu ure 30: Simulaation Actuate ed Tensegrity Type 1

Figu ure 31: SimulaationActuated d Tensegrity TType 2

Figu ure 32: Simulaation Actuate ed Tensegrity Type 3

2. Hyberb body, TUDellft, Kas Oostterhuis a. Introductio on h group at th the Faculty of of Architectu ure at the Deelft University ty of “Hyperbody is a research arch Technologyy directed byy prof. ir. Kass Oosterhuiss. The goals sset for the grroup’s resea arre to exploree techniques and methodds for designing and buillding non‐sttandard, virttual and interractive archiitectures. Cuutting edge ttechniques and methods are taught and appliied by researchers and sstudents.”(Ooosterhuis 20 000) Durring their w work they co ollected mulltiple examp ples and student projeccts. The one thiss research w will simulate e is the firstt Muscle Tow wer. Stiff intterconnectinng crystals were held togeether by outter actuatorrs. Actuatorss were pneu umatic musccles that we ere maade availablee by the Festo Corporattion. A simillar project w was realizedd under sup pervision off Axel Killian n et al. that ggoes by the name of Wh hoWhatWh enAir.

Figu ure 33: WhoW WhatWhenAirr, Flexible Tow wer (Kilian et al. 2006)

Figu ure 34: Muscle Tower II, Hyyberbody (Ooosterhuis 2000 0)

b. Simulation n

Figu ure 35: Simulaation Flexible e Tower

3. ORANG GEVOID, Rob botic Memb brane a. Introductio on Oraangevoid is an conceptu ual architecctural firm specializing in IA, interaactive facades and d robotic meembranes. O One of their r remarkablee prototypes is that of aa robotic triaangulated m membrane th hat can movve due to pn neumatic acttuators attaached to it. Witthout declarring the sen nsory inputss, only the k kinetic countterpart, thiss design is meerely techniccal. How wever TESSSEL is an intteractive insstallation alsso consistin ng of a trianggulated meembrane witth the same appearancee but actuatted by retractable cablees attached to thee ceiling. Thiis installatio on moves acccording to sound wave es that a couuple of sensors pick up on the membrane.

Figu ure 36: TESSEL (Lab[au] 201 10)

Figu ure 37: Robottic Membrane e (Orangevoidd n.d.)

b. Simulation n

Figu ure 38: Simulaation Roboticc Membrane

4. Actuateed Truss a. Introductio on A ccollaboration n at the University of T Toronto, betw ween an arcchitect and aan aerospacce enggineer, camee up with an n responsivee truss (Merrali & Long 2009) consiisting of an upp per beam co onnected by y hinged tru uss memberss and steel ttensioned caables. Eacch triangle p pointed dow wnwards is aa single cell. Each cell h has embedd ed force sen nsors which h can measure pressure in the uppeer beam. Depending onn the interna al streess the trian ngle elongattes, stretchiing the steell cables but adding morre reaction upw wards forcee and bendin ng resistancce to the beaam. The beam will thus adjust its heiight to the fo orces applie ed to it. The usable heig ght of the sp pace below iis therefore con nstantly opttimal.

Figu ure 39: Excerp pt from disserrtation, Respoonsive Actuatted Truss (Me erali & Long 20009)

b. Simulation n

mulation Actuated Respoonsive Truss Figgure 40: Sim

5. Kineticc Circle a. Introductio on Dessigned by th he writer him mself, a Kin netic Circle tthat can cha ange its heigght by rotatiing thee lower circlle. Based on n the mechan nism of an aaperture thiis mechanis m will heiighten its up pper circle instead of cllosing it tow wards the ce enter. The onnly memberr thaat has not beeen modeled d is the colu umn that haas to be placed in the miiddle of the circcle to avoid the upper ccircle movin ng from the center. b. Simulation n

Figu ure 41: Simulaation Kinetic C Circle

6. Nurnbeerg scissorss, Hoberman nn a. Introductio on Chu uck Hoberm man, Archite ect and foun nder of Hobeerman Associates, is thee inventor o of thee expanding Geodesic D Dome. The d dome, which h has even been changedd into a chilld’s toyy, is one of th he first in th he era of KA A based on th he Nurnberg Scissor meechanism. Bessides the exxpanding dome the Hob berman Asso ociates have e developedd different exp panding stru uctures like the helicoid ds and hypaars. A sister program caalled the Adaaptable Building Initiattive or ABI h has also made differentt kinetic moodels includiing theeir patented d Strata System and diffferent adapttable glass ffritting’s.

Figu ure 42: Expanding Geodesic Dome (Hobberman 1997)

Figu ure 43: Strata Module(Adaptive Buildingg Initiative 20 006)

Figu ure 44: Simulaation of the Expanding Geoodesic Dome

7. Resultss Mo odels compilled from nodes, beams and anchorr points which are consstant in spacce, can n be simulatted. nding can allso be accurrately incorp porated in K Kangaroo by y adding bennding stiffness Ben on a node and two of its connecting m members. Different stru uctural nodees like hinge es, tru usses or beam ms can thuss be modeleed with this option.

Figu ure 2: Bendingg validation K Kangaroo (Pikker 2011a)

Issue 1‐1: Mod dels involving rolling a nchor pointts, meaning anchor poinnts on a line e or ssurface, are not yet imp plemented. However Daaniel Piker, the creator of Kangaroo, tellls the comm munity that tthese featurres will be aavailable in tthe next verrsion of Kan ngaroo expeected late 20 011. dome for example cann not be propeerly simulated. Rolling gguides are Thee geodesic d sup pposed to sttay on a certtain line and d are unablee to move frrom it. The eexample of tthe kin netic circle w was able to d define a rollling guide u upwards. This however by intrroducing a n new force ca alculated byy its displaccement from m two perpe ndicular surrfaces, cuttin ng in the cen nter point. A A very comp plicated solu ution whereeas it can be e eassily modeled d by an anch hor point byy line if available.

Figu ure 3: Geodessic Dome Simu ulation

Issue 1‐2: Wh hen introduccing the exa ct stiffness in Kangaroo o, the iteratiion engine can nnot handle this high, v very stiff, vallue. Therefo ore a smaller time step of the iterration has to o be chosen n which can be camouflaged by incrreasing the sub iteratio ons thaat happen beetween plottting the str ucture in th he Kangaroo o engine. Moore info ormation ab bout the calculations off the engine can be foun nd in the Kaangaroo maanual.(Piker 2011c)

3.1 1.2 Numerical Validation Graasshopper iss validated tthrough thee simulation n of a 2D tru uss confinedd at its ends.. In thiss validation n the displaccements of aall the nodes will be com mpared to aan FE calculation maade in ANSY YS. The differrences in diisplacementt will be calcculated and d wn next to eeach other ffor comparison. theeir percentages are show Botth models h have the sam me material properties and dimenssions. Youngg’s Modulus,, E, equ uals the stan ndard consttruction steeel value of 2 200000MPa. The cross ssection of all thee truss mem mbers is equa al to 2500m mm², consisttent with a ssquare sectiion of 50mm m. n is based on n a linear caalculation in n ANSYS. In oother words Issue 1‐3: This validation we assume thaat the superrposition of different load cases will lead to th e same end ressults. It is po ossible to acccount for n on‐linear beehavior of th he construcction but is n not neeeded in thesse stages of the validatiion. As mentioned before KA d describes th he truss mem mbers as springs. Sprinngs that follo ow Hooke’s Law. SSince we know the stiffn fness using tthe same pa arameters foor calculatio ons in A ANSYS, we ccan simply d divide the m member’s strrain in the ssimulation w with their app propriate sttiffness to fin nd the interrnal forces. T These forces are projeccted on a color scaale and prev viewed on th he structuree.

Figu ure 45: Adding a color scale e in Grasshoppper

3.1 1.2.1 Default Scenario o Results Thee default sceenario is tha at of no actu uation and iis used to va alidate the G Grasshopper as aa means to ccalculate displacementts and intern nal forces in n a normal ssituation. 5k kN and d 10kN load ds were applied to the u upper nodess.

Figu ure 46: Simulaation Grashop pper, 5kN, Noot Actuated, D Deformation S Scale 1:1

Figu ure 47: Simulaation ANSYS, 5kN, Not Act uated, Deform mation Scale 1:1

No ode

X Dire ection Y D Direction N Node X Dirrection Y Diirection 0,0 0,0 0,0 1 0,0 0,0 0,1 0,1 2 0,1 0,1 0,1 0,1 3 0,1 0,1 0,1 0,1 4 0,1 0,1 0,1 0,1 5 0,2 0,0 0,1 0,1 6 0,0 0,1 0,1 0,1 7 0,2 0,1 0,1 0,1 8 0,1 0,1 0,1 0,1 9 0,1 0,0 0,1 0,1 10 0,1 0,0 0,0 0,0 11 0,0 0,0 0,0 0,0 12 0,0 0,0 0,1 0,1 13 0,0 0,0 0,1 0,1 14 0,0 0,0 0,1 0,1 15 0,0 0,0 0,1 0,1 16 0,0 0,0 0,1 0,1 17 0,0 0,0 0,1 0,1 18 0,0 0,1 19 0,0 0,0 0,1 0,1 20 0,0 0,0 0,1 0,1 21 0,0 0,0 0,1 0,0 22 0,0 0,0 0,0 0,1 0,1 0,0 0,1 Tab ble 3: Error Maargin %, Default 5kN Tab ble 4: Error ma argin %, Defa ult 10 kN 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

3.1 1.2.2 Actuatted Scenario Results Thee actuated sscenario willl shorten th he 4th vertical truss mem mber to halff of its lengtth upper nodees for validating the kinnetics and th and d apply 0kN N and 5kN lo oads on the u he kin netics respecctively togetther with ap pplied loadss.

Figu ure 48: Simulaation Grassho opper, 0kN, A Actuated, Defo ormation Scale 1:1

Figu ure 49: Simulaation ANSYS, 0kN, Actuateed, Deformation Scale 1:1 Node

X Dire ection Y Dire ection No ode X Dire ection Y Dire ection 0,0 0,0 1 0,0 0,0 ‐106,4 21,6 2 ‐105,7 21,3 ‐111,8 9,5 3 ‐111,2 9,4 317,3 ‐2,7 4 316,2 ‐2,7 247,8 ‐17,4 5 247,3 ‐17,4 206,8 ‐28,0 6 206,7 ‐28,0 158,8 ‐32,9 7 159,0 ‐33,0 127,6 ‐38,0 8 128,0 ‐38,1 106,0 ‐45,2 9 106,4 ‐45,4 90,1 ‐59,2 10 90,6 ‐59,7 0,0 0,0 11 0,0 0,0 0,0 0,0 12 0,0 0,0 63,0 31,1 13 62,6 30,8 70,9 13,6 14 70,5 13,4 79,3 17,7 15 79,0 17,6 ‐132,1 ‐18,8 16 ‐132,0 ‐18,8 ‐120,8 ‐29,0 17 ‐120,8 ‐29,1 ‐112,0 ‐33,6 18 ‐112,2 ‐33,7 ‐104,6 ‐38,9 19 ‐104,8 ‐39,0 ‐97,7 ‐46,7 20 ‐97,9 ‐46,9 ‐91,0 ‐65,2 21 ‐91,4 ‐65,7 0,0 0,0 22 0,0 0,0 32,8 ‐20,1 32,8 ‐20,3 Tab ble 5:Error Maargin %, 0kN Table 6:Error Margin %, 5kN 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

3.2 2 Simulatiing behav vior 3.2 2.1 The Sim mulation So oftware Thaanks to the plugin, Firefly, Grasshoopper can in nput and outtput data froom the Ard duino micro ocontroller. By doing soo this plugin n is the missing link for observing o our inteeractive arcchitecture w with a real seensory envirronment wiithout physiically con nstructing itt. pare the phyysical with tthe simulate ed model onn a small sca ale It iss even possible to comp for validation b before constructing thee entire design. With th hese final steeps the sim mulation of K KA is complete and the physical deesign can be e built.

Figu ure 50: Arduin no Send/Rece eive implemenntation in Gra asshopper

3.2 2.2 Linking Data Meth hods 1. Swarm m Intelligencce Swarm behavior, as aforem mentioned, can be seen n as the simp plest but alsso the fastesst wayy to controll intelligence. Sensor daata is interp preted by a ssingle cell, w which it actss upo on accordin ng to its prog gramming. T Therefore sw warm behav vior entails that the sen nsory enviro onment and d the actuatiion environm ment are the same. Swarm behavior is implem mented with h ease in Grasshopper. T The raw datta values of sen nsors can bee remapped d to the rangge of the acttuator’s stro oke. Functioons such as smoothing oveer a numberr of intervalss to avoid su udden spike es as well ass dampened d wavve functionss can be imp plemented tto simulate a swaying m movement rresponding tto a cerrtain threshold of applied pressuree or acousticc waves. If o only remapp ping the sensor data is n no longer en nough, Grasshopper suupports basic maathematical operations to manipulaate the dataa. If the data is manipulaated in a mo ore draastic way thaan in mathe ematical opeerations, thiis thesis refers to this inntelligence as cen ntral intelliggence.

Figu ure 51: Manip pulating and vvisualizing Sennsor Data in G Grasshopper

2. Central Intelligencce wo methodss of implementing central intelligeence: Thiis research cconsiders tw Pro ogramming in an extern nal languagee and implementing in Grasshoppeer or using tthe standard Galap pagos Evolu utionary solvver in Grassshopper. Pro ogramming is possible iin C++ or VB B. While pro ogramming intelligencee the design ner can n anticipate various sce enarios and implement them to hiss choosing. T This howeve er req quires time aand program mming skill s from the d designer, bu ut can be impplemented in Graasshopper aas a compon nent to act w with the inco oming data. other way to simulate a a certain acttion is to use an optimization solveer. Meaning Ano intrroducing an n end value w which can b be minimizeed or maxim mized. Thesee values cou uld for example bee the sum off internal fo rces multiplied by its b beam lengthh to minimizze he distance between a point and a structure too minimize,, thee internal strresses. Or th gro ow towards,, or maximizze, grow aw way from. Galapagos w will then optiimize each p parameter, aactuator Thee optimizatiion solver G stro oke, to miniimize or ma aximize the eend value.

3.2 2.3 Simulattions 1. Kineticc Arch expan nding towarrds a specifiic point. Imaagine a kineetic arch wh hich is a 2D ssection of an actuated ttensegrity hhalf pipe . Th his arcch has perpeendicular acctuators in h his structuree which can n shrink theiir length by y up to 2 20%. point is designated on the exterior of the arch to visualize e a certain ppoint of A p inteerest to the arch. A poin nt where th he arch can g grow toward ds or stay aw way from. T The Graasshopper eenvironment can calculaate the distaance betwee en the pointt and the surrface of the aarch. This p point can alsso be the staarting positiion of a speccific node to o meeasure and m minimize itss displacemeents. meter optim mization solv ver, built intto Grasshop per, can Gallapagos, an multi param iterratively find d the right elongation foor every acttuator to minimize, or m maximize th he distance betweeen the poin nt and the aarch. In this observation n are the ressults of 3 olutionary o optimization ns and one ccomparison swarm metthod. evo Thee compared d method is a swarm beehavior calcu ulating the d distance to each divisio on of tthe arch and d remapping g those num mbers to thee interval of actuator moovement, e.g. [0;‐‐0,2]. The sw warm method is direct and can be performed without a ccentral miccrocontrolleer performin ng a cumberrsome iteraative calculation.

Figu ure 52: Optim mization, Kinettic Arch towa rds point

Inffrared senssors are able e to measurre a certain distance aw way from theem and can thu us be implem mented dire ectly from th he sensor in n the simulation. Like afforemention ned thee data can bee smoothed d, meaning taaking an average of a couple of preevious value es, to aavoid unwan nted spikes.

Figu ure 53: IR sensor connected to the Arduuino

Figu ure 54: Manip pulating & visualizing Sensoor Data in Gra asshopper

Acttuator

Inte elligent 1 1 2 3 4 5 6 7 8 9 CP

Diffference

0 0 18 20 19 0 7 10 0 0,5655 594 0

Tab ble 7: Intellige ent‐ versus Sw warm Behavioor

Intelligentt 2

Intelligent 3 0 0 20 20 20 0 9 4 0 0,565594 0

0 0 8 20 19 0 3 0 0 0,5655 594 0

Swarm 7 7,93 12 2,58 17 7,68 20 0,00 16 6,76 11 1,51 7 7,12 3 3,25 0 0,00 0,565 5692 9,8EE‐05

Issue 2‐1: Theese compare ed results sh how that an n intelligent design can actuate more acccurately than n a swarm m method. How wever the lo ong calculattion methodd and the phyysical means to connect every senssory input to a central m microcontrooller gives itt a disadvantage ccompared to o the swarm m method. It ccan also be sseen that va arious actuaator combinaations offer an optimal solution. Theerefore the end results are not preedetermined d but depend on the prooceedings o of eacch iterative p process.

2. Actuateed Truss Thee responsivee actuated ttruss as sim mulated in th he previous chapter cann be linked tto a praagmatic sensor value lik ke that of a p push sensitive sensor r. In this exaample the sen nsor outputss a value between 0 and d 1024, whiich is norma al for analogg sensors. ues are smoothed and m mapped to fi fit in the Just like the infrared sensors the valu acttuator stroke range. The ese inputs aare directly inputted lik ke the param metrical slid ders were in Grassh hopper earliier. The folloowing illusttration used d the value fo for the rightt ost cell in the truss. Sim mulating 5 ceells also imp plies that there need to be 5 mo ind dependent sensor value es. no microcon ntroller boaards have on nly 6 analog slots and 114 or more Currrent Arduin diggital inputs. This practiccal problem m can be solv ved by using g shift registters to use onlly three inpu ut slots for a a range of 8 8 independeent inputs.

Figu ure 55: Push ssensitive senssor connectedd to the Arduiino

Figu ure 56: Implem menting Senssor Data

3. Kinetic Arch minimiizing interna l stresses Thee same kineetic arch as sspoken of in n the first simulation ca an also miniimize its inteernal forcess by defining g the sum off the produccts of intern nal force andd length of eacch beam. Galapagos can n then minim mize this sum to calcula ate its optim mal form. placed on th he third nodde from the Forr this simulaation a downward forcee has been p leftt. Using this downward d force and sstructure, Kaangaroo calculates the internal forrces and d displacem ments. The ca alculated fo rces and len ngths will th hen be usedd in the pro oduct sum. In rreality the aapplied forces are not kknown in tim me. Strain ga auges wouldd therefore be app plied to everry beam in tthe structurre, providing the structure with reaal time mo onitoring of the strain a and internal forces in itss members. These valu es would th hen be used to mak ke it possiblle to optimi ze its structture using itts programm ming inteelligence. Issue 2‐2: If w we compare three differrent iteratio on processess we see thaat the exact acttuator valuees occur in every processs. Howeverr this does n not prove thhat every iterrative proceess delivers the same reesults, as shown in issue 1.

Figu ure 57: Optim mization, Kinettic Arch minim mizing stresse es

Actuator

Intelligent 1 1 2 3 4 5 6 7 F*L

Intelligent 2

1 0 ‐3 0 0 0 0 0,000033

Tab ble 8: Comparison Differentt iteration proocesses

Inte elligent 3 1 0 ‐3 0 0 0 0 0,000033

1 0 ‐3 0 0 0 0 0,000033

4. Remarks a. Sensors An enormous aamount of low cost sen nsors are avaailable as an n electrical ccomponentt. Som me can even n be recuperrated like sh hown in the informal ha andbook of Usman Haq que and d Adam Som mial‐Fischerr: “Low‐tech h sensors an nd actuators”. (Haque & & Somlai‐ Fischer 2005) Sen nsors worth h mentioning g that have been used d during this rresearch buut haven’t be een imp planted in aa working simulation arre: Flex‐ben nd resistor, O Optical resisstor, tilt sensor and d RFID antenna. The RF FID antennaa cannot be directly imp plemented iin GH without thee necessary programming, whereass all the oth hers can be d directly rem mapped.

b. Actuators Thee add‐on Firrefly for Gra asshopper ccan also outp put values to servo’s, m motor or oth her acttuators from m GH. This w way GH can eeven be used to sync th he simulatioon model to a phyysical modeel. This is useful for exam mple when working on n a prototyppe or when com mparing thee models to each other ffor research h or validatiing the prottotype beforre pro oducing on llarge scale.

c. Protocols Oth her remarkaable functions are impleemented in Firefly, like e the ability to link GH tto Pacchube (Haqu ue n.d.). Pacchube was ccreated by U Usman Haqu ue and offerss a place to uplload and download data streams. FFor this thessis a temperrature and l ight sensor were set up to upload data to Pachub be. From thee Pachube po ortal the strreams of datta were downloaded into Grasshopper. T This protocol can be ussed in variouus situation ns varrying from aa single senssor on top oof a building g that contro ols the entirre façade or letss actuators respond to data from aanother conttinent for va arious desiggn reasons.

Figu ure 58: Pachu ube receive im mplementatio n in Grasshop pper

Figu ure 59: Pachu ube, Live senso or streaming and stream in nformation

Firefly also inttroduces the e fiducial prrotocol in GH H. This protocol was deeveloped and firsst used by a team (reacT TIVision n.d d.) which waas introduciing a recognnition tool fo or usee in multi to ouch tables. Using this p protocol a sttandard cam mera can nootice differen nt standard shapes and even n the directi on they are pointed in. This can foorm the basiis for a simple traacking algorrithm for usse in IA. Linking these sshapes to diifferent people maakes this pro otocol a hum manistic sen nsor. Coordin nates from tthe movemeent of differrent peo ople can thu us be used fo or actuatingg the structu ure using sw warm or cenntral inteelligence.

Figu ure 60: Fiducial implementtation in Grassshopper

3.2 2.4 Emotivee behavior a. Humanistic Sensors Thee sensors av vailable toda ay are mereely analog orr digital dev vices who caan output praagmatic valu ues like applied pressurre, daylight level, etc. Itt is the writeer’s opinion n how wever that sseeing the current pacee of events, ssensors willl be designeed that can deccide on whaat activity we are condu ucting or how w we are feeling by loooking at our stance or faciaal expression n: humanisttic values. RFIID componeents are alre eady able too sense inforrmation stored in passiive RFID tag gs wh hich are gettting smaller and which can even bee implanted sub‐dermaally, under our skin, addressin ng some key y issues such h as privacy y though.

Figu ure 61: Sensors

Miccrosoft laun nched its “Kiinect” sensoor this year. A motion ca apture devicce for conso ole gam ming, that m makes use off a controlleer obsolete. The Kinect is a small 3 D scanner tthat can n capture ou ur skeleton b be decidingg a couple off key points in our stancce. These poiints can be llinked to ou ur mood or aactivity. At tthe time of w writing thirrd party exp periments are being settup to send Kinect dataa to Grasshopper using the universal OSC C protocol.

Figu ure 62: Grassh hopper/Kinecct Sensor (Anddy Payne et al. 2010)

b. Behavior Ano other topic is the actua ation of a deesign. We tak ke it for granted that IA A can follow w praagmatic or h humanistic d data as it coomes along p per second, minute or hhour. But do oes it h have to? Keeeping in min nd that theree are differeent levels off interactivitty, they can all havve different behaviors. Behaviors aas discussed d here are th he structuree’s reaction speeed, accuraccy and logic.. ople react an nd experien nce space diifferently wh hen the stru ucture movees gently with Peo a sw waying mov ve or sudden nly shakes tto its end po osition. Peop ple can starttle or even em mpathize witth the kinetiic structure.. The place rreceives its own characcter and beh havior and ccan alter the e perception n of space. F For example e the Dune 44.0 project b by Stu udio Roosegaarde chang ges the spacce of a sterille pedestria an tunnel intto a living, ressponsive env vironment. Acccuracy, as deepicted in our comparisson between intelligent and swarm m behavior, can n be a design n issue. May ybe we wantt a building g that does n not do as weell as bigger,, stro onger and m more expenssive buildin ngs. Or mayb be increased d accuracy juust is not neccessary to su uccessfully complete itts basic goalls, hence sw warm versuss central inteelligence. Log gic can be in ntroduced w when more aaccessible v versions of le earning artiificial Intelligence make their way to the pu ublic. This iss not the casse at the tim me of writing g.

Figu ure 63: Dune 4 4.0 Maastunn nel(Roosegaa rde 2011)

3.3 3 Design IIssues Sim mulating a m model of you ur design is a great way y of getting tto know thee global stru ucture and its behaviorr. Only an ab bstract levell of detail is necessary tto do so. It iis posssible to dettail a simula ation modell to the levell of construcction. This iis however verry time conssuming and without thee use of parametrical design almosst un‐existin ng for large scale application ns. A n new era of CNC milling, 3D printingg and laser ccutting how wever has coome to our doo orstep. Partts with different lengthss, but the saame charactteristics, cann now easily y be pro oduced paraametrically tto be installled in a final design as a a puzzle. Thhese new technologies to ogether witth existing m means shoulld be incorp porated in ouur designs a and ould be takeen into account in the p primary desiign phases. sho

Figu ure 64: Laser‐cutting and e engraving a shheet of MDF

3.3 3.1 Joints Join nts are defin ned as the n nodes betweeen memberrs. A joint co ouples diffeerent members in d different dirrections and d allows diffferent degreees of freedo om for eachh separate meember. Sincee different push and pulll forces com me into conttact with th e joints, the ey havve to be dev veloped and created to b be able to w withstand th hem with miinimal weak k poiints that migght cause fa ailure. hat nodes on nly moving in the 2D pllane, involvi ving two or In ggeneral it caan be said th mo ore members, are relativ vely easy too produce. N Nodes conne ecting membbers in 3D spaace require, even with o only two meembers, an eenormous a amount of exxtra design and d production time.

3.3 3.2.1 2D Joiint Thee connection point of th he node is ccalculated by y the intersection pointt of the con nnecting meembers. Usin ng a transveerse pin diffferent 2D members cann be attached to eeach other. This connecction also reesists movem ment out off the plane ddue to its con nnection. Issue 3‐1: This obvious so olution how wever introd duces eccenttricity, whicch creates mo ovement outt of the 2D p plane if the sstructure haas large forcces workingg on it. To av void thiss the memb ber can be co onnected wiith a symmeetrical end p point, whichh avoids the e pro oblem of ecccentricity. Lim miting factorrs of these n nodes are th he thicknesss of the node e and the sttrength and len ngth of its co onnecting piin.

Figu ure 65: 2D Turning Joint, w with eccentriciity

Figu ure 66: 2D Turning Joint, w without eccenttricity

Issue 3‐2: Wh hen designin ng these 2D joints their intersection line alwayys has to fall in thee same pointt. Nodes dessigned in an n earlier stage as depictted in the loower figure are thu us not correct. Even when we conn nect multiplee members the node is still unstab ble and d cannot be used as succh.

Figu ure 67: 2D Joint Unstable

3D nodes comprised of tw wo 2D jointss are also po ossible. The movement of the con nnected mem mbers is however only in those tw wo planes, which is an inntegral partt of thee single 2D joint. Meaning this 3D n node is not u useful in applications w where the con nnected mem mbers move e out of the two interseecting planes. Because tthe connection doees not fall in n the interse ecting pointt there need d to be at lea ast three connnecting meembers to sttabilize the n node in spa ce, instead o of the unsta able 2D nodee afo orementioneed. Th he model prroduced in this researchh consisted out of f parts which h were laserr‐cut and coould be insserted into each other forming a pperpendicula ar strructure. Thee connection n was modeeled with a sn nap‐fit4 desig gn so that th he two perppendicular paarts could no ot be pulled d apart beforre first re leasing the snap‐fit.

Figu ure 68: Interse ecting 2D joints, Snap‐Fit

Sn nap‐Fit Design: Using a hook‐like mechannism parts can n be locked intto position. Thhe design of a a snap‐fit involves extensive calcculations in m material strenggth and applie ed forces.

3.3 3.2.2 3D Joiint Dessign of 3D jo oints depends greatly oon the numb ber of attach hed truss m embers. The bassic connection of only two memberrs has been used in many applicatiions such ass thee transmission of boats and cars. Issue 3‐3: Thee universal joint or Card dan‐joint is made of tw wo symmetriical pins con nnected with h a middle ccross conneecting both. This node is thus able tto move in ttwo directions and d even able tto transmit aa rotating m motion in the member inn another direction. Duriing this rese earch a paraametrical m model was de esigned to 33D print these con nnections. Thee first modeel that was p printed was not correcttly designed d. There wass no structu ure hollding the miiddle pins in n its location n, causing itt to fall out o of place butt also break durring creation. This how wever has beeen adjusted d by adding a circle in th the inner cro oss in aa second mo odel.

Figu ure 69: Param metrical Mode el Universal Jooint 2

Figu ure 70: 3D‐priint Universal JJoint 2

Issu ue 3‐4: A balll joint is another methodd linking two o members able to rotatee in the 3D plane. An obvio ous limitation n when usingg 1 ball is the e inability to connect moore than two e system for sspace trusse es, that goes by the namee “Tuball”, members. A patented node con nsists of a meetal sphere w where threadded ball jointts attached tto the beam can be imp plemented to o connect sp pace truss meembers.

Figu ure 71: Cardboard Space frrame; Ring Paass, Delft (Octtatube 2010)

In tthe scope off this researrch the writeer designed d a similar parametricall ball joint o only witth internal b ball joints in n every card dinal direction, which m makes the baall joint attaached to thee beam obso olete. Param meters are th he general d dimensions as well as the plaacement of tthe ball jointt. With thesse parameteers the angle e of freedom m is also calculated and d can be take en into accoount. Thiis design is not better in the econoomical sensee of material use but haas a wider anggle of movem ment, developed especiially for KA,, and cannott be comparred to the no ode sysstem for stattic space tru usses, which h only requiire a certain n degree of ffreedom con nsistent with h its calcula ations. Thiis node is ob bviously lim mited in streength to the specificatio ons of the 3D D printer. How wever it is tthe writer’s opinion thaat these prin nters will be e able to usee plastic of higgher strengtth and densiity to even p print ready‐to‐use node es for real sttructural pro ojects in thee next few de ecades.

Figu ure 72: Param metrical Ball Jo oint

Figu ure 73: Sectio on Parametrical Ball Joint

Figu ure74: 3D Prin nted Ball Joint

Figu ure 75: 3D printed Ball Join nt, Section

A 3 3D printer w works by lay yering hot pllastic on top p of each oth her to makee a model. Wh hen stiffenin ng structure e is needed tthe 3D printter can print a dissolvabble plastic wh hich later can n be remove ed in a NaOH H bath. Thiss ability wass used in thiis model to imp plement balll joints in th he sphere w without haviing to use an ny other hollding stru ucture. The ball pins arre thus able to handle tension and pull forces.

3.2 2.1 Memberrs Issue 3‐5: Wh hen construccting a trusss member or beam in a 2D plane thhe beam hass no need for stiiffness in the perpendiccular plane. However w when talkingg about 3D tru usses or beam ms they sho ould have sttiffness in bo oth directions, meaningg height in botth directions, consideriing the mom ment of inerttia of beamss. Fro om a basic m mechanical iinsight we leearn that th he bending m moment impplied in the stru ucture is maaximal in th he middle off the membeer whereas it is flexiblyy connected to thee nodes. Morre height is therefore n needed in the middle of the membeers rather th han in tthe endpoin nts. Forr this researrch parts we ere laser‐cu t from plasttic to be inse erted into eeach other 5 using an exact fit method . The resultt is a bidirecctional stiff beam, ideall for 3D plications. Itts connectio on however is still only y in one 2D‐p plane. app

Figu ure 76: Truss Member

Figu ure 77: Truss Member

Exxact‐fit method: The metho od of laser‐cuttting connecting parts with h attention to the thicknesss of the laser‐cut linee of 0.1mm. Interconnectingg pieces will then fit perfectly and providde a certain hicknesses chaange accordin ng to the speccific model). streength to the connection (th

3.3 3.2 Cladding Wh hen talking aabout viable e spaces wee cannot absstract the ne eed for a suiitable insulation and d airtightnesss that is avaailable in today’s performing skinss. Whereas new w materials and flexible e insulation ns are makin ng their way y into large sscale app plications, cconnection d details and p proper speccific sealants seem to bee lagging beh hind. Howev ver it is the writer’s opiinion that th hese materials will folloow when more praactical experrience is harvested with h regards to o cladding systems on kkinetic stru uctures. 1. Textile membranes Texxtile membrranes, which h are an obvvious choicee for waterproofing ourr kinetic stru ucture, can be insulated d. Tensothe rm (Birdairr n.d.) for ex xample is a fflexible com mposite insu ulated mem mbrane comp posed out of a layer of N Nanogel inssulation pro otected by tw wo layers off PTFE fiberrglass textilee. It has a re emarkable loow heat transmission, sstrong resisstance to im mpact damag ge and a very low own w weight. Neggative pointts might still be the inab bility to witthstand vandalism or cuutting. Texxtile membraanes can also be used ass a means to manipulate light levels. A stretched membrane will be more transparent thaan an un‐stre etched mem mbrane. For eexample whe en a stru ucture expan nds its surfacce, the membbrane will be e stretched, thus letting m more light in nto thee space.

Figu ure 78: Textile e membrane, Unstretched

Figu ure 79: Textile e membrane, Stretched

2. Stiff Cladding Issue 3‐6: Stiff cladding like wooden or metal parts can also be constructed. However when working in a 3D plane this cladding has to be constructed isostatic. When a cladding material moves out of his plane, as a result of the structural frame deforming, it introduces hyperstatic forces in the panels when they are simply fixed to a structure. The new connection is similar to an expansion joint for metal cladding systems which are influenced by their heat expansion coefficient. To research these phenomena a kinetic box was simulated consisting of one actuator in each horizontal face of the box. Scenario 1 shows what happens when the cladding plane is moved and scenario 2 shows us what happens when the cladding materials move out of the plan but stay connected to both upper and lower points on the frame.

Sceenario 1 sho ows us that sstiff claddin ng made of v vertical or h horizontal sttrips can ha ave thee ability to fo ollow the de eforming su urface when n it moves in n its own plaane. Suitable e rub bber fittingss should be applied betw ween two strips which are able to move along g theeir line and sstill apply su ufficient cloosing pressu ure. ere fixed to the lower fr frame memb ber. Instantlyy can be see en In sscenario 2 tthe strips we thaat the claddiing strips ha ave moved u upwards, in this example the midddle strip mov ves 18,,9mm, or 2% % of its leng gth, upwardss when the actuator in the other faace shrinks % of its own n length. 30%

Figu ure 80: Kinetic Box, Default Scenario

Figu ure 81: Kinetic Box, Scenarrio 1

Figu ure 82: Kinetic Box, Scenarrio 2

It iss thus impo ortant that connections are made w which are ab ble to withsttand these mo ovements du uring the acttuation of th he entire strructure. A m model has beeen made to o sim mulate this cconnection. When operaating this m model the mo ovement of the claddin ng was possible in n the same p plane. Howeever this joiint still resissted movem ment of the upp per beam ou ut of the pla ane. This du e to the straaight connection of the transverse pin n. Thiis can be sollved by repllacing the trraverse pin by a knuckle joint. A knnuckle jointt is a ball joint witth attached b bolt to applly a nut to faasten this cladding. Thiss also implies thaat the claddiing has to ha ave moving space betw ween the plane of the strructure and d thee plane of th he cladding tto allow thiss movementt.

Figu ure 83: Expansion joint Wo ooden claddinng

Figu ure 84: Ball jo oint (Kejia Industry n.d.)

3. Interacttive claddingg Interactive claddings follo ow the samee upper prin nciples whetther the claddding is stifff or fflexible. Diffferent exam mples are alrready availaable in the cu urrent IA laandscape, mo ostly withou ut discussing g the attach ment to a lo oad carrying g structure. This con nnection is h however an important aspect whicch involves a a lot of pracctical kno owledge likee aforementtioned. Thiss is howeverr obsolete iff the load caarrying stru ucture itselff is static. Pro ojects such aas Living Gla ass, which oopens creases in its clad dding as a rresponse to pro oximity, or tthe xeromax x envelope, w which is an elaborate conceptual ddesign for a liviing, self‐replicating skin n, are projeccts where th his is not fullly elaborateed in the wriiter’s opinio on.

Figu ure 85: Living Glass (The Livving n.d.)

Figu ure 86: Xerom max Envelope (Future Citiess Lab 2010)

3.3 3.3 Actuator design Acttuators in th his thesis arre mostly deesigned as liinear motion n mechanism ms, meanin ng beaams that can n contract o or expand th heir own len ngth to actua ate the entirre structura al meechanism. Th his is mainly y sufficient when descrribing kinetiic space truuss meechanisms, b but does nott imply thatt other actuaators must d do the samee. Acttuators havee a wide sco ope of drivin ng mechanissms involvin ng pneumattic, electrica al or eeven chemiccal processe es. A definin ng characterristic of thesse actuatorss is what torrque they caan resist and d how long tthey can shrrink or elongate their leength.

Figu ure 87: Rectan ngle, Diagona al Actuation

1. Musclee Wire Mu uscle wires tthat go by th he productioon names Sttabinol, Flex xinol and Niitinol are wirres based on n a Nickel allloy which ccan contractt up to 3‐5% % of its lengtth when heaated or cond ducting elecctricity. Issue 3‐6: Theese wires sh hould howevver be avoid ded most of the time. A muscle wire reaacts to heat aand its use iin for examp ple an interractive façad de will actuaate the muscle wirre thanks to o the sun witthout progrramming. Th his could be implementted as a passsive actuation but is m mainly uncon ntrollable by y other mea ans. uscle wires aalso have a p pull strength th of multiplle times their own weigght which Mu maakes them usseful in conttrolled sma ll scale appllications. Ho owever not in large sca ale outtdoor and laarge applied d forces app plication succh as buildin ng skins andd other stru uctural buillding concep pts. Thee physical environmenttal features and the small absolute e pull strenggth make the e usee of these wires thus no on‐existing iin the field o of KA.

Figu ure 88: Muscle Wire Actuation

2. Rotatio onal Actuato or Rottational actu uators are a already wideely availablee because of the naturee of the gen neration of m motion in ellectrical meechanisms. R Researched models are small‐scale e serrvo and step pper motorss controlled and fed by the Arduino o microconttroller. Thiis circular m motion howe ever can be changed into linear mo otion thankss to variouss meechanisms. T The most po opular have been researrched, inclu uding a crannkshaft meechanism, a screw mech hanism and a gear‐pinio on system. T These basic mechanism ms aree also widely y available iin different shapes and stroke leng gths availablle through pro ocess engineeering manu ufacturers. T Thanks to th his research h it became very obviou us thaat every mecchanisms ha as its own liimiting torq que and elon ngation ratee.

Issue 3‐7: A sccrew and ge ear‐pinion aactuator can n theoreticallly shrink byy up to 50% % of theeir total lenggth. In practtice though, all actuatorrs depend on their pracctical con nstruction. IIn this practtical researcch the rates were respe ectively 28% % and 48%. A ccrankshaft m mechanism ccan theoretiically expan nd a value eq qual to 2 tim mes the diaameter of the rotation le ever. There is however need for a g guide that sttiffens and allo ows the mov vement of th he expandin ng arm and therefore limits the tottal elongatio on of tthe actuatorr. The elonga ation of the test model is equal to 23%. Forr even larger actuation,, possibilitiees are telesccopically linear actuato rs or a wind dup meethod of a sttring, which are not res earched in tthis thesis. Thee torque is tthe force mu ultiplied witth the lever which is installed on thhe servomo otor. Theere is a large difference e in price an nd available torque of se ervomotorss. The right mo otor thereforre has to be calculated on the applied load or practically rresearched. Forr these expeeriments mo otors wheree used with tthe same ch haracteristiccs, which allo ows us to co ompare elon ngation ratees.

Figu ure 89: Screw w Linear Actuator

Figu ure 90: Cranksshaft Linear A Actuator

Figu ure 91: Gear‐P Pinion Linear Actuator

Meechanism Craankshaft Geear Pinion Scrrew Pneumatic mu uscle

S Shrink Rate [%]

Tab bel 9: Linear A Actuators, Shrink Rate

23 48 28 11

3. Hydrau ulic & Pneum matic actuattors Thee final group p consists o of pneumaticc and hydraaulic actuato ors. These arre actuatorss wh hich can contract due to o an air presssure or com mpressed liq quid. These actuators how wever are ab ble to withsstand great p pressure orr tension forrces, which, in the write er’s opiinion, makes them idea al for KA. Agaain, mechan nical processs engineerin ng firms hav ve large line es containinng both type es in aall shapes an nd forms. This thesis w will only reseearch one ex xample baseed on the Pneeumatic mu uscle of the F Festo Corpooration.

Figu ure 92: Muscle Project (Fessto Corporatee 2009)

Aftter reading aa dissertatio on on the an nalysis (Daeerden & Lefe eber n.d.) innvolving diffferent pneumatic musccle it was qu uite obvious that these m muscles weere not the o only typ pes availablee. Different ttypes of mu uscles have ttheir own ch haracteristiics, negative e and d positive asspects. Kibben type air muscle w was chosen. The McKibbben type is Forr this researrch the McK thee most widespread musscle, that ha s an easy in nstallation and still has performing g chaaracteristicss. Pleated Aiir Muscles ((PAM’s) have been researched at thhe Universitty of B Brussels on a theoretical and practtical level (V Van Mele 20 008). ner tube thaat does not Issue 3‐8: Thee McKibben air muscle consists of a supple inn ressist deformaation while u under presssure. The maaterial used d in this reseearch is silicone rubber. A braided d sieving willl however b be put on top of the innner tube whiich tigh htens when stretched. T This will ke ep the inner tube from deforming locally and failling under eeven a smalll air pressurre of 3 bar. T The total airr muscle is aa composite e wh here the braiided sieving g is ideal forr resisting p pull forces. T The total pulll resistance e beffore snappin ng is enormous (depen dent on typ pe), making it ideal for sstructural app plications.

Figu ure 93: McKib bben Principle e (Daerden & Lefeber n.d.)

Thee McKibben n air muscle has been reesearched u using a basicc setup to appply loads o on thee muscle. Th he elongation of the mu uscle was do ocumented w with every sstep of 0.5 b bar air pressure. D Different weights were cconnected tto the end of the musclee ranging from 1kgg to 5kg. The silicone tu ubing used h had a total d diameter of 15mm and a wall thicckness of 2m mm.

Figu ure 94: Test Setup

Figu ure95: McKibben air musclle setup

Thee muscle is controlled b by a 3/2 waay Festo air v valve which connects thhe muscle to o eith her the presssured air ta ank or the ooutside air. T This valve w was steered bby a solenoiid valvve on 12V, w which only h has a properr working range of 2‐8 bar, which makes the ttest ressults only av vailable from m that pointt on. Using aa Huntington n array as a a relay the Ard duino micro ocontroller w was able con ntrol the vaalve using a p pressure knnob or timerr. Thee maximum m pressure ra ange was prractically ch hosen at 5 ba ar. Since connnections a are weak points in n the setup, they could ssuddenly brreak withou ut notice. Thhere was also hange notice eable in thee change of llength after around 5 bbar. onlly a slight ch Tesst results on n the next pa age show uss the elongaation (positive) or shrinnk (negative e) relaative to its o original leng gth. The “Tootal Range” rrow shows u us the actuaation range of eacch load casee. Results vary between n 9‐11% of aactuation be etween its sttretched and acttuated stancce.

Figu ure 96: 3/2 Aiir Valve Festo

Figu ure 97: Arduin no Controller

Elongation[/] vs. Air Pressure[bar] Length/ Original length [/]

1,08 1,06 1,04 1,02

1kg

1,00

2kg

0,98

3kg

0,96

5kg

0,94

4kg

0,92 0,00 0,50 1,00 1,50 2,00 2,50 3,00 3,50 4,00 4,50 5,00 Air Pressure [bar]

Figure 98: Elongation/Original Length [%]

Druk(Bar) 1 kg 0,00 0,50 1,00 1,50 2,00 2,50 3,00 3,50 4,00 4,50 5,00 Total Range

2 kg

3 kg

4 kg

0,35

2,04

3,73

4,74

5,42

‐3,03 ‐4,72 ‐5,73 ‐6,74 ‐7,42 ‐8,09 ‐8,43 8,78

‐2,35 ‐4,04 ‐5,05 ‐5,73 ‐7,08 ‐7,42 ‐7,76 9,80

‐0,66 ‐1,68 ‐3,36 ‐4,38 ‐5,73 ‐6,74 ‐7,42 11,15

1,36 0,35 ‐1,34 ‐2,35 ‐3,36 ‐4,72 ‐5,39 10,14

2,04 0,69 ‐0,32 ‐1,34 ‐2,69 ‐3,36 ‐4,38 9,80

Table 10: Muscle Elongation [%]

5kg

3.3.5 Prototype Design 3.3.5.1 Introduction Flexible Skin As a summarization of practical knowledge this research ends with the design and creation of an Interactive Kinetic Structure. This prototype does not focus on documenting the social interaction with the structure, hence its social aspects, but documents its design process, production process and problematic issues. The prime conceptual idea behind the prototype is that of a flexible skin. A skin which is able to define architectural space on its own. A skin that responds to pragmatic data such as sunlight, proximity and touch. By doing so the inhabitant is no longer shielded from the outside, passersby or sunlight by a brick wall but perceives the space in an interactive way, constantly changing in time. While existing prototypes in the field of IA do not specifically mention the different levels of interactivity involving timespan, this research does. This research states that there are three different levels of interactivity: Direct, Weeks and Months. Most of the projects in the current landscape only involve direct interactivity. This prototype skin is comprised of the two first layers of interactivity, meaning direct interactivity such as daylight entrance and ventilation as well as defining its own behavior like shyness and aggressiveness based upon these pragmatic values such as proximity and touch. The second layer of interactivity, meaning the structural layer in this case, can form itself into an optimal space according to minimal internal stresses or spatial optimization. Both layers are aesthetically woven into each other unlike projects in the current landscape which mainly introduce either structural or direct interactivity. Issue 3‐8: Another fact that this research specifically mentions is the overall inability to incorporate two different levels while they are linked together with only one actuator. Meaning one actuator cannot be responsible for two levels of interactivity. For example, our need for daylight and ventilation does not coincide with our need for an optimal structure with minimal displacements. This insight only came after the practical issues during the actuator design.

Bio omimicry “B Biomimicry or biomimettics is the exaamination of of nature, its models, systtems, processses, an nd elements to emulate o or take inspiiration from in order to solve humann problems. The terms biomimicry and b biomimetics s come from the Greek words bios, m meaning life, and mimesis, m meaning to imitate. Otheer terms ofteen used are b bionics, bio‐iinspiration, a and biognosis.” (Wiikipedia 2011b) by nature in n the sense tthat the desiigner was inntrigued by Thee design waas inspired b corrals and und derwater po olyps. Seemiingly monottone and sta atic these poolyps can chaange their sh hape and fo orm under d different con nditions. Pollyps can rettract when tou uched by an unknown e entity or can n open up to o catch suste enance. Thiis like our fllexible skin that also haas to catch ssustenance llike daylightt and ven ntilation butt also intrigues people w with its inteeractivity an nd responsee to touch orr pro oximity. It iss for this rea ason that th e design of the actuator is based uupon the form of aa polyp and delivers the e primary laayer of interractivity.

Figu ure 99: Underrwater Polypss (National Geeographic n.d.)

3.3 3.5.2 Resultts Design Thee axonomettric view sho ows the dessign split up into the tw wo different llayers. The pollyps, layer 1 1, and the tru uss, layer 2.. Both of thee layers are independenntly actuated. Thee truss actuation is not physically b built but wiill depict a ccertain snappshot of its acttual behavio or. Besides th he polyps an nd truss a ccladding will be fitted too the outer surrface to prov vide protecttion but alsoo to serve ass a touch sensor. Thee cladding ttogether witth the outerr polyp armss will be colored black. The entire stru ucture of po olyps and truss membeers are madee out of Plex xi‐Glass of 22mm, laser‐ccut into o its form. W When the po olyps are op pened they w will allow da aylight and//or ven ntilation. Daaylight dispe erses over th he transparrent surfaces, illuminatiing the inne er spaace.

Layer 1, Polyps Direct in nteractivity:: Daylight, v ventilation Actuated d by electriccal servo Mo otor

Layer 2, Truss Medium m Interactiviity: Optimal structural form Actuated d by linear aactuators (Not mo odeled in thiis prototype e)

Figu ure 100: Axon nometric View w Prototype

Figu ure 101: Proto otype, 3D Ske etch

Pollyp Thee design of tthe polyp acctuator usess the “Scotch h Yoke”, a ca am mechaniism, to transform the rotational a actuation of f the servo m motor to a linear motionn of polyp arm ms moving in and out of the skin. T This mechan nism exists o out of two gguides and a a mid ddle beam, ““yoke”, whicch is attacheed to the eleectric motorr. As shown in th he lower figu ure the yokee transform ms into four sseparate poolyp arms wh hich allow th hem to move e when movved out of th he skin. Each h arm is helld out of its norrmal configu uration by ttransparent strings, mim micking the e appearanc e of an und derwater po olyp. Sim mulation of tthis movement is possi ble but not necessary b because of tthe minor diffficulty of the system an nd since therre are no exxternal loads placed on the meechanism. Th he outer she ell of the acttuator provides the neccessary stifffness for use e in thee truss as a m member. Th he shape of tthe outer membrane follows the innterior meechanisms as well as the e optimal sttructural forrm for a truss member, meaning th he larggest bendin ng moment o occurring in n the middlee of the mem mber.

Figu ure 102: Scotcch Yoke Mech hanism (Mechhanisms 101 n n.d.)

Figu ure 103: Polyp p Actuation, 3 3D Sketch

Figu ure 104: Polyp p Actuator

Figu ure 105: Polyp p, Upper node e connection

Issue 3‐9: Durring constru uction of thee entire prototype it became obvioous that the pollyps connection to the ttruss memb bers was nott sufficient tto provide ppull strength h. Maaking the strructure unsttable and boody parts faalling out of their approopriate slide e. To provide theem with the necessary p pull strength h, all of the body parts were con nnected thro ough plasticc wire. Makiing the nodee connection n able to wiithstand pulll forces and act as presume ed in the dessign. Thiis is mainly due to the ffact that thee exact‐fit m method used for laser‐cuutting the parrts was not aaccurately ccalculated too provide th he necessary y pull resisttance by she ear.

Tru uss Members of th he truss are reinforced iin both direections for th he occurrin g bending mo oment, which is maxima al in the mid ddle of the ttruss member. This joinnt design, wh hich is fairly easy to produce, was th he limiting factor in the e search forr a valid trusss sysstem. Truss members co ould only m move in the 2 2D plane the ey have beenn connected d in. Issue 3‐10: On ne of the first truss dessigns was a 2 2D simulation where thhe actuator stilll actuated tthe polyp an nd the truss and where a series of rrectangles w would provide mo ovement of tthe skin. However when n simulating g the structu ure in 3D it became obvvious that nodes and in nterconnectiing memberrs would mo ove out of thhe plane the ey were connecteed. The consstruction wiith 2D jointss, is thereforre not possiible. Meanin ng nod des would h have to be off the 3D prin nted ball joiint type men ntioned beffore. Becausse of tthe unknow wn material sstrength an d cost of thee 3D print, tthis researc h chose to seaarch for an aalternative d design wherre truss mem mbers would only movee in the plan ne theey are conneected in.

Figu ure 106: 2D Siimulation, De esign 1

Figu ure 107: 3D siimulation, Design 1

By simplifyingg the truss to o a space tru uss of rectangles and diagonals a ssolution wass fou und. The diaagonals placed in each rrectangle of f the space truss can be actuated. Wh hen the actu uator elonga ates the recttangle will d deform and will heighteen the upper con nnected nod de while shrrinking in th he other cardinal directtion. For thiss prototype a grid d consistingg of nine nodes (polypss) will be creeated and siimulated. Too move one nod de of the griid in the upp per directioon surround ding diagona als must be pointed tow wards it. Wh hen all surro ounding actu uators are g given the same elongatiion the poin nt willl move verttically upwa ards. A smalll shrinkage of the skin will occur inn the other directions to aallow the mo ovement of tthe node.

Figu ure 108: 2D siimulation, Design 2

Diaagonals can be placed in n a pattern sso that everry couple off two nodes can deliver upw ward and do ownward m movement. Following fig gures repressent a simullation made e on a grrid of nine n nodes in a specific stan nce. This stance will also o be appliedd in the final pro ototype, by u using stiff d diagonals wiith differentt lengths and not by acttuators.

Figu ure 109: 3D siimulation, Design 2

Figu ure 110: Trusss assembly

Claadding Thee cladding ffor the proto otype is inteended to shiield sunlight from the innner space, increasing the effect of the e opening p polyps, and tto be as ligh htweight as ppossible. Theerefore a claadding mate erial of pain nted plastic was chosen n. However tto provide th he clad dding with a large stiffn ness but at the same tim me maintain n a low weigght of its ow wn, thiss research cchose parts which weree vacuum formed6 to create stiffer ccladding sheeets through h their three e dimension nal form. Th hese claddings were theen painted blaack to provid de the light shielding efffect. Another design re equirement of the clad dding was tthat it could d be used in the chosen truss rectan ngle truss syystem and tthat if o one node of tthe rectangle should m move upward ds that the interlaying ccladding cou uld cop pe with the movement. Bassed on seem mingly rando om patternss occurring in nature th he designer sketched a ran ndom contin nuous interssecting line.. This line w was then tran nsformed innto a pattern n wh hich was laseer‐cut onto a sheet of M Medium Den nsity Fiberboard (MDF)) of 6mm.

Figu ure 111: Laserrcut Vacuum Forming Moldds

6 Va acuum form ming, commo only known as vacuufo orming, is a ssimplified vversion of theermoforming, whereby a sheet of p plastic is heaated to a forrming tempeerature, streetched onto o or into a siingle‐surfacce mold (BrE E, mould), and held agaainst the mo old by applying vaacuum betw ween the molld surface aand the shee et.(Wikipediia 2011c)

Forr the vacuum m forming p process, an ooperating bo ox was prod duced consissting of sucction holes o on the top, b based on thee dimension ns of the pla astic sheets,, and an insertion point for a vacuu um cleaner, providing tthe vacuum needed to fform the plaastic.

Figu ure 112: Vacu uum Former w with mold

ming would aalso have beeen used forr the polyp aarms. The Issue 3‐11: Vaacuum form mo old, that has been CNC‐m milled out oof a piece of cellulose, h however wass too high fo or thee plastic cau using it to loosen from i ts frame and annihilate e the vacuum m effect. The plaastic dimenssions are to be chosen i n accordancce with the height of thhe mold.

Figu ure 113: Vacu uum forming rresult with higgh mold

Issue 3‐12: Th he dimensio ons of the vaacuum box w were limited d to the surfface of the laseer‐cutter, m meaning 600 0x300mm. T This vacuum m box thereffore limited the size of tthe plaastic sheets u used to 250 0x250mm an nd thus also o limiting th he cladding tto 190 0&190mm. If larger vaccuum formeers are availlable the cla adding and tthus dim mensions of f the truss arre possible. This is not the case however durinng the desig gn of tthis prototy ype. Issue3‐13: Th he pattern off the claddin ng, each of tthe four rectangles, wass triangulatted, meeaning cut ov ver both of its diagonalls. This wou uld allow mo ovement of eeach con nnected nod de, while still maintainiing cladding g integrity. C Cladding seaams are con nnected to eeach other u using a plasttic one direcctional hinge.

Figu ure 114: Cladd ding, Upper V View

Figu ure 115: Cladd ding, Lower V View

Behavior Various sensors were implemented into the flexible skin. Piezo elements capable of measuring impact or shocks were glued to the cladding, transforming the cladding to a touch sensitive surface. One light sensor was attached to measure daylight levels, so that the polyps could respond accordingly. Since the 9 nodes of the prototype lie close to each other there is no need for installing 9 independent sensors. However in reality these are supposed to be installed. Each of the polyps then reacts to its specific sensor, transforming the flexible skin into a visualization of the incident solar radiation. Finally two infrared sensors were also implemented on the surface of the cladding, measuring the proximity of objects towards the skin. The polyps can thus react and interact with passersby or could shy away from them to maintain inner space privacy. The same principle goes for the implementation of multiple infrared proximity sensors so that the polyps will act more autonomously and in at a greater resolution. As a means of prototyping the polyps furthest away from each other will be driven by a separate infrared sensor. And the middle polyps will be driven by an averaged value of the 2 infrared sensors. All of the programming7 was done in Arduino environment based on Processing. Sensor Light Light

Action Behavior Polyps Open Polyps will catch daylight dispersing it over its structure. Polyps Close Polyps will block daylight to intervene in its inner space. Polyps will shy away from interested people, opening again over Touch Polyps Close time. Polyps will be eager to respond to interested people. Conversing Touch Polyps Open with the person in front of it. Proximity Polyps Close Polyps will shy away from passerby's. Proximity Polyps Open Polyps will affirm passerby's, luring them closer Table 11: Polyps Behavioral Scheme

Appendicx B: Behavior Arduino code

Figu ure 116: Built‐In Opto‐Resistor

Figu ure 117: Built‐In Piezo Elem ment

Figu ure 118: Built‐in IR Sensor

Figu ure 119: Proto otype Side‐View

Figu uur 120: Proto otype Side‐View

Figu ure 121: Proto otype Perspecctive View

Figu ure 122: Proto otype Upper V View

Chapter 4: Evaluation & Discussion 4.1 Evaluation & Discussion Simulating Design 4.1.1 Simulation Case Studies The simulation of kinetic beam structures is possible with the Grasshopper environment. The component Kangaroo uses a spring based model where nodes are considered as discrete points and beams are modeled as springs with the appropriate stiffness. Actuators are springs with adjustable rest length. This research however did not implement a change in spring stiffness involving actuators. When the rest length of an actuator changes, its stiffness is supposed to change according to the stiffness formula E*A/L, when abstracting the actuator as a truss member with constant cross section. An actuator could also have a different stiffness behavior since its cross section is not constant over its length. Further research could analyze different actuators and their stiffness behavior over its stroke, to implement in Grasshopper as an accurate stiffness function. Kinetic structures only made of truss members, actuators and anchor points fixed in time and space can be implemented, when the basic skillset involving Grasshopper and Kangaroo is available. Bending can also be implemented on two coupled lines to simulate hinged nodes. However Kangaroo lacks the necessary documentation explaining the used units as bending strength. The Grasshopper environment together with Kangaroo is not a commercial package. It is also not intended to be a theoretical calculation package. Therefore understanding Grasshopper only for the use of displacement calculation is not meant as a basis for further research. This package however provides the simulation environment with easy to use kinematics where the user can have total, visual, control over its design. Further research can however take a deeper look into the exact programming of Kangaroo and improve or add components where necessary.

Thee main prob blem when u using Kangaaroo is its cu urrent inabiility to introoduce rolling g guiides, meanin ng anchor points attach hed to a specific line or surface. Thhese rolling guiides form th he basis for n numerous kkinetic strucctures, mean ning a part oof kinetic stru uctures can n still not be simulated. ngaroo is co ontinuously b being develooped as we sspeak. It hass been annouunced that Kan imp plementatio on of the rollling guide iss to be introd duced in the next releasee of Kangaro oo and d should pro ove to be a big improvem ment in this package’s siimulation caapacity. In th he meantime simu ulating rolling guides byy variable pull forces towards inters rsecting plan nes is a an elaboratee and inaccu urate solutioon.

Figu ure 123: Simu ulation Flexible Tower

Figu ure 124: Simu ulation of the Expanding Geeodesic Dome e

4.1.2 Numerical validation Kangaroo is quite accurate for simulating non‐dynamic structures. A comparison study in displacements, comparing Kangaroo and ANSYS, shows that the averaged error margin of Kangaroo is only 0,1% of the ANSYS result. When simulating a dynamic structure, meaning an actuated structure, Kangaroo is not as accurate based on the comparison results. Displacements found by Kangaroo have error margins of 316% maximum. However this does not prove that Kangaroo is not suitable for the simulation of KA. In ANSYS the actuator was modeled as a truss member with an initial strain. In Grasshopper it was modeled as a spring with variable rest length. Changing stiffness and other factors could play a part in these end results, as discussed before. Non‐linear analysis in ANSYS and further research would be conclusive. Since the difference in results are small in absolute value this research however states that Kangaroo is a valuable early simulation package and will improve or justify its results in further research. Node X Direction Y Direction Node X Direction Y Direction 1 0,0 0,0 1 0,0 0,0 2 0,0 0,1 2 ‐105,7 21,3 3 0,1 0,1 3 ‐111,2 9,4 4 0,1 0,1 4 316,2 ‐2,7 5 0,1 0,1 5 247,3 ‐17,4 6 0,0 0,1 6 206,7 ‐28,0 7 0,1 0,1 7 159,0 ‐33,0 8 0,1 0,1 8 128,0 ‐38,1 9 0,1 0,1 9 106,4 ‐45,4 10 0,0 0,1 10 90,6 ‐59,7 11 0,0 0,0 11 0,0 0,0 12 0,0 0,0 12 0,0 0,0 13 0,0 0,1 13 62,6 30,8 14 0,0 0,1 14 70,5 13,4 15 0,0 0,1 15 79,0 17,6 16 0,0 0,1 16 ‐132,0 ‐18,8 17 0,0 0,1 17 ‐120,8 ‐29,1 18 0,0 0,1 18 ‐112,2 ‐33,7 19 0,0 0,1 19 ‐104,8 ‐39,0 20 0,0 0,1 20 ‐97,9 ‐46,9 21 0,0 0,1 21 ‐91,4 ‐65,7 22 0,0 0,0 22 0,0 0,0 32,8 ‐20,3 0,0 0,1 Table 12: Error Margin %, Default 5kN Table 13:Error Margin %, 5kN

Wh hen analyzin ng the intern nal stressess of the diffeerent calcula ations it cann be seen tha at thee results in A ANSYS calcu ulate tension n in the upp per left corner, where K Kangaroo calculates neutral or posittive interna l forces. Thiis result is ccaused by the way actuaation is impllemented in each simulaation softwa are: Kan ngaroo simu ulates a spring with variiable rest length and a rrelatively la rge stiffnesss, whereas actuation in ANSY YS is inserteed as a differrent constan nt set. The innitial strain con nstant of thee specific meember is inseerted into th he simulation program. Thee simulation n by Kangaro oo can be seeen as a non‐linear soluttion becausee of the iterrative process of its simu ulation engiine. A non‐liinear solutio on will produuce an appliied ben nding momeent thanks to o the angle w which the trruss memberrs has been pplaced in. A ben nding momeent will imply ly two oppossite fixed end d moments llike shown bbelow. n by ANSYS w will keep thee initial strain constant during the eentire Thee simulation sim mulation, meeaning no exxtra strain w will occur oth her than the e initial straiin. This is allso nott the case in reality, whiich Kangaro o simulates better by on nly changingg its rest length butt still being a able to elong gate accordding to its stif iffness.

Figu ure 125: Simu ulation Grassh hopper, 0kN, A Actuated, Defformation Sca ale 1:1

Figu ure 126: Simu ulation ANSYSS, 0kN, Actuatted, Deformattion Scale 1:1

4.2 2 Simulatiing behav vior Usiing the Ardu uino microcontroller an nd the comp ponent Fireffly In the Grrasshopper envvironment, ssensor data a can be read d directly frrom the board and usedd in the sim mulation of K KA. The actu uation of thee kinetic strructure is on nly based onn the differe ent varriable length hs of its actu uators. Baseed on the incoming data a these lenggths vary. Dirrectly remap pping the da ata values too the strokee range of th he actuator ccan be easily y imp plemented iin the Grasshopper envvironment u using the Firrefly componnents. Meaning pragm matic sensor values can n be directly y linked to the actuationn of differen nt acttuators. Thiss method is named Swaarm Intelligeence. Humanistic data ccannot be stored in numb bers and thu us cannot b e implemen nted in the a above methood. Cen ntral intelliggence on the e other hand d is a coordinated actuation of all oof the acttuators baseed on a coup ple of sensorr values nott necessarily y linked to eeach resspective cell. Central inttelligence caan be implemented usin ng either thhe integrated d Gallapagos Opttimization Solver and/oor programm ming in exte ernal languaage C++ and d VB. Thee optimizatiion solver can be used w when optim mizing a specific value ssuch as displacement, distance orr internal forrces. Human nistic data ssuch as skel eton mented by p programminng in an reccognition orr RDIF readings can onlyy be implem extternal langu uage.

Figu ure 127: Optim mizatin, Kinettic arch movinng towards po oints

Besides central intelligence being more accurate than swarm intelligence, which was found in the compared results of a basic simulation, the end actuation is also dependent on the iterative process of the optimization solver. This was not visible in the first simulation, minimizing the distance towards a point, but was in the second simulation when minimizing the internal forces. This problem will always occur when using evolutionary solvers and their iterative process. However results show that different actuation end results give the same end value. Problems are likely to arise when more complex simulations will lead to different end results with major differences the end result. Therefore optimization solvers are to be handled with care and researched when implementing in a final design. Actuator

Intelligent 1 1 2 3 4 5 6 7 8 9 CP

Difference

Intelligent 2

0 0 18 20 19 0 7 10 0 0,565594 0

Intelligent 3 0 0 20 20 20 0 9 4 0 0,565594 0

Swarm

0 0 8 20 19 0 3 0 0 0,565594 0

Tabel 14: Optimization results versus swarm implementation, Simulation 1

7,93 12,58 17,68 20,00 16,76 11,51 7,12 3,25 0,00 0,565692 9,8E‐05

Actuator

Intelligent 1 1 2 3 4 5 6 7 F*L

Intelligent 2

1 0 ‐3 0 0 0 0 0,000033

Intelligent 3 1 0 ‐3 0 0 0 0 0,000033

Tabel 15: Optimization results, Simulation 2

1 0 ‐3 0 0 0 0 0,000033

Grasshopper is not only interesting for the simulation of kinetics, this free and open coding environment makes way to different protocols that can be used in combination with upcoming humanistic as well as pragmatic sensors. For further details involving subjects such as the emotive layer and behavior we refer to the chapter methodology and results in question. It is the writer’s opinion that Grasshopper provides and will continue to provide a valuable environment for the simulation and design of Interactive Architecture.

4.3 3 Design IIssues 4.3 3.1 Joints 4.3 3.2.1 2D Joiint In ggeneral it caan be stated d that modelling 2D joints moving in n their ownn plane are eassier to build d than a 3D n node conneccting memb bers in differrent directioons in 3D spaace and allow wing the ne ecessary deggree of freed dom. A node e combiningg two 2D joiints is p possible when at least tthree memb bers connectt with the node, fixing iit in space, a and wh hen the trusss members do not move ve out of their 2D plane.. Wh hen designin ng 2D jointss the limitingg factors are the streng gth of the traansverse con nnecting pin n and the he eight of the ccombined connecting m members at the inteersection po oint. To avoid eccentriccity in the 2D D structure,, causing it tto break the e join nt or move o out of the 2D D plane, a syymmetricall attachment has to be uused. Sym mmetrical connections will providee a balanced d node with hout eccentrricity. Nodes should be designed d to be stablle, meaning 2D joints allways need to be con nnected in the intersectting point o f the truss m members. Ev ven when thhree membe ers aree connected to such an u unstable noode, it becom mes unstable and unablle to be placced in aa kinetic strructure.

Figu ure 128: 2D Tu urning Joint, w without eccenntricity

Figu ure 129: 2D unstable joint

4.3 3.2.2 3D Joiint Diffferent 3D nodes were m modeled in tthis researcch. When disscussing theese nodes theere is a substantial diffe erence betw ween the con nnection bettween two m members, wh hich can be m modeled ide eally with an n intersectio on point, an nd the conneection bettween moree than two m members. W When conneccting more tthan two meembers which aree able to move in a large e angle relattive to the n node this ressearch statees that this iis onlly possible w when using a multiple b ball joint no ode. Thee universal jjoint or Cardan‐joint coonsists of tw wo symmetrrical pins prroviding exccellent behaavior withou ut eccentriciity and still placing the node centeer directly att thee intersectio on point of tthe two conn necting mem mbers. Durring the 3D printing of tthis node th e first modeel broke at th he center crooss. This was ma ainly due to tthe lack of m mass for streength and sttiffness but a also becausee of the cha aracteristicss of the 3D printer itself.f. 3D printing g works by layering plasstic string on top p of each oth her. In the peerpendicularr direction o of the layers the model is is relatively frag gile, which ccaused it to slide/break k from its forrm. Solutionss are strenggthening the moodel but also printing the model in aaccordance tto its layerin ng, avoidingg crucial poin nts in tthe perpendicular direction of the pprinter.

Figu ure 130: 3D‐print Universal Joint 2

Thee concept baall joint wass designed b by the writeer. It was forrmed by pla cing ball joiints in ccardinal directions of a larger ball‐‐form node. When this node is con nected by mo ore than threee truss members it is ffixed in 3D sspace and a able to fulfilll its role in Kin netic Architeecture. Also the dimenssion of the ttotal node has to be muultiple times smaller than th he order of length of th he truss mem mbers. Furrther researrch and FE‐a analysis of thhe ball subjeected to push h and pull foorces will show cru ucial breakin ng points in the model, pproviding th he design mo ore optimal fforms. A cru ucial point w would be the outer rim w which keeps the ball join nt in place w when pull forrces aree introduced d. Thanks to multiple ba ll joints placced in this outer rim, thee mass is min nimal at tho ose points an nd could leadd to failure//breaking off the outer laayer. Push forcces do not seeem to cause a problem m since sufficcient mass is available inn the body off thee node.

Figu ure 131: 3D printed Ball Joint, Section

4.3 3.3 Memberrs Tru uss memberrs used in a 3D structurre, connecteed by a 2D or 3D joint, hhave to be streengthened iin perpendicular directtions, to pro ovide stiffne ess in all direections. Theese parts can n be easily cconstructed by inserting g laser‐cut parts into eacch other. Byy enllarging interrconnecting parts by haalf of the cuttting‐line thiickness, theyy fit into eacch oth her providing g a suitable connection without exttra material. This methood was also useed when producing the ffinal prototyype.

Figu ure 132: Trusss Member

4.3 3.4 Cladding Claadding of kin netic frame structures iis a necessaary step for m making our r newly dessigned spacees viable. Att the time off writing, ellastic cladding such as m membraness can n already bee insulated, even provid ding different densitiess when strettched to allo ow mo ore or less light into the e space. Exceept for the cconnection d details of m membranes theeir implementation is re elatively eassy by using stiffened metal rings inn reinforced d parrts of the meembrane. wever can also be used aas cladding and could a also be insullated like Stifff parts how san ndwich paneels consistin ng of two layyers of metaal glued to a a stiff insulaation. Howev ver wh hen designin ng a cladding g system on n a kinetic sttructure, in which a claadding plane e mo oves out of itts original p plane, necesssary steps h have to be ta aken: Knuckkle joints em mbedded in tthe upper orr lower trusss element w which attach h the claddinng isostatically allow the neccessary degrree of freedom. The neccessary freeedom of the nnection point has to be e researche d and simullated before ehand. con adding. Knucckle joints Thee lower figurre depicts the isostatic coonnection off the stiff cla how wever have n not been imp plemented inn the physica al test but ha ave the samee physical app pearance of a nut and bo olt, only attaached to a ba all joint built in the beam m to which tthe clad dding is connected. The exact degre e of freedom m should be ssimulated ussing the neccessary softw ware.

Figu ure 133: Kinettic Box, Scena ario 2

Figu ure 134: Expansion joint W Wooden claddiing

4.3 3.5 Actuator design Acttuators are aavailable in all sorts of types, driviing mechaniisms or drivving forces. In thiss thesis lineear actuatorrs were reseearched, whereas this does not impply that all K KA hass to be actuaated by linear actuatorss. The impleementation of rolling guuides in the e form of lines aand planes w will allow m ore compreehensive structures. Mu uscle wire, th he smallest in the familly of linear aactuators, iss not suitablle for KA beccause of its rrelatively sm mall strengtth, unsuitab ble for buildiing loads, annd its dep pendence on n physical fa actors such as external heating. uators are w widely availaable in diffeerent sizes, a available strrength/torq que Rottational actu and d speed. A n number of basic mechan nisms to traansform the rotational m movement into o linear mov vement werre introduceed and builtt to measure e the practiccal elongatio on rate of these m mechanisms. fferent mechanisms weree used but fuurther researrch could im mprove or dessign new Diff mechanisms wh hich allow bigger actuattion rates where needed d. Pneeumatic and d hydraulic muscles aree the final ty ypes of linea ar actuatorss, proving to o be verry easy to prroduce and capable of ccarrying relatively large e loads in teension. hanks to thee setup of thee muscle. The McKibben air muscle cconsists of a Thiis ability is th siliccone tubing which deforrms under aiir pressure a and a strong braided outter sleeving prooviding tensiion strength.. Obviously tthe muscle iss unable to rresist push foorces, and theerefore canno ot be used ass such in a kkinetic structture. The bra aided sleevinng is also neccessary in the setup of th he McKibbenn air muscle tto avoid loca al deformatiions of the siliccone tubing causing the muscle to faail. Desspite this strrength the m muscle can onnly contract up to 10% o of its originaal length, whereas rotatio onal/ linearr actuators ccan contract up to 48% a and can resisst push and ording to thee strength off the electriccal motor. pulll forces acco Meechanism S Shrink Rate [%] Craankshaft 23 48 Geear Pinion 28 Scrrew 11 Pneumatic mu uscle Tab bel 16: Shrink Rates of diffe erent actuatoors

Figu ure 135: McKiibben air musscle setup

100

By looking at the test results of the McKibben air muscle this research recognizes the fact that the air muscle has a variable elongation rate according to the applied load. There even seems to be a maximum value at 30N. This effect was not examined further but is likely to be caused by different material strengths and properties like strength of the specific braided sleeve and silicone tubing. Additionally parameters such as the wall thickness, length or diameter of the silicone tubing used could lead to these findings. Further research, documentation and examination of material strength should provide conclusive insights.

Elongation[/] vs. Air Pressure[bar] Length/ Original length [/]

1,08 1,06 1,04 1,02

1kg

1,00

2kg

0,98

3kg

0,96

5kg

0,94

4kg

0,92 0,00 0,50 1,00 1,50 2,00 2,50 3,00 3,50 4,00 4,50 5,00 Air Pressure [bar]

Figure 136: Elongation/Original Length [%]

Druk(Bar) 1 kg 0,00 0,50 1,00 1,50 2,00 2,50 3,00 3,50 4,00 4,50 5,00 Total Range

2 kg

3 kg

4 kg

0,35

2,04

3,73

4,74

5,42

‐3,03 ‐4,72 ‐5,73 ‐6,74 ‐7,42 ‐8,09 ‐8,43 8,78

‐2,35 ‐4,04 ‐5,05 ‐5,73 ‐7,08 ‐7,42 ‐7,76 9,80

‐0,66 ‐1,68 ‐3,36 ‐4,38 ‐5,73 ‐6,74 ‐7,42 11,15

1,36 0,35 ‐1,34 ‐2,35 ‐3,36 ‐4,72 ‐5,39 10,14

2,04 0,69 ‐0,32 ‐1,34 ‐2,69 ‐3,36 ‐4,38 9,80

Table 17: Muscle Elongation [%]

5kg

101

4.3 3.6 Prototyp pe Design Design & Poly yp Thee first conceeptual desig gn was a sin gle actuatorr that could actuate thee first layer of inteeractivity. T This first lay yer was defin ned as a structural fram me together r with the pollyps and stilll needing th he support oof a load‐beearing structture (layer 22) which wa as acttuated and ccontrolled by other actu uators and d data. When designing thhe actuator thee designer quickly came e across diffferent physiical complications and iissues which cou uld not be ov vercome. Thee first actuaator form alsso did not p perform optiimally regarrding internnal forces. Itts phyysical design n of elongatting at one eend and stay ying fixed att the other eend made itts form not optim mal involving bending m moment intrroduced at tthe middle aand at the con nnection point at the co onnection beetween layeer one and layer two, w which were dessigned separately in thiis preliminaary idea. Bessides the ph hysical desig gn, the electtrical motorr that should d have been implementted was also not sttrong enoug gh to carry tthe introducced loads off the entire sskin structu ure. Insstead of overr‐dimension ning one eleectrical motor, the meth hod of dividiing the laye er into o two structturally sepa arate layers was the obv vious choice e. Thiis was the confirmation n but also th he practical insight thatt flowed outt of the design: thaat different llayers of intteractivity c ould not be actuated by y the same aactuators. Layyers can be aesthetically interwoveen but cannot be actuatted by the saame meechanism.

Figu ure 137: Sketcches Polyp, Design 1

102

Thee second an nd final desig gn used thiss insight and d decoupled d both of thee layers. The seccond layer n now provide es structurall stability an nd the polyp ps provides the first lay yer of iinteractivity y, allowing d daylight entrrance and/o or ventilatio on. Both layeers are inteerwoven bu ut actuators work comp pletely indep pendently and can also be dim mensioned o only on their layer. Servvo’s with low w torque could then be used for the pollyps, on whiich no exterrnal loads arre being placed. The shell of the poolyps acts ass a tru uss member which prov vides stabilitty and neceessary streng gth towardss the middle e for the occurriing bending g moment an nd normal fo orces. Thee separate p polyp arms a are supposeed to disperrse from the center wheen fully exttended. Thiss was suppo osed to be poossible by aattaching pla astic stringss to the endss to work as a sprin ng holding tthem back. T This implem mentation proved to bee very difficu ult and d caused thee arms to brreak when ttensioned to o hard. Anotther possibiility is to dessign the poly yp itself to sspread the p polyps armss when fully y extended, bby laser‐ cuttting the holles for the arms at the yyoke closer to each other.

Figu ure 138: Polyp p Actuator

Figu ure 139: Proto otype Perspecctive View

103

Tru uss & Cladd ding Wh hen designin ng a structure which is kinetic, a su uitable conccept for the cladding is neeeded in the earlier phasses of the deesign. The d design of the e cladding w will have imp plications on the structtural frame b below. One basic insigh ht was gaineed in this ressearch. Whicch is that on nly triangulaated surfacees are able to move togeether with nod dal displaceements and can thus forrm a basic id dea to begin n designing structural clad dded frames. In tthe productiion of this prrototype thee cladding w was designed d after the sttructural frame. Like sho own in the prototype thee rectangula ar cladding p pieces, base d on the ame, were cu ut up after ttheir producction. Meaning the trianngulation that recctangular fra wass necessary ffor nodal movement waas not thoug ght of in the design phasses. By using g thiss insight to rredevelop th he same flexiible skin, thee use of a triiangulated fframe would d havve been morre optimal. Claadding surfaaces could also not be aattached to n nodal pointss. The prelim minary con ncept was to o attach the cladding su urfaces to th he nodes and not to thee truss meembers with h the use of ssimple hingges which arre able to move in one ddirection. How wever when n one of two o neighborin ng nodes (trriangulation n) changes iits height, th he nod de in question and its cconnecting ccladding mo oves in a direction otherr than that maade possiblee by the hing ge. It is for tthis reason that the con nnection of tthe cladding mo oved to the ttruss members instead of the nodees.

Figu ure 140: Cladd ding Hinge, Trruss member connection

104

Vaccuum formin ng is a greatt way of intrroducing 3D D form into a simple plaastic sheet. Thiis stiffens th he plastic sh heet, combin ning strengtth and low o own weight.. When usin ng thee vacuum forrming proce ess, the setu up needs to be of sufficiient dimenssions to pro ovide claddiing with the e appropriatte dimensions. Cladding g which is hhad internal seaams lead to w weak pointss in the clad dding design n. Alsso molds wh hich are used in vacuum m forming sh hould be chosen wiselyy. A higher mo old will utilizze more pla astic, causingg the plasticc to loosen ffrom its fram me, elim minating thee vacuum efffect undern neath. Wh hen large, meaning high h, molds are used in the vacuum form ming processs it best tha at a setu where an movable heatinng element iis used to pla ace over thee vacuum up is used w form mer. This wa ay the vacuu um forming process willl be slower b but successfu ful in using a a hig gher mold. T The original p plate also haas to be dim mensioned to o allow the hhigher defformation.

Figu ure 141: Vacu uum Forming results with hhigh mold

105

Behavior Behavior was programmed using the Arduino programming language8, which is based on Processing. During development and end use it became obvious that smoothing methods have to be applied on incoming sensor data. Pragmatic data such as proximity, delivered by an IR (beam) sensor, introduces, thanks to the nature of its sensor design, a particular noise onto the data stream. This has to be smoothed out to overcome the effect of “twitching” actuation. The used smoothing function sums up an amount of measurements with a delay and divides them by their amount. Causing the data stream to be flattened out to reduce major spikes. The servo motors used (Hextronik HX550) moved in an arbitrary direction every time the programming was uploaded to the Arduino board. This twitch caused the servo to move out of the range, enabled by the mechanism, causing failure of the lever connecting the motor with the mechanism. This however was overcome when moving the servo to a known in‐range position at the time of declaration in the programming. The used Motor library used in the Arduino programming environment is also only able to actuate 8 servo motors.

Appendicx B: Behavior Arduino code

106

Wh hen uploadin ng the first tests of the behavior to o the Arduin no board, th e servo mo otors began to twitch. A After furtherr research th he Arduino programminng began to o resstart following the actua ation of the servo moto ors. This was due to thee fact that th he Ard duino board d connected to a USB poort was not able to supp ply the neceessary powe er to aactuate eigh ht servo mottors. An add ditional 9V b battery was attached too the Arduin no boaard to succeessfully actu uate every seervo motor. This was th hus not caussed by faulty y pro ogramming. Acccurate meassurements off the energy consumptio on showed th hat 8 servo m motors duriing acttuation could d consume u up to 2000 m mA. The USB B port powerring the Ardduino board wass only deliveering about 500 mA. Th e extra batttery or external power ssupply with tthe neccessary speccifications was able to deeliver that a amount of cu urrent.

Figu ure 142: Ardu uino powered by USB and 99V battery

107

Chapter 5: Conclusion This research concludes with the summarization of different results and practical insights involving Kinetic Architecture, modeling design and behavior.

5.1 Simulating Design Kangaroo and Grasshopper are rather new software packages and not yet fully incorporated in the use of architecture design. Like stated in the literature study, even in the specific field of Interactive Architecture, simulation packages are not widely used. Simulation tools do not exist because Interactive Architecture exist but parametrical tools which are continuously developed together with new projects are no longer bound to that specific design. New tools therefore stimulate and positively reinforce new structures during their design. In this research a case study research showed that Kangaroo, the used component for simulating physics, is a promising tool. When designing structures, which are anchored by points, Kangaroo is able to simulate kinetics, a primary demand. The biggest issue involving this component is the current inability to implement rolling guides or anchor points. Meaning other than anchor points fixed in space, Kangaroo is not yet able to implement them. Kangaroo is still being developed at the time of writing however and these components have been announced. Further research could be the design of multiple component packages based on a specific design to implement and publish for the use in Grasshopper. Involving accuracy, it can be concluded that Kangaroo is able to accurately simulate structural behavior of non‐actuated structures. Averaged error margins in comparison to ANSYS, a Finite Elements package, are as low as 0,1%. Error margins of the comparison between actuated structures however are as high as 316,2%. This research is not able to accurately argument this large error margin. It states however that ANSYS is not designed to actuate members during its calculations. An initial strain was applied to the beam in ANSYS which was the only possible method. Compared to Kangaroo however where actuation of a beam is implemented by adjusting the rest length of the stiff spring depicting the beam.

108

Thee methods o of implemen nting the acttuation togeether with tthe linear caalculation by y ANSYS and a n non‐linear, itterative, cal culation meethod by Kangaroo are tthe main ues to be further researrched to vallidate the nu umerical accuracy of thhe simulatio on issu pacckage Kangaaroo and acccount for th he numericaal mismatch. No ode X Dire ction Y Diirection Nod de X Dire ction Y Dire ection 0,0 1 0,0 1 0,0 0,0 0,0 2 0,1 2 21,3 ‐105,7 0,1 3 0,1 3 9,4 ‐111,2 0,1 4 0,1 4 ‐2,7 316,2 0,1 5 0,1 5 ‐17,4 247,3 0,0 6 0,1 6 ‐28,0 206,7 0,1 7 0,1 7 ‐33,0 159,0 0,1 8 0,1 8 ‐38,1 128,0 0,1 9 0,1 9 ‐45,4 106,4 0,0 10 0,1 10 ‐59,7 90,6 0,0 11 0,0 11 0,0 0,0 0,0 12 0,0 12 0,0 0,0 0,0 13 0,1 13 30,8 62,6 0,0 14 0,1 14 13,4 70,5 0,0 15 0,1 15 17,6 79,0 0,0 16 0,1 16 ‐18,8 ‐132,0 0,0 17 0,1 17 ‐29,1 ‐120,8 0,0 18 0,1 18 ‐33,7 ‐112,2 0,0 19 0,1 19 ‐39,0 ‐104,8 0,0 20 0,1 20 ‐46,9 ‐97,9 0,0 21 0,1 21 ‐65,7 ‐91,4 0,0 22 0,0 22 0,0 0,0 ‐20,3 32,8 0,0 0,1 Tab ble 18: Error M Margin %, Deffault 5kN Tab ble 19:Error M Margin %, 5kN N

Figu ure 143: Simu ulation Grassh hopper, 0kN, A Actuated, Defformation Sca ale 1:1

Figu ure 144: Simu ulation ANSYSS, 0kN, Actuatted, Deformattion Scale 1:1

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5.2 Simulating Behavior. Besides being able to simulate kinetics, Grasshopper has the ability to introduce real‐ life sensor data to the programming environment thanks to the component Firefly. Being able to implement these streams of data, the designer can begin to design the intelligence which is a crucial part in the translation of data into actuation of the kinetic structure. Basic techniques which are already implemented in Grasshopper are the remapping function and the Optimization solver, Galapagos. The remapping function allows to easily remap the value in the sensor range to the actuation range. The sensor range is dependent on the specific sensor and post processing. The actuation range is specified by the used actuator driving the structure. Remapping functions however lead to a swarm like intelligence not taking the whole structure into account. The Galapagos Optimization solver however is able to optimize a single value, maximally or minimally, based on every actuator length. Techniques which prove to be valuable in further designs and research are position towards a point (displacement or attractor) and the sum product of beam length and internal force. Structures could be actuated to minimize internal forces or minimize displacements. Again further implementation and programming of components specifically for architectural design and data manipulation is a possibility. This research also remarks the fact that the optimization solver is an evolutionary type solver, meaning every iteration process will lead to another actuation. However seeing compared results the end value is always the same, leading to an optimal actuation, independent from the chosen actuation values. Actuator

Intelligent 1 1 2 3 4 5 6 7 8 9 CP

Difference

Intelligent 2

0 0 18 20 19 0 7 10 0 0,565594 0

Intelligent 3 0 0 20 20 20 0 9 4 0 0,565594 0

Figure 145: Central Intelligence versus Swarm intelligence, Simulation 1

0 0 8 20 19 0 3 0 0 0,565594 0

Swarm 7,93 12,58 17,68 20,00 16,76 11,51 7,12 3,25 0,00 0,565692 9,8E‐05

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5.3 3 Practical IIssues Thiis research aacknowledg ges the use oof new fabrication tech hniques suchh as 3D printing and laaser cutting. And statess that seeing g the overalll fabricationn process off currrent projecct landscape e and its own n prototypee, that these techniquess form a valuable sourcce of inspira ation and req quire a thorrough know wledge to succcessfully con nstruct a design. 5.3.1 Joints A vvariety of joiints was firsst researcheed involving g the differen nce betweenn 2D and 3D D join nts. To conclude this thesis states tthat nodes iin a 2D plane are easy tto fabricate to acccount for ecccentricity an nd degrees of freedom.. 3D joints h however aree relatively diffficult to con nstruct. A 3 3D joint connecting 2 m members is m mainly due tto the unive ersal joint m mechanism o or balll joint. The optimal nod de point theen still lies in the intersecting poinnt and allows a largge degree of freedom. T The requirem ment for the intersection point is nnecessary beccause otherw wise the node becomess unstable aand cannot b be implemennted in a kin netic structu ure. Wh hen connectting more th han 2 memb bers howeveer the ideal n node point ccannot be buiilt while maaintaining a large degreee of freedom m. This rese earch designned a node incorporated w with a ball jo oint per attaached truss members. T This allows a large degree of ffreedom. Th he intersectiion point dooes not fall iin the same point, makiing the node e unsstable. How wever when a attaching a minimum o of 3 truss me embers in 33D space this nod de is still staable and can n be used in n a kinetic sttructure. Attaching 1 orr 2 memberrs maakes the nod de unusable for use in kkinetic strucctures. en researcheed using a F Finite Elements calculattion involvin ng Thiis ball joint has not bee its resistance tto push and pull forces.. This is how wever an important poiint in nodal dessign, to reco ognize and a analyze weaak points in the structurre. The deveeloped ball join nt could be examined in n further re search ackn nowledging its weak pooints and adjusting the n node design n maintainin ng a large deegree of free edom.

Figu ure 146: 3D printed Multip ple member B Ball joint

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5.3 3.2 Cladding Claadding is an important p part of makking our inteeractive spaces viable. SSystems include flexible membranes and stiff materials. F Flexible mem mbranes aree not tho oroughly ressearched in this researcch but states that memb branes havee the ability y to intrroduce sunllight into sp paces using ttheir stretch h density an nd the fact tthat they can n insulted using Nano gel te echnology em mbedded in n a composite membranne. Further too ols or insights could be taken care oof in furtherr research. Stifff cladding llike composite panels aare already w widely availlable. Thesee could also be useed in Kineticc Architectu ure. Howeveer when attaached to a kinetic structture, the clad dding has to o be attache ed isostatic. When attacched hypersstatic movem ment of the stru ucture out o of the cladding plane w will cause thee attached ccladding or cconnection to faill and break. Further ressearch into p proper sealants for the e air tightne ss of these pan nels as well as insulatio on research will prove v valuable in iimproving tthe viability y of Interactive Spaace.

Figu ure 147: Kinettic Box, Scena ario 2

Figu ure 148: Expansion joint W Wooden claddiing

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5.3.3 Actuator Design Actuators are the means of our Kinetic Architecture. According to the literature study a variety of actuators, which not even be categorized because of their numbers, are available. All of these with different characteristics or limiting factors. This research looked into muscle wires, rotational actuators and pneumatically driven actuators. Muscle wires were researched but discarded for the use in Kinetic Architecture because of their limited strength and large dependence on environmental factors such as temperature. Muscle wires therefore did not fit in the use for Kinetic Architecture. Rotational actuators, in this research small servo motors, are available in different applications. To transform the rotational actuation into linear actuation for our Kinetic structures different possibilities or mechanisms occur. This research has built 3 different mechanisms with rotational actuators: a rack‐pinion system, a crankshaft mechanism and a screw mechanism. This research states that these actuators are limited by their available torque, depending on the type, and their elongation/shrink rate (stroke). Since actuators used were of the same torque strength, different shrink rates could be calculated and compared to each other. Further research in cooperation with mechanical engineers could provide new insights involving actuators and their behavior in real scale applications. Mechanism Shrink Rate [%] Crankshaft 23 Gear Pinion 48 Screw 28 Pneumatic muscle 11 Figure 149: Linear actuators, Shrink Rate

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For this research a McKibben air muscle was also fabricated to test its elongation rate versus applied load. When introducing a variable pressure range of 0 to 5 bar the muscle contracted. Different total elongation rates were found, depicting the accuracy of the setup or other issues that might influence the end results. These issues are the strength of the braided sleeve, a component of the muscle, as well as the dimensions of the silicone tubing. Further research could research this specific air muscle or design and validate different new mechanisms for linear or rotational actuation.

Druk(Bar) 1 kg 0,00 0,50 1,00 1,50 2,00 2,50 3,00 3,50 4,00 4,50 5,00 Total Range

2 kg

3 kg

4 kg

0,35

2,04

3,73

4,74

5,42

‐3,03 ‐4,72 ‐5,73 ‐6,74 ‐7,42 ‐8,09 ‐8,43 8,78

‐2,35 ‐4,04 ‐5,05 ‐5,73 ‐7,08 ‐7,42 ‐7,76 9,80

‐0,66 ‐1,68 ‐3,36 ‐4,38 ‐5,73 ‐6,74 ‐7,42 11,15

1,36 0,35 ‐1,34 ‐2,35 ‐3,36 ‐4,72 ‐5,39 10,14

2,04 0,69 ‐0,32 ‐1,34 ‐2,69 ‐3,36 ‐4,38 9,80

Figure 150: Air muscle, Elongation rate [%]

5kg

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5.3 3.4 Prototyp pe Thee produced prototype is inspired b by the curreent landscap pe of IA, KA and foremo ost natture. Startin ng from a general idea oof a structurral skin bein ng able to foorm its own shaape and inneer space this research d designed a p prototype. A A prototype based on th he typ pology of un nderwater polyps residiing in coralss this protottype combinnes direct inteeractivity, reesponse to d daylight, pr oximity and d vibration, with a layerr of structurral stability and in nteractivity on medium m long timefrrames.

Figu ure 151: Proto otype, Perspe ective view

Thee first layer of interactivity, directlyy linked to tthe biomimicry of undeerwater pollyps, offers tthe flexible skin with m means of intrroducing lig ght and venttilation in itts inn ner space. Beesides these e physical n needs of thiss inner space, the polypps are able to o dettect proximiity or touch, passing it tthrough thee skin makin ng its inhabiitants aware e of preesence. Inhaabitants are no longer sshielded from outdoor ffactors but aare now ma ade aware of them m using this IInteractive A Architecture. Thee production of the poly yps made w way for insig ghts in making as well aas designing g acttuators. Stru uctural interrnal forces w were taken iinto account of the polyyps which pro oduced a sim mple but effficient and eelegant actuator design.

115

Figu ure 152: Proto otype Upper V View

Figu ure 153: Proto otype Side vie ew

116

Figu ure 154: 3D Trruss Simulatio on

Eveen if the stru uctural layer was not im mplemented d in this pro ototype the iidea remain ns thee same. A strructural fram me is able too react to seets of data to deform acccording to spaatial needs o or structura al optimizatiion. The bassic structure e consistingg of a recctangular fraame was sim mulated and d fabricated. Actuators w with differeent lengths were fabricateed as membe ers with a fiixed length. By doing th his, the prottotype did n not sho ow its full po otential butt does show w its true usee and meaniing of differeent layers o of inteeractivity in n a real time eframe. Thee second lay yer is based on slower sstructural change. Chan nges in windd patterns d due to n new buildin ngs or the bllossom of trrees in the v vicinity will cause the eenvironmental app plied forces to shift. Alttering the coonditions off this interacctive equatiion. The stru ucture will tthen respon nd accordingg to its intellligence and d change its shape in a perriod of days or weeks and not minu utes or seco onds. Thee design and d constructiion of this p prototype w was conceived as a respoonse to the currrent Interactive and Kiinetic archittecture land dscape wherre structuraal interactiviity and d direct inteeractivity follow their oown indepen ndent path. This prototy type suggestt thaat these two different la ayers can bee woven into o each otherr and do nott have to be striictly divided d as in the ccurrent proj ect landscap pe. Further research annd designs ccan devvelop more elaborate and more inttelligent structures whiich extend tthese notion ns into o the field o of practical, usable and built architecture.

117

Appendices

118

Appendix A

Both

Weight

Linkage None‐ Physics

structural capacity

Both

Linkage

structural capacity

Direct M‐ Building Dynamic Systems Activity Climate)

Head

structural capacity Bending at node

Direct M‐ Building Embedde d Activity Climate)

Head

Truss

structural capacity

2008 Group MIT United States e Skylichts

Direct M‐ Building Dynamic Systems Activity Climate)

Swarm

Truss

structural capacity

2008 n,Orange void United Kingdom PixelSkin 2

Direct M‐ Building Dynamic Systems Activity Climate)

Swarm

structural capacity Antagonis t

structural capacity Bending at node

Load Bearing mechanis m Intelligen ce Both Bending Motor Direct M‐ Building Dynamic Systems Activity Climate)

2006 Group MIT United States WhoWha tWhenAir

Jaartal Architect Plaats

Direct

None

Sensor WaysAct uator

S‐ interior Embedde d Design (Interior)

2003 Gang Architects United States Starlight Theater Architect ure

Architect ure

Linkage

structural capacity

Linkage

structural capacity

c Cilinders

M‐ Building

Direct

M‐ Building

2008

Dynamic Systems

2008

WHITEvoi d

Embedded

Anshuman, Orangevoid

Germany

Activity Climate)

United Kingdom

Activity Climate)

Pragmatic Pragmatic Pragmatic Pragmatic Pragmatic Pneumatic Cilinders Bending c Bending Motor Cilinders SMA Motor Muscles Direct

Timespan

Direct M‐ Building Embedde d Activity Climate)

2008 Associate s United States Emergent Surface

Scale Kinetic motion on Kinetics 2008 Spectacul ar United States ery Module Architect ure

2008 David Fisher Arab Emirates rotating tower Naam Boek

Architect ure

Interactive Architect Architecture ure

119

Flare

Robo tic mem bran e

Both

structural capacity

Head

Various

structural capacity Postitioni ng

Both c Cilinders Direct

Linkage

structural capacity Linkage

structural capacity structural capacity

Both Swarm Both Head Humanist Pragmatic Pragmatic Pragmatic ic Bending Motor SMA Motor Various

linkage

structural capacity

Swarm

linkage

structural capacity

Swarm

Linkage

structural capacity

Both

structural capacity Pneumati c

Swarm

structural capacity Antagonis t

Light

Swarm

Both Pneumati c

S‐ interior Dynamic Systems Activity Climate)

Aperture Architect ure

Pragmatic

Pragmatic Pragmatic Both SMA, Muscles

S‐ interior Dynamic Systems Activity Climate)

Fans

Direct S‐ interior Dynamic Systems Activity Climate)

Servo

Direct

S‐ interior Embedde d Design (Interior)

Direct

Direct M‐ Building Dynamic Systems Activity Climate)

4D Pixel Architect ure

Direct

S‐ interior Dynamic Systems Design (Interior)

Germany RemoteH ome Architect ure

Direct

S‐ interior Dynamic Systems Activity Climate)

S‐ interior Dynamic Systems Design (Interior)

The Living United States Glass, Guills Architect ure

Direct

S‐ interior Dynamic Systems Optimizat ion

2008 rde Sstudios Netherlan ds 2009 Foster+Pa rtners United Kingdom of justive Shading Architect ure

Various

Direct

Direct M‐ Building Embedde d Activity Climate)

2010 Michael Fox United States

Dune 4.0 Architect ure

2007 2008 Morphosi Usman s Haque United States Federal Building Architect ure

Direct M‐ Building Dynamic Systems Activity Climate)

Bubbles Architect ure

Belgium rable House Architect ure

2008 2005 2008 2008 2005 rde Philip Smart Frederic studios Beesley Studio Eyl Netherlan United Germany States ds Hylozoic Grounds Architect ure

2007 Pezshkpo ur United States Environm ent Architect ure

120

Head

structural capacity Pneumati c Head

structural capacity Postitioni ng Head

Truss

structural capacity

Head

Truss

structural capacity

Swarm

structural capacity Postitioni ng Head

Truss

structural capacity

Head

Linkage

structural capacity

Head

structural capacity Antagonis t

Head

structural capacity Nurnberg scissors

Head

structural capacity Postitioni ng

Direct M‐ Building Embedde d Activity Climate)

Direct M‐ Building Deployabl e Activity Climate)

Direct M‐ Building Embedde d Activity Climate)

Spain Plaza & Fountain Design Group

Germany Guided Mast Design Group

Germany Hoechst Stadium Design Group

Otto Frei

1976

Direct M‐ Building Embedde d Activity Climate)

Pragmatic Pragmatic Pragmatic Pragmatic Pragmatic Pragmatic Pragmatic Pragmatic Pragmatic Pragmatic Pragmatic Muscles

Muscles

Direct

Muscles

Direct

S‐ interior Embedde d Activity Climate)

Direct

S‐ interior Embedde d Optimizat ion

Festo Netherlan ds Interactiv e Wall IA number 2

Direct

Direct M‐ Building Embedde d Activity Climate)

2007 Oosterhui s Netherlan ds Muscle Space IA number 2

Direct

2008 Oosterhui s Netherlan ds Muscle Tower 2 IA number 2

Direct M‐ Building Embedde d Activity Climate)

S‐ interior Embedde d Optimizat ion 2007 Oosterhui s Netherlan ds Muscle Tower 1 IA number 2

S‐ interior Embedde d Optimizat ion

S‐ interior Embedde d Optimizat ion 2005 Oosterhui s Netherlan ds Muscle Body IA number 2

1995 1998 2004 1976 Santiago Associate Calatrava Otto Frei s United States Hoberma n Sphere Design Group

2005 2003 Oosterhui Oosterhui s s Netherlan Netherlan ds ds Reconfigu red IA number 1 Muscle IA number 1

121

Linkage Head

structural capacity Nurnberg scissors Head

structural capacity Antagonis t Head

structural capacity Bending at node Head

structural capacity Nurnberg scissors Head

Linkage

Head

structural capacity Bending at node

structural capacity

structural capacity Bending at node Head

structural capacity

Head

Direct M‐ Building Embedde d Activity Climate) 1992 Felix Pallares United Kingdom Deployabl e Schell Design Group

Direct M‐ Building Embedde d Activity Climate) Direct S‐ interior Dynamic Systems Optimizat ion 2004 Group MIT United States Kinetic Wall Design Group

1995 Santiago Calatrava Switzerla nd Floating Pavilion Design Group

Direct M‐ Building Embedde d Activity Climate)

France Kinetic Canopies Design Group

Direct M‐ Building Embedde d Activity Climate) 1976 1998 1995 Associate Piano Otto Frei Renzo s United United States States IBM Pavilion Design Group Iris Dome Design Group

Direct M‐ Building Embedde d Activity Climate)

Pragmatic Pragmatic Pragmatic Pragmatic Pragmatic Pragmatic Pragmatic Pragmatic

Direct M‐ Building Embedde d Activity Climate) 1992 1997 Santiago FTL Calatrava Happold United States Music Pavilion Design Group Spain Kuwait Pavilion Design Group

122

Appendix B

#include <Button.h> #include <Servo.h> // Declaration! Servo myservo1; // create servo object to control a servo // a maximum of eight servo objects can be created Servo myservo2; // create servo object to control a servo // a maximum of eight servo objects can be created Servo myservo3; // create servo object to control a servo // a maximum of eight servo objects can be creat Servo myservo4; // create servo object to control a servo // a maximum of eight servo objects can be created Servo myservo5; // create servo object to control a servo // a maximum of eight servo objects can be created Servo myservo6; // create servo object to control a servo // a maximum of eight servo objects can be creat Servo myservo7; // create servo object to control a servo // a maximum of eight servo objects can be created Servo myservo8; // create servo object to control a servo // a maximum of eight servo objects can be created int sensorPinLight = 0; int sensorPinIR = 2; int sensorPinKnock = 5; int sensorPinButton = 13; int pos= 30; boolean Knocking = false; int counter = 1; Button Knop = Button(sensorPinButton,PULLDOWN);

123

// Initialization! void setup() { myservo1.attach(12); // attaches the servo on pin 12 to the servo object myservo1.write(pos); myservo2.attach(3); // attaches the servo on pin 3 to the servo object myservo2.write(pos); myservo3.attach(4); // attaches the servo on pin 4 to the servo object myservo3.write(pos); myservo4.attach(5); // attaches the servo on pin 5 to the servo object myservo4.write(pos); myservo5.attach(6); // attaches the servo on pin 6 to the servo object myservo5.write(pos); myservo6.attach(7); // attaches the servo on pin 7 to the servo object myservo6.write(pos); myservo7.attach(8); // attaches the servo on pin 8 to the servo object myservo7.write(pos); myservo8.attach(10); // attaches the servo on pin 10 to the servo object myservo8.write(pos); pinMode(sensorPinLight, INPUT); pinMode(sensorPinIR, INPUT); Serial.begin(9600); // prints title with ending line break Serial.println("Program Starting");

124

// Loop ! void loop() { int ValueLight = map(irRead(sensorPinLight,10),0,900,30,160); //ValueLight = map(analogRead(sensorPinLight),0,900,30,160); float distance = 12343.85 * pow(irRead(sensorPinIR,10),‐1.15); //float distance = 12343.85 * pow(analogRead(sensorPinIR),‐1.15); //float distance = irRead(sensorPinIR,10); int ValueIR = map(distance,0,100,30,160); int ValueKnock = irRead(sensorPinKnock,10); if (ValueKnock >= 50) {Knocking = true;} ValueLight = constrain(ValueLight, 30, 160); ValueIR = constrain(ValueIR, 30, 160); if (Knop.uniquePress()){ counter++; if(counter == 3){counter=0;} Serial.println("Program:"); Serial.println(counter); } if (counter == 0){ Serial.println(ValueLight); WriteAll(ValueLight); } if (counter == 1) { Serial.println(ValueIR); //Serial.println(distance); WriteAll(ValueIR); } if (counter ==2){ Serial.println(ValueKnock); if (Knocking == true) {WriteAll(170); delay (10000); SweepAll(170,30); Knocking = false;} } delay(100); } 125

int irRead(int readPin, int amount) { int halfPeriod = 13; //one period at 38.5khZ is aproximately 26 microseconds int cycles = amount; //26 microseconds * 38 is more or less 1 millisecond int i; int total = 0; for (i=0; i <=cycles; i++) { int interval = analogRead(readPin); total = total + interval; delay(halfPeriod); } return (total/cycles); } void WriteAll(int value) { myservo1.write(value); //delay(1000); myservo2.write(value); //delay(1000); myservo3.write(value); //delay(1000); myservo4.write(value); //delay(1000); myservo5.write(value); //delay(1000); myservo6.write(value); //delay(1000); myservo7.write(value); //delay(1000); myservo8.write(value); //delay(1000); } void SweepAll(int start, int einde) { if (start > einde) { for( int value = start; value > einde; value‐‐) // goes from 0 degrees to 180 degrees { // in steps of 1 degree WriteAll(value); // tell servo to go to position in variable 'pos' delay(15); // waits 15ms for the servo to reach the position }} if (einde > start) { for( int value = start; value < einde; value++) // goes from 0 degrees to 180 degrees { // in steps of 1 degree WriteAll(value); // tell servo to go to position in variable 'pos' delay(15); // waits 15ms for the servo to reach the position }}

126

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K.U.Leuven Faculteit Ingenieurswetenschappen

2010‐2011

Fiche Masterproef Student: Carlo Rousseeuw Titel: Kinetische Architectuur: Modelleren van ontwerp en gedrag Engelse titel: Kinetic Architecture: Modelling design and behavior UDC: 72 Proefschrift voorgedragen tot het behalen van de graad van Master in de ingenieurswetenschappen: Architectuur – Bouwtechnische Optie Promotor(en): Prof. Andrew Vande Moere Assessoren: Prof. Leo Van Broeck Begeleiders: Prof. Stefaan Boeykens Korte inhoud: The way we use and experience objects in our daily lives is constantly being improved with increasing user‐interactivity. From our cars which are filled with sensors to enrich our driving experience to the automated shading of our windows which disappears when we need to get out of bed in the morning. Architecture today on the other hand is static, its structural form does not interact with its users or its changing environmental factors. Instead of shielding the inhabitants from these factors, these factors can be responded to and interacted with to change the inhabitant’s perception of this new space, Interactive Architecture. In the design of interactive architecture with structural kinetic changes, Kinetic Architecture, the simulation of a structure and its behavior plays a valuable role in its overall design and production. Being able to connect a wide range of sensor data with this design‐software we cross the bridge necessary for completely simulating interactive architecture, which in turn has an effect on the final design. Recent developments and community efforts in plugins for drawing software like Grasshopper for Rhinoceros have given us these abilities.

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Every project is unique by its own context and usage and therefore unique by its means to interact. This thesis simulates different existing structures in the current landscapes and tests the scope of current simulation packages and their use to designers with regards to Kinetic Architecture. Also the intelligence which controls this Kinetic Architecture and the different kinds of data streams are addressed together in the context of the simulation software. Besides the research in terms of simulation, this thesis also discusses practical issues of Kinetic Structures in a general way before building a working prototype. This research will act as a catalyst to provide architects with the necessary skillset to develop and design interactive architecture but also to provide a mutual goal for other disciplines like robotics and material engineers to form and research different end products with enhanced user interactivity which could be used in this new breed of Interactive Architecture.

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