bio-digital morphogenesis in architecture · mahmoud mohamed gomaa ahmed for the degree of master...

University of Alexandria Faculty of Engineering

Architectural Engineering Department

BIO-DIGITAL MORPHOGENESIS IN ARCHITECTURE

An Application on Digital - Botanic Architecture (D.B.A)

A Thesis

Presented to the Graduate School Faculty of Engineering, Alexandria University

In Partial Fulfillment of the Requirements for the Degree

Of

Master of Science

In

Architectural Engineering

By Mahmoud Mohamed Gomaa Ahmed

April 2015

University of Alexandria Faculty of Engineering

Architectural Engineering Department BIO-DIGITAL MORPHOGENESIS INARCHITECTURE

An Application on Digital - Botanic Architecture

(D.B.A)

Presented by

Mahmoud Mohamed Gomaa Ahmed For The Degree of Master of Science

In Architectural Engineering

Approved: Examiners Committee

Prof. Dr. Mohamed Abdelall Ibrahim _______________ Professor of Architecture, Architectural Engineering Department, Faculty of Engineering, Alexandria University.

Prof. Dr. Yehia Mostafa Mohamed _______________ Professor of Architecture, Department of Architecture, Faculty of Fine Arts, Alexandria University. Prof. Dr. Mostafa Morsy El Araby _______________ Professor of Architecture, Architectural Engineering Department, Faculty of Engineering, Alexandria University.

Vice Dean for Graduate Studies and Research: Prof. Dr. Magdy Abdelazim Ahmed _______________ Faculty of Engineering, Alexandria University

Advisors Committee: Approved Prof. Dr. Mohamed Abdelall Ibrahim _______________ Professor of Architecture, Architectural Engineering Department, Faculty of Engineering, Alexandria University.

Dr. Samer Mohamed Adel El Sayary _______________ Lecturer, Architectural Engineering Department, Faculty of Engineering, Alexandria University.

"In the Name of ALLAH, Most Gracious, Most Merciful"

BIODIGITAL MORPHOGENESIS IN ARCHITECTURE i

I. ACKNOWLEDGMENTS Above all, I thank almighty God, the most merciful and compassionate, for

granting me the willingness and ability to accomplish this research.

It would not have been possible to write this thesis without the help and support of the honorable people around me, to only some of whom it is possible to give particular mention here.

It is with immense gratitude that I acknowledge the support and extreme patience of my supervisor, Prof. Dr. Mohamed Abdelall Ibrahim, not to mention his continuous encouragement, intellectual advice and assistance in keeping my progress on schedule. Likewise, my grateful thanks are extended to Dr. Samer El Sayary for his guidance and support.

Indeed, I cannot find words to express my mere gratitude to my generous parents and my brother for their unequivocal support throughout my entire life, as always, for which my mere expression of thanks likewise does not suffice. I would also like to offer my special thanks to my dear fiancé: Nourhan Muhammad Saad for her endless support and patience at all times.

Last but not least, I am indebted to all my professors and colleagues in the Department of Architecture for their endless support and academic guidance. Finally, I consider it an honor to have precious friends who encourage me and provide me with perpetual support.

BIODIGITAL MORPHOGENESIS IN ARCHITECTURE ii

II. ABSTRACT

The big dream beyond using computers in different phases of architectural design is to reach a complete digital design process. Successful endeavors, which gave acceptable results and have been developed to be complete software, were in the phases of programming, design development, drafting and visualization. Other phases of design process; such as functional relationships, form finding and manufacturing; still have many trials to reach complete software to aid in the knowledge-base design, scripted architecture and the computer aided manufacturing, towards the big dream. By automating parts of the design process, computers make it easier to develop designs through versioning and gradual adjustment. These approaches to designing have been described as morphogenesis.

Morphogenesis differs between biology and architecture. They share some similarities but also, they have differences. Despite the differences and difficulties, direct collaborations between biology and architecture are necessary not only in the narrow context of the present discussion but also because they can help to orient designing towards biologically compatible outcomes. Another, equally exciting outcome of such collaborations will be in further contributions towards creative inspiration.

Depending on the similarities between them, that would make collaboration between them easier and open the way to assume a complete hybridization between them in software in order to generate a biological plug-in into architectural software that would help to start designing a building depending on a biological base and making use of their ability to evolve and growth . After that there would be analysis of the biological base structure, for example, to be used as a structure for the building. Finally the production will be different volumes which are simulating the organic growth and these grown shapes can then be engineered and detailed as architecture.

Keywords: Generative design – Morphogenesis - Algorithmic architecture – bio design– bio digital architecture.

BIODIGITAL MORPHOGENESIS IN ARCHITECTURE iii

III. TABLE OF CONTENTS

I. ACKNOWLEDGMENTS ................................................................................................ i

II. ABSTRACT..................................................................................................................... ii

III. TABLE OF CONTENTS ............................................................................................. iii

IV. LIST OF FIGURES ..................................................................................................... ix

V. LIST OF ABBREVIATIONS ...................................................................................... xv

VI. LIST OF DEFINITIONS ........................................................................................... xvi

VII. ASSUMPTION ......................................................................................................... xvii

VIII. AIMS AND OBJECTIVES ................................................................................... xvii

IX. METHODOLOGY ................................................................................................... xviii

A. Literature review ........................................................................................................... xviii B. Application and conclusion .......................................................................................... xviii

X. THESIS STRUCTURE ............................................................................................... xix

Part -1- Generative Design and Algorithms.............................................. 1

CHAPTER -1- GENERATIVE DESIGN .......................................................................... 2

1.1 Introduction ........................................................................................................................ 3 1.2 Generative Design Definitions ........................................................................................ 3 1.3 Properties of Generative Design ..................................................................................... 4 1.4 Differences between the Traditional Method of Design and Generative Design 4 1.5 Generative Design System in Architecture .................................................................. 6

1.5.1 Generative Design System Definition. .......................................................................... 6 1.5.2 Historical Background of the Generative Design Systems. ........................................ 6 1.5.3 Generative Design Process ............................................................................................ 7 1.5.4 Categories of Generative Design Systems. ................................................................... 8 1.5.5 Generative Systems Approaches .................................................................................. 8

1.5.5.1 Algorithmic generative systems. .................................................................... 9 1.5.5.2 Parametric systems. .......................................................................................... 9 1.5.5.3 Formalisms ........................................................................................................ 9

1.5.5.3.1 L-systems. ............................................................................................... 9 1.5.5.3.2 Cellular automata systems.................................................................... 9 1.5.5.3.3 Fractal systems..................................................................................... 10 1.5.5.3.4 Shape grammars. ................................................................................. 10

1.6 Generative Model ............................................................................................................ 10 1.6.1 Categories of Generative Models. ............................................................................... 10

BIODIGITAL MORPHOGENESIS IN ARCHITECTURE iv

1.6.1.1 Grammatical transformative design models. .............................................. 11 1.6.1.2 Evolutionary design models. ......................................................................... 11

1.7 Conclusion ......................................................................................................................... 12

CHAPTER - 2 - COMPUTATION AND PROGRAMMING ....................................... 14

2.1 Introduction ...................................................................................................................... 15 2.1.1 Differences between Computation and Computerization. ....................................... 16 2.1.2 Different Visions about Using Computers in the Design Process. ........................... 17 2.1.3 Computational Design ................................................................................................. 19

2.1.3.1 Computational design techniques. ............................................................... 19 2.1.3.2 Characteristics of computational design techniques. ................................. 19

2.1.3.2.1 Geometry. ............................................................................................. 20 2.1.3.2.2 Composition. ........................................................................................ 20 2.1.3.2.3 Algorithmic thought. ........................................................................... 21

2.1.4 Differences between Conventional Design and Computational Design. ................. 22 2.2 Algorithms ......................................................................................................................... 22

2.2.1 The Origin of the Word Algorithm and Definitions. ................................................ 22 2.2.2 Expressing Algorithms. ............................................................................................... 22 2.2.3 Algorithmic Design. ..................................................................................................... 23

2.2.3.1 Algorithmic design requirements. ................................................................ 23 2.2.3.1.1 Techniques. .......................................................................................... 23 2.2.3.1.2 Resources. ............................................................................................. 23

2.2.4 Algorithm Problems. ................................................................................................... 23 2.2.4.1 Algorithmic problems classification. ........................................................... 24

2.2.5 Problem Solving. .......................................................................................................... 24 2.2.5.1 Types of problem solution ............................................................................ 25

2.2.5.1.1 Algorithmic solution. .......................................................................... 25 2.2.5.1.2 Heuristic solutions. .............................................................................. 25

2.2.5.2 Computers as a tool to solve problems. ....................................................... 25 2.2.5.3 Difficulties with problem solving. ............................................................... 26

2.2.6 Algorithms in Computational Design......................................................................... 26 2.3 Programming .................................................................................................................... 26

2.3.1 Introduction .................................................................................................................. 26 2.3.2 Coding. .......................................................................................................................... 27 2.3.3 Scripting. ....................................................................................................................... 27 2.3.4 Modeling Methods in Architecture. ........................................................................... 28 2.3.5 Scripting Languages or Programming Languages. .................................................. 29

2.3.5.1 Programming languages classification. ....................................................... 30 2.3.5.1.1 Visual Programming Languages (VPLs). ........................................ 30 2.3.5.1.2 Textual programming languages (TPLs).......................................... 31

2.4 Conclusion ......................................................................................................................... 32

BIODIGITAL MORPHOGENESIS IN ARCHITECTURE v

Part-2- Bio Inspired Design and Morphogenesis ................................. 33

CHAPTER-3- BIO-INSPIRED DESIGN ........................................................................ 34

3.1 Introduction ...................................................................................................................... 35 3.2 Definitions .......................................................................................................................... 35

3.2.1 Biology. ......................................................................................................................... 35 3.2.2 Architecture. ................................................................................................................. 35

3.3 Integration between Architecture & Biology ............................................................ 36 3.3.1 Biological analogy in Architecture. ............................................................................ 36 3.3.2 Bio-Architecture........................................................................................................... 36

3.4 Towards Sustainable Development ............................................................................. 37 3.4.1 Differences between the Conventional Design and the Integrated Approaches of Design (Bio-Design) .............................................................................................................. 37

3.4.1.1 Conventional design approach ...................................................................... 38 3.4.1.2 Integrative design approaches (Bio-design). .............................................. 38

3.5 Bio Design .......................................................................................................................... 39 3.5.1 Differences between Bio-Design and Bio-Mimicry. .................................................. 40

3.5.1.1 Beyond bio-mimicry. ..................................................................................... 40 3.5.2.1 Nature ............................................................................................................... 41

3.5.2.1.1 History of nature in design. ................................................................ 41 3.5.2.1.2 How designers dealing with nature. .................................................. 42 3.5.2.1.3 Nature in bio-design. ........................................................................... 42 3.5.2.1.4 From the natural to the unnatural. ..................................................... 43 3.5.2.1.5 Properties of living structure. ............................................................. 43

3.5.2.1.5.1 Organized complexity. ...................................................... 43 3.5.2.1.5.2 Metabolism. ............................................................................ 44 3.5.2.1.5.3 Replication. ............................................................................. 44 3.5.2.1.5.4 Adaptation. .............................................................................. 45 3.5.2.1.5.5 Intervention. ............................................................................ 45 3.5.2.1.5.6 Situatedness. ........................................................................... 45 3.5.2.1.5.7 Connectivity. .......................................................................... 46

3.5.2.2 Science. ............................................................................................................ 46 3.5.2.2.1 Science and biology. ........................................................................... 46 3.5.2.2.2 Importance of Science in bio- design and the integration between

nature and science. ............................................................................. 47 3.5.2.3 Creativity ......................................................................................................... 47

3.5.2.3.1 What is creativity? ............................................................................... 47 3.5.2.3.2 What is a creative approach? ............................................................. 48 3.5.2.3.3 Linking creativity and problem solving. .......................................... 48 3.5.2.3.4 Creative problem solving. .................................................................. 49

3.5.2.3.4.1 Main purposes or CPS process components. ..................... 49 3.5.2.3.4.2 CPS process stages ................................................................ 49

BIODIGITAL MORPHOGENESIS IN ARCHITECTURE vi

3.5.3 Architecture and Biological processes. ...................................................................... 51 3.5.4 Outcomes of Bio-Design. ............................................................................................. 51

3.6 Cases Studies ..................................................................................................................... 52 3.6.1 Example -1- Bridges of Meghalaya ............................................................................ 52

3.6.1.1 Description. ..................................................................................................... 52 3.6.1.1 Origination. ..................................................................................................... 52

3.6.2 Example -2- House of the Future ................................................................................ 54 3.6.2.1 Description. ..................................................................................................... 54 3.6.2.2 Construction phase. ........................................................................................ 55 3.6.2.3 Development. .................................................................................................. 55

3.6.3 Example -3- Fab Tree Hab .......................................................................................... 57 3.6.3.1 Description. ..................................................................................................... 57 3.6.3.2 Construction phase. ........................................................................................ 59 3.6.3.3 Innovation. ....................................................................................................... 60

3.6.4 Example -4- Dune......................................................................................................... 60 3.6.4.1 Description. ..................................................................................................... 61 3.6.4.2 Inspiration................................................................................................ 62 3.6.4.2 Materials. ......................................................................................................... 64

3.6.5 Example -5- Filene's Eco Pods .................................................................................... 64 3.6.5.1 Description .............................................................................................. 65 3.6.5.2 objectives and construction ..................................................................... 66 3.6.5.3 Components ............................................................................................. 66 3.6.5.4 Composition Growth ...................................................................................... 67

3.7 Conclusion ......................................................................................................................... 68

CHAPTER -4- TOWARDS MORPHOGENESIS .......................................................... 70

4.1 Introduction ...................................................................................................................... 71 4.2 Definitions of Morphogenesis........................................................................................ 72 4.3 Computational Models and Morphogenesis Types .................................................. 73

4.3.1 Proliferation ................................................................................................................. 73 4.4 Architecture & Biology .................................................................................................. 74

4.4.1 Morphogenesis in Architecture & Biology. ............................................................... 74 4.5 Morphogenesis in Architecture (Digital Morphogenesis) ...................................... 75

4.5.1 Computational Architectures ..................................................................................... 76 4.5.1.1 Topological architecture ………………………………………...……..77 4.5.1.2 Isomorphic architecture ………………………………………………..79 4.5.1.3 Animate architecture. ..................................................................................... 80 4.5.1.4 Metamorphic architecture. ............................................................................ 80 4.5.1.5 Parametric architecture. ........................................................................... 81 4.5.1.6 Evolutionary architecture. ............................................................................. 81

4.5.2 Implications. ................................................................................................................. 82 4.5.2.1 Dynamics and the fields of forces. ............................................................... 82

BIODIGITAL MORPHOGENESIS IN ARCHITECTURE vii

4.5.2.2 Emergence and the fields of indetermination. ............................................ 83 4.5.2.3 Mass customization. ....................................................................................... 83

4.6 Morphogenesis in Biology .............................................................................................. 84 4.6.1 Computational Models of Plant Morphogenesis. ...................................................... 85 4.6.2 Characteristics ............................................................................................................. 85

4.6.2.1 Focus and limitations. .................................................................................... 85 4.6.2.2 Multi-scale hierarchy. .................................................................................... 86 4.6.2.3 Dynamic structure. ......................................................................................... 87 4.6.2.4 Processual continuity. .................................................................................... 88

4.7 Conclusion ......................................................................................................................... 88

Part -3- Bio Digital Morphogenesis .............................................................. 91

CHAPTER -5- BIO-DIGITAL ARCHITECTURE........................................................ 92

5.1 Introduction ...................................................................................................................... 93 5.1.1 Different Points of View of Architecture Dealing with Plants ................................. 94

5.2 Approaches to the Bio Digital Architecture .............................................................. 95 5.2.1 Virtual Reality .............................................................................................................. 95 5.2.2 Live Architecture. ........................................................................................................ 95 5.2.3 Theory of Monads and Theory of Memes .................................................................. 95

5.2.3.1 Theory of meme-monad. ............................................................................... 96 5.2.4 Architecture Re-conceptualization ............................................................................. 96

5.3 Botanic Digital Architecture ......................................................................................... 97 5.3.1 Seeding Digital-Botanic Architecture. ....................................................................... 99 5.3.2 Sullivan's Concept for Development ........................................................................ 102

5.3.2.1 Efflorescence. ............................................................................................... 103 5.3.2.2 Applying growth and generation to architectural design. ....................... 103 5.3.2.3 Inspiration in architecture. .......................................................................... 104 5.3.2.4 Integration between Sullivan ideas and meme monad compounds ....... 104 5.3.2.4.1Example of collaboration .......................................................................... 105

5.4 Application ...................................................................................................................... 107 5.4.1 Hypothesis. ................................................................................................................. 107 5.4.2 Introduction for Examples ........................................................................................ 108 5.4.3 E-Trees & E-Plants. ................................................................................................... 108 5.4.4 Examples ..................................................................................................................... 109

5.4.2.1 Example -1- E-Tree anatomy & morphology. .......................................... 109 5.4.2.2 Example -2- E-Tree column. ...................................................................... 111 5.4.2.3 Example -3- E-Tree branch and tendril morphology ............................... 113

5.4.2.3.1 STL & SLS E-tree models. .............................................................. 113 5.4.2.4 Example -4- E-tree animation: Arizona tower ......................................... 114 5.4.2.5 Example -5- Self-shading tower for Los Angeles. ................................... 115

5.5 Recommendations .......................................................................................................... 116

BIODIGITAL MORPHOGENESIS IN ARCHITECTURE viii

5.6 Conclusion ....................................................................................................................... 117 Conclusion ……………………………………………………………………...……….118

Using Programs ……………………………………………………………..…….……120

References ………………………………………………………………………………121

Appendix …………………………………………………………………….………….130

Xfrog Manual ......................................................................................................….....130

Summary ………………………………………………………………………………..146

147...……………………………………………………...……………… الملخص باللغة العربية

BIODIGITAL MORPHOGENESIS IN ARCHITECTURE ix

IV. LIST OF FIGURES Figure 1: Structure Thesis .................................................................................................. xix

Figure 2: Chapter (1) Structure. ............................................................................................ 2

Figure 3: Generative Design Elements. ................................................................................ 3

Figure 4: Generative Design Approach ................................................................................ 3

Figure 5: Traditional Design Loop ....................................................................................... 5

Figure 6: Generative Design Loop ....................................................................................... 5

Figure 7: Generative System Concept .................................................................................. 6

Figure 8: A System of Architectural Ornament According with a Philosophy of Man’s Powers ..................................................................................................................... 7

Figure 9: Generative Design Process .................................................................................... 7

Figure 10: Generative Systems Approaches ......................................................................... 8

Figure 11: Generative Model .............................................................................................. 11

Figure 12: Chapter (2) Structure ......................................................................................... 14

Figure 13: Algorithmic Process Done by Using A Computer ............................................ 15

Figure 14: The Computation Process ................................................................................. 15

Figure 15: Computational Design Techniques ................................................................... 20

Figure 16: Algorithmic Problems Classification ................................................................ 24

Figure 17: Three Different Types of Representation of Computational Design Concepts, with Different Abstraction Levels ......................................................................... 28

Figure 18: Different Types of Programming Language ..................................................... 29

Figure 19: An Example VPL in Grasshopper Interface...................................................... 31

Figure 20: An Example of TPL in AutoCAD Interface ..................................................... 32


Figure 22: Integrated Design Approaches and Concepts of Sustainability ........................ 37

Figure 23: Conventional Design Process and How the Team Works ................................ 38

Figure 24: Integrated design process and how the team works .......................................... 38

BIODIGITAL MORPHOGENESIS IN ARCHITECTURE x

Figure 25: Bio-Design Approach........................................................................................ 39

Figure 26: Bio-Design System............................................................................................ 41

Figure 27: Properties of Living Structure ........................................................................... 43

Figure 28: Noller's Symbolic Formula for Understanding Creativity ................................ 48

Figure 29: The Core Purposes or CPS Process Components ............................................. 50

Figure 30: The Core Purposes of CPS Process Components and Stages ........................... 50

Figure 31: Bridges of Meghalaya ....................................................................................... 52

Figure 32: As with All Living Structures, The Bridges Rely on A Healthy Environment for Their Maintenance, Abundant clean air, water, and soil are essential .................. 53

Figure 33: The Bridges are Ever Changing in Form and They are Strengthened by The Addition of Branch and Grass Clippings, Which Nourish The Roots ................... 53

Figure 34: Over Time, Bridges are Shaped from The Roots of Several Trees. These Natural Structures are Capable of Lasting for Hundreds of Years ................................... 53

Figure 35: House of the Future ........................................................................................... 54

Figure 36: Screw Bases of The Temporary Scaffold.......................................................... 55

Figure 37: Pre-Cultivated Plants in The Greenhouse ......................................................... 55

Figure 38: Assembly with The Crawler Crane ................................................................... 55

Figure 39: Connecting of Plants with Stainless Steel Screws ............................................ 55

Figure 40: Winter 2010 ....................................................................................................... 56

Figure 41: Spring 2010 ....................................................................................................... 56

Figure 42: Early Summer 2010........................................................................................... 56

Figure 43: Last Summer 2010 ............................................................................................ 56

Figure 44: Autumn 2010 ..................................................................................................... 56

Figure 45: Winter 2011 ....................................................................................................... 56

Figure 46: Summer 2011 .................................................................................................... 56

Figure 47: Autumn 2011 ..................................................................................................... 56

Figure 48: Spring 2011 ....................................................................................................... 56

BIODIGITAL MORPHOGENESIS IN ARCHITECTURE xi

Figure 49: By Directing Their Growth, Trees and Woody Plants can be Integrated into Built Structures. This Slow Construction Method Creates Living Architecture Integrated with—and Enhancing—The Environment ............................................................ 57

Figure 50: Energy and Nnutrient Flows are Connected with The Natural Cycles of The Surrounding Ecosystem, Thereby Harnessing Both Cool Air and Rainwater ...... 58

Figure 51: A variety of Plants Fill in The Gaps in The Façade, Encouraged By The Use of Perforated Scaffolding Through Which Stems and Leaves Can Intertwine .......... 58

Figure 52: The process of Composing A House by Depending on Planting Trees ............ 59

Figure 53: The Final Predicted Product .............................................................................. 59

Figure 54: Structure Development Process ........................................................................ 59

Figure 55: How to Stop Desertification .............................................................................. 60

Figure 56: The Wind and Sand That Result in Expansion of The Desert, Threatening Settlements and Arable Land, are Exploited in Biological Construction .............. 61

Figure 57: Sand Solidified by Bacteria and Shaped by The Wind Eventually Allows Water to Accumulate and Forms A Barrier Against The Spread of The Desert .............. 61

Figure 58: A Dune Cross-Section with Rigid Chambers Where Precious Moisture and Soil Might Be Preserved ............................................................................................... 62

Figure 59: The Shape of The Structure Here is Shown in A Tafoni Pattern—Characteristic of Rock That Has Been Eroded by Wind or Moisture for Many Years ................ 62

Figure 60: Resisting The Spread of The Desert Becomes Ever More Difficult and Yet Important as The Climate Warms. The Vast Savanna of The Sahel Belt is One of Many Areas That are Currently Under Threat Source: (Myers W. , 2012) .......... 63

Figure 61: The Architect‘s Proposal Stemmed from An Examination of Extreme Environments, Such As Desert, Ocean, and Tundra, Where Traditional Approaches to Building are Simply Unfeasible ........................................................................ 63

Figure 62: Microbially Induced Cementation is A Natural Process That Can Be Observed in Swamps and Lakes. It Is Not Harmful to Humans and Will Cease Once Available Nutrients Have Been Depleted .............................................................................. 64

Figure 63: Filene's Eco Pods .............................................................................................. 64

Figure 64: Future Eco Bods ................................................................................................ 65

Figure 65: Full Set Drawings for the Module Pod ............................................................. 65

BIODIGITAL MORPHOGENESIS IN ARCHITECTURE xii

Figure 66: Grown Algae between Modules (Bioreactors) .................................................. 66

Figure 67: Eco-Pod Process ................................................................................................ 66

Figure 68: Robotic Armature (Powered by the Algae Bio Fuel) ....................................... 67

Figure 69: Different Deformations of Modules .................................................................. 67

Figure 70: Different between New Trend of Buildings and the Ordinary Buildings ......... 68


Figure 72: Generate from Algorithm to Structure - Exhibition Structure .......................... 71

Figure 73: Performance Building For the Oulu Music Video Festival; Competition Entry and 3rd Prize for Ideas for Yard and Environmental Constructions Held by Kainuun Etu Oy .................................................................................................................... 72

Figure 74: Cell Arrangements in Plant Tissues .................................................................. 73

Figure 75: Homeomorphic (Topologically Equivalent) Figures ........................................ 76

Figure 76: Homeomorphic (Topologically Equivalent) ..................................................... 77

Figure 77: Spatial Computing with Conformal Geometric Algebra .................................. 77

Figure 78: A Composite Curve Constructed from Tangent Circular Arcs and Straight Line Segments ................................................................................................................ 78

Figure 79: Varying the Degree of A NURBS Curve Will Produce Different Shapes ........ 79

Figure 80: Isomorphic Surfaces .......................................................................................... 79

Figure 81: Animate Architecture: Lynn’s Port ................................................................... 80

Figure 82: Parametric Architecture: Marcos Novak‘s “Algorithmic spectaculars” .......... 81

Figure 83: Paramorph by Mark Burry ................................................................................ 81

Figure 84: Bernard’s Cache “Objectiles.” .......................................................................... 84

Figure 85: Conceptual Diagrams Based on Photomicrograph of Coleochaete Orbicularis 86

Figure 86: Biomechanical Model for Cell Expansion in Morphogenesis: Cell Wall Response to Turgor Pressure Through A Viscous Yielding of The Cell Wall, Compensated at The Same Time by Thickening to Maintain A Constant Cross-Section ............... 88

Figure 87: Chapter (5) Structure. ........................................................................................ 92

Figure 88: Photograph of Woven, Urban Walls in Peru’s Pueblos Nuevos ....................... 93

BIODIGITAL MORPHOGENESIS IN ARCHITECTURE xiii

Figure 89: Semper’s Braids ................................................................................................ 93

Figure 90: Semper‘s Vision of Architecture ....................................................................... 94

Figure 91: Dollens's Vision of Architecture ....................................................................... 94

Figure 92: Digital-Botanic Architecture ............................................................................. 98

Figure 94: X-frog Truss-Frame Grown from A Tree (Top Left) to Study Possible Structural Articulations for A Building Frame and Columns ................................................ 99

Figure 95: Part of the A System of Architectural Ornament – Plate 2 ............................. 100

Figure 96: Tumble Truss Project Lexicon, Observational Biomimetics Leading to Physical Models ................................................................................................................. 100

Figure 97: Growing with Digital Model ........................................................................... 101

Figure 98: Xfrog Grown Structural Truss Based on Physical Tumble Truss Model ....... 101

Figure 99: A Typical Seed with Two Cotyledons from Part of The A System of Architectural Ornament – Plate 2 .............................................................................................. 102

Figure 100: Nietzscheian, Transformative Criteria .......................................................... 102

Figure 101: Applying Growth and Generation to Architectural Design .......................... 103

Figure 102: Collaboration between Sullivans' Ideas and Meme-Monad .......................... 104

Figure 103: X-frog Growth with Pod Dispersion; Inspired by Sullivan’s A System of Architectural Ornament and His Merchant’s National Bank, Grinnell, Iowa ..... 105

Figure 104: Xfrog Growth Developed As A Tall Building Inspired by Sullivan’s A System of Architectural Ornament and His Merchant’s National Bank .......................... 106

Figure 105: Hypothesis ..................................................................................................... 107

Figure 106: Using X-Frog to Generate A Plant ................................................................ 109

Figure 107: Converting This E Tree to Be A Building .................................................... 110

Figure 108: X-frog Grown Tree-Column ......................................................................... 111

Figure 109: STL Tree Branches Supporting Leaf Grown Floors ..................................... 112

Figure 110: E-Tree Branch & Tendril Morphology ......................................................... 113

Figure 111: E-Tree Animation: Arizona Tower ............................................................... 114

Figure 112: Self-Shading Tower for Los Angeles ............................................................ 115

BIODIGITAL MORPHOGENESIS IN ARCHITECTURE xiv

Figure 113: Steps to Produce A Bio-Digital Building ...................................................... 116

Figure 114: Programs Timeline ........................................................................................ 116

BIODIGITAL MORPHOGENESIS IN ARCHITECTURE xv

V. LIST OF ABBREVIATIONS

Abbreviation Explanation CAD Computer-Aided Design

CATIA Computer Aided Three-dimensional Interactive Application

CA Cellular Automata NURBS Non-Uniform Rational B-Spline

GD Generative Design VPLs Visual Programming Languages TPLs Textual Programming Languages

PL Programming Language VBA Visual Basic for Application IDE Interactive Development Environment GUI Graphical User Interface MEL Maya Embedded Language

WCED Western Cape Education Department CPS Creative Problem Solving

CAM Computer-Aided Manufacturing AAD Algorithms-Aided Design

SF Science Fiction STL Standard Template Library SLS Space Launch System

BIODIGITAL MORPHOGENESIS IN ARCHITECTURE xvi

VI. LIST OF DEFINITIONS

Term Definition

Generative Design It is a design method in which the output – image, sound, architectural models, animation – is generated by a set of rules or an Algorithm, normally by using a computer program.

Generative Design System

It is a production system that does not specify the design artifact, but instead specifies a higher-level specification that encodes the making of the artifact, or the design procedure.

Algorithmic Generative Systems They are the basic components in all generative system.

Parametric Systems They are a part of the algorithmic system.

Computation

It is the procedure of calculating, i.e. determining something by mathematical or logical methods. It is about rationalization, reasoning, logic, algorithm, deduction, induction, extrapolation, exploration, and estimation.

Computerization

It is the act of entering, processing, or storing information in a computer or a computer system. It is about automation, mechanization, digitization, and conversion.

Computational Design

It is an approach that operates mostly through the facilities of mathematical thinking due to the calculation skills of computers.

Algorithm It is a procedure for addressing a problem in a finite number of steps using logical if-then else operations.

Biology It is the scientific study of life and living organisms, from one-celled creatures to the most complex living organism of all the human being.

Architecture A general term to describe buildings and other physical structures.

Bio-Architecture It is the art and science of designing and building spaces which create, support and enhance life and living systems.

Morphogenesis It is a concept used in a number of disciplines including biology, geology, crystallography, engineering, urban studies, art and architecture.

Plant Morphogenesis

It is the formation of shape and structure by Co-ordination of cell shape, growth, and proliferation by mitosis.

Digital Morphogenesis

It is using digital media not as a representational tool for visualization but as a generative tool for the derivation of form and its transformation.

Morphogenesis in Biology

Morphogenesis is often used in a broad sense to refer to many aspects of development, but when used strictly it should mean the molding of cells and tissues into definite shapes. It is the formation of shape and structure via a coordinated process that involves changes in cell shapes, enlargement of cells and proliferation by mitosis.

Efflorescence This code word for a process of life and growth; instills botanic transformation in both a physical and metaphorical sense.

BIODIGITAL MORPHOGENESIS IN ARCHITECTURE xvii

VII. ASSUMPTION

Using of computers in different phases of architectural design not just for drafting and visualization, but in other phases of design process; such as functional relationships, form finding and industrial and manufacturing production.

A Computer could be a generative tool which could be used in the design process by depending on algorithmic approach for designing as there must be a synergetic relationship between the human mind and the computer system. Such a synergy is possible only through the use of algorithmic strategies that ensure a complementary and dialectic relationship between the humans to realize, overcome and ultimately surpass their own physical and mental limitations.

Collaboration between biology and architecture in design would generate a bio-design approach which could be useful for the environment.

It has been discovered that, there is potential inherent between biology and architecture so, that would help for collaboration between them. If they could be collaborated, they also would be collaborated in software. Such hybridization in software would generate architectural forms which could simulate organic growth in order to confirm the ability of form to evolve.

Starting design with a biological base would have its effect on the building form as it would be related to its structure and generate different generations of forms belonging to one family.

VIII. AIMS AND OBJECTIVES The main aim of this research is to highlight the importance of using computer as a

generative tool in the design process depending on scripting and algorithmic architecture approach of designing.

Realizing a complete collaboration between biology and architecture in order to generate a bio design approach of designing.

Studying the differences between biological morphogenesis, digital morphogenesis and their collaboration to generate a bio-digital architecture approach. That approach differs from any other approach as it starts designing a building from a biological base depending on the potential inherent exists between biology and architecture which encourage for hybridization between them in software. That hybridization could be realized by generating a biological plug-in software to be a part of an architectural software. This plug-in would help the designers to deal with a biological element through that plug-in by just opening the architectural software so, there would be no need to open any biological software to export their files to be opened by the architectural ones. After these form are being generated from that plug-in, they would be engineered and detailed through the architectural softeware in order to be implemented.

BIODIGITAL MORPHOGENESIS IN ARCHITECTURE xviii

After analyzing the biological base, its structure should be studied in order to convert it to be a building structure and generate different generations of forms belonged to one family.

IX. METHODOLOGY The research explores the bio digital design approach and the development of form generation due to transformation in the structure inspired from a biological element.

First, the research defines the meaning of the generative design and the role of the computer as a part of the design process which could be named as morphogenesis , defining the algorithmic approach for designing as it would make connections between the human mind and the computer system.

Second, defining the collaboration between biology and architecture to generate the bio design approach of designing by the collaboration of nature, science and creativity, defining the differences between the biological morphogenesis and the digital morphogenesis and the importance of studying them.

Third, studying the bio digital architecture approach of designing as it would be assumed that there are similarities between biology and architecture and these similarities encourage to make a complete hybridization between biology and architecture in software and that would help to start analyzing a biological base's structure in order to generate more generations of forms belonged to one family.

A. Literature review

Understanding the meaning of generative design and using of computers as a generative tool of design.

Understanding the meaning of algorithmic architecture and its role in writing scripting and programming new software to generate designs.

Understanding the meaning of bio design approach of designing which is the result of the collaboration of biology and architecture.

Understanding the differences between biological morphogenesis and digital morphogenesis.

B. Application and conclusion

Understanding the meaning of bio digital design approach of designing Finding the similarities between biology and architecture and assuming a trail of

hybridization between them in software in order to produce a plug-in of a biological software to be a part of architectural program like a hybridization between (X-frog) and (Maya, Rhino Ceros).

Analyzing the structure of a biological element to be a structure of a building Discussing some different case studies. Conclusion

BIODIGITAL MORPHOGENESIS IN ARCHITECTURE xix

X. THESIS STRUCTURE

To achieve the above mentioned aims and objectives, several steps should be followed including five chapters as follows:

Figure 1: Structure Thesis Source: (The Researcher, 2015)

BIODIGITAL MORPHOGENESIS IN ARCHITECTURE xx

BIODIGITAL MORPHOGENESIS IN ARCHITECTURE 1

Generative Design and Algorithms PART -1-


CHAPTER -1- GENERATIVE DESIGN

“The Natural science is concerned with how things are . . . design on the other hand is concerned with how things ought to be” (Simon, 1969)

Figure 2: Chapter (1) Structure Source: (The Researcher, 2015)


Chapter 1: Generative Design 1.1 Introduction

Computational systems have emerged as a fundamental keystone in architectural design during the last decades, marking the rise of a new area of study that engages with design cognition, computation and generative principles in contemporary design practice (Gero & Tyugu, 1994). Gero enlists two main areas in the development of computer aided design: “the representation and production of the geometry and topology of designed objects” and “the representation and use of knowledge to support or carry the synthesis of designs”. While the first category relates to the general use off-the-shelf CAD tools that aim to increase the efficiency or aim to automate design and drafting activities, the second has given birth to novel generative approaches that regard computation as an aid to the design process and to explore design ideas. Generative design systems allow the formation of complex compositions, both formal and conceptual, through the implementation of a simple set of operations and parameters. This new understanding marks the emergence of innovative modes of design thinking. Here, the main challenge lies in the cultivation of computation as a tool that complements the designer’s capabilities in the conceptualization and production of design artifacts in the contemporary architectural agenda (Ahlquist & Menges, 2011).

1.2 Generative Design Definitions

It is a design method in which the output – image, sound, architectural models, animation – is generated by a set of rules or an Algorithm, normally by using a computer program (Bohnacker, Gross, Laub, & Lazzeroni, 2012).

Using a set of rules or an algorithm in order to generate designs or what could be named as architectural forms (Krish, 2011).

Generative design is to use your computer

as a design stakeholder to co-generate alternative design solutions/ morphologies which are then chosen by the designers to suit their requirements. Generative design is combined with computation through a generative design system using mechanisms (Tang & Chang, 2005).

Generative design is a design methodology that differs from other design approaches insofar that during the design process the designer does not interact with materials and products in a direct (“hands-on”) way but via a generative system (Fischer, Ceccato, & Frazer, 2001).

Figure 3: Generative Design Elements.

Source: (Bohnacker, Gross, Laub, & Lazzeroni, 2012)

Figure 4: Generative Design Approach Source: (Fischer, Ceccato, & Frazer, 2001)


Generative Design is a morphogenetic process using algorithms structured as not-linear systems for endless unique and un-repeatable results performed by an idea-code, as in Nature (Soddu & Colabella, 1995).

Generative design approaches have been emerged from the search for strategies to facilitate the exploration of alternative solutions in design, using computers as variance producing engines to navigate large solution spaces and to come up with unexpected solutions. In generative design, algorithms are often used to produce an array of alternative solutions based on predefined goals and constraints, which the designer then evaluates to select the most appropriate or interesting. Design decisions that require a more context-based understanding and judgment are typically left to be decided upon by designers (Negroponte, 1975).

1.3 Properties of Generative Design

Most generative design is based on parametric modeling. It is a fast method of exploring design possibilities that is used in various design fields such as Art, Architecture, Communication Design, and Product Design. Typically, generative design has:

A design schema that provides criteria requirements A means of creating variations A means of selecting desirable outcomes

Based on these characteristics, generative design environments provide significant advantages for conceptual design as the emphasis is on exploration of alternatives. However, one of the most significant advantages is that generative design environments are dynamic and interactive, providing real-time visual feedbacks, as the geometric and dimensional variations are manipulated (Guidera, 2011).

Some generative schemes use genetic algorithms to create variations. Some use just random numbers. Generative design has been inspired by natural design processes, whereby designs are developed as genetic variations through mutation and crossovers (Guidera, 2011).

1.4 Differences between the Traditional Method of Design and Generative Design

Herbert, Lionel March, Yahuda E. Kalay, and many others, discussed the concept of (generate-test) design loops. They defined design as a result composed by two engines, one is involved with generation and the other is involved with evaluation.

In architecture studios, the traditional design process starts with collecting data and investigating sites, build a concept of the design, and then analyze possibilities based on an array of criteria which had been defined or received from clients. This process can be loosely illustrated as shown below in a three-node diagram. One of the limitations in this process appears in the number of solutions that the "design language" node can generate. It is usually very few, if not one (El-khaldi, 2007).


History is a great resource. It is easy to understand how phenomena mature or decay, last or end, continue or break. Most architects like Durans, Sullivan, Le Corbusier and others prescribed their processes. All of them externalized their design processes after building a body of work, defining a certain style, and working by a set of architectural elements for certain goals. As for computing, it is known how L systems or Cellular automata and others were created for simulation. It was after phenomena were broken down to units, relationships and behaviors. Generative systems can only be built after defining design objectives, processes and relationships (El-khaldi, 2007).

The following illustration shows a possible diagram for integrating generative systems in design. A fourth node, "generation", is placed between concept and evaluation. The main gain behind integrating such systems within a process is the ability to test "many" generated solutions and be able to compare between them. This allows for capturing more possible design solutions for every conceptual design language. It is important to realize that generative systems are specific context as they come after a formalized (defined) design language (El-khaldi, 2007).

Figure 5: Traditional Design Loop Source: (El-khaldi, 2007)

Figure 6: Generative Design Loop Source: (El-khaldi, 2007)


1.5 Generative Design System in Architecture

Design has a dual meaning. It simultaneously means the act of designing an object (design as an activity), and the designed object as an end result of the design act (design as an artifact). This distinction is central in generative design systems (Gursel, 2012).

1.5.1 Generative Design System Definition. A generative system is a production system that does not specify the design artifact, but instead specifies a higher-level specification that encodes the “making” of the artifact, or the design procedure. Therefore, generative systems are said to precede formation over form, which indicates a fundamental shift from the modeling of a designed “object” to modeling of the design’s “logic” (Leach, 2009).

Generative design systems require the computational specification of the principles of the formation of a design (artifact), which opens up a design space for the exploration of design alternatives and variations. As such, generative systems suggest the delegation of some design tasks and intelligence from the human designer to the generative system, thereby claiming a degree of autonomy. However this does not mean that the generative system now becomes the designer, but that the human designer externalizes and encodes some of its working intelligence into the “generator” to carry out certain design tasks or solve problems. These specifications can be rules, constraints, parametric dependencies, genetic structures, case-bases etc. (Gursel, 2012).

1.5.2 Historical Background of the Generative Design Systems. Generative logic is nothing but new to design and architecture. Mitchell traces the roots of generative systems in general to philosophy, literature and musical composition, and architectural generative systems in particular to Leonardo da Vinci (Mitchell, 1979). According to Hanna and Barber, Jean-Nicolas-Louis Durand followed an analogue generative approach for the creation of neo-classical architecture by applying different combinations of building elements (Hanna & Barber, 2001).

Louis Sullivan’s plates that describe processes for reproducing floral ornamentation based on geometrical constructs, and Le Corbusier’s Five Points of Architecture in which he formalized his style are accounted as examples of analogue generative systems before the use of computation in architecture (El-khaldi, 2007).

Figure 7: Generative System Concept Source: (Bohnacker, Gross, Laub, & Lazzeroni, 2012)


Peter Eisenman, used analogue transformational rules in architectural design synthesis (Gandelsonas, 1982). Eisenman’s design concept operates on a system (a language) that permits creative action, generating an infinite number of utterances and making infinite use of finite means (Hays, 2000). Eisenman reflects this practice on the design of a series of houses (House I - X), where he states that “the house is not an object in the traditional sense - that is the end result of a process – but more accurately a record of a process” (Eisenman, Gass, & Gutman, 1977). This emphasis on the process over the end product, and the act of conceiving of architectural form suggests a generative principle as the essential driver during architectural synthesis (Gursel, 2012).

1.5.3 Generative Design Process

Figure 8: A System of Architectural Ornament According with a Philosophy of Man’s Powers

Source: (Morrison & Samuelson, 2001)

Figure 9: Generative Design Process Source: (Bohnacker, Gross, Laub, & Lazzeroni, 2012)


The process of generative formation requires four elements: the start conditions and parameters (input), a generative mechanism (rules, algorithms etc.), the act of generation of the variants (output), and the selection of the best variant. The design artifact does not materialize until the fourth step, therefore a generative system is considered as a production system rather a representational construct. Moreover, “the generative role of new digital techniques is accomplished through the designer’s simultaneous interpretation and manipulation of a computational construct… The capacity of digital, computational architectures to generate “new” designs is, therefore, highly dependent on the designer’s perceptual and cognitive abilities, as continuous, dynamic processes ground the emergent form” (Kolarevic, 2000).

1.5.4 Categories of Generative Design Systems. Generative systems can be roughly classified into two categories: linguistic and biological (Shea, 2004).

A linguistic system is a grammar-based formalism where a set of compositional rules (syntax) govern and shape the design (semantics). The computational implementation of linguistic generative systems primarily manifests itself in shape grammars. Shape grammars define and apply a set of modification rules on a starter object (a shape) in order to generate new complex design. According to Knight, shape grammars are descriptive and generative in a way that the modification rules both describe the forms of the generated designs, and generate or compute designs (Knight & Stiny, 2001).

Biological generative design systems, on the other hand, adopt a different generative strategy, which takes nature and complex living organisms as a precedent and applies its principles in the derivation and transformation of architectural form (Hensel, Menges, & Weinstock, 2010). Vincent further articulates on the emphasis placed on the becoming of the form rather than the resulting form itself (Vincent, 2009). Natural emergence, describing the ways in which complex natural systems evolve, self-organize and grow, contribute to architectural knowledge creation towards the production of complex architectural, and especially performative design (Weinstock, 2010). As such, a deeper engagement with the nature is pursued, which investigates the ways in which the principles of nature present useful concepts such as functional integration, performative capacity and material resourcefulness (Ahlquist & Menges, 2011).

1.5.5 Generative Systems Approaches

Figure 10: Generative Systems Approaches Source: (The Researcher based on (Bohnacker, Gross, Laub, & Lazzeroni, 2012), 2015)


1.5.5.1 Algorithmic generative systems. Algorithmic systems are the basic components in all generative system. They are the most malleable when it comes to customization because they don't impose a specific structure, or relationship, or representation, or units' type or context. They only provide a working environment as opposed to recipes to implement. For this reason, these systems are the most popular of all systems among architects. In fact, designing with algorithms is not a totally new concept in architecture. As many architects repackaged their design languages in algorithmic descriptions for others to implement. Thinking in terms of algorithms is a mapping process of design objectives onto step-by-step descriptions. Such a process helps designers decompose context, understand relationships and devise methods to judge the utility of the outcome (El-khaldi, 2007).

1.5.5.2 Parametric systems. Algorithmic systems are the basic component on top of any other specific systems. Parametric systems are a part of the algorithmic system. These are built around two concepts: Associativity and/or Inheritance by hierarchy. Parametric systems in architecture are usually understood in the context of: A) Geometric Modelers B) Animation packagers. Modelers like CATIA, Generative Components, or Solid works can create geometry, structure data within hierarchies and create dependencies through relationships (El-khaldi, 2007).

Animation packages like 3D Max, Cinema-4D and Maya offer a different type of parametric systems where designers can relate elements to each other through dynamics and inverse kinematics solvers. The fact is that the parametric system is capable of associating elements with another one (El-khaldi, 2007).

1.5.5.3 Formalisms 1.5.5.3.1 L-systems. Parametric systems are a specific case of algorithmic

systems, (ones with associations). L-Systems are more specific algorithmic systems. These are rule-based systems, which is defined as formalisms. Rules are usually presented as a left side, arrow and a right side. For example (X→Y), this means find X and replace it by Y (El-khaldi, 2007).

It is important to note that these formalisms were created to simulate very specific phenomena as opposed to provide a working platform like Algorithmic or Parametric systems. For example: L-systems were used to simulate botanic growth, Cellular automata were created to simulate reproduction, Fractals were created to simulate self-similarity in nature, and shape grammars were created to simulate human ability to see, or compute visually (El-khaldi, 2007).

1.5.5.3.2 Cellular automata systems. L-systems are the first of the four formalisms as it was the least flexible of all systems. Its symbols are limited to one type of meaning, alphabets (El-khaldi, 2007).

Cellular Automata systems offer a richer environment for its symbols as they are not limited to one type of meaning. A symbol in CA (cell) can refer to "Color" with its variations (black, white, etc.), or size (with various numbers), location (in reference to many axes), etc. or even different objects (El-khaldi, 2007).


1.5.5.3.3 Fractal systems. L-systems and Cellular Automata maintain the size of their smallest units. Rules replace alphabets or cells without breaking them to smaller ones. The concept of the "smallest unit" is not applicable to Fractal Systems for they are based on mathematical models of recursion. Fractal algorithms will recursively fracture elements first, and then replace them by new ones (El-khaldi, 2007).

1.5.5.3.4 Shape grammars. The previously discussed formalisms (L-systems, Cellular Automata, and Fractals) recognized units as discrete in reference to their locations (boundaries) assuming they have fixed identities throughout the computation process. In Shape Grammars, units are recognized both by fixed and flexible definitions. The first relies on "identity" (like other systems) where the second relies on "embedding" (intrinsic to shape grammars). These systems were built to capture visual calculation processes in design. They handle recognition through the human ability to see. Mapping such a concept to the world of discrete units that computers understand requires very sophisticated algorithms. Ones that can pick shapes wherever they may be. This fact limited the implementation of shape grammars to analog processes performed by humans, or computer-automated ones working with discrete units only (El-khaldi, 2007).

1.6 Generative Model

In generative design, algorithmic procedures are often used to produce arrays of alternative solutions based on predefined goals and constraints, which the designer then evaluates to select the most appropriate or interesting (Herr & Kvan, 2007).

This position is reiterated by Oxman, who stated that “the generative model is the design of, and interaction with, complex mechanisms that deal with the emergence of forms deriving from generative rules, relations and principles.” However, it was argued that designer interactivity is a key component. It has been stated that “Interaction has a major priority in this model” and added that “in order to employ generative techniques in design, there is a need for an interactive module that provides control and choices for the designer to guide the selection of desired solutions.” (Oxman, 2006).

1.6.1 Categories of Generative Models. There is a rich theoretical body of research-related applications of generative models. Two main distinct current sub-approaches are shape grammars and evolutionary models. Shape grammars are mathematical expressions for computational mechanisms that drive shape generation processes through transformational rules. Shape grammars are well-known in the design research literature. Evolutionary form-generation techniques are based on evolutionary models of natural generation that can be applied to generative processes in design. There was no examples of compound models combining generative mechanisms in formation models; however, this combination is theoretically possible (Stiny, Introduction to Shape and Shape Grammars, 1980).

Elements and their individual letter symbols represent the basic components of the model:

R = representation and formal content, G = generation, E = evaluation and P = performance.


Boundaries and arrows represent interaction type between the designer and the representational media as illustrated in the symbol schema below.

Links are represented by a line. Lines and arrows explicate interrelation links between the components of the model. Implicit and cognitive links are represented by dotted lines and explicated computational links are represented by full lines (Oxman, 2006).

According to these symbols, that model can be depicted as presented in. The designer implicitly integrates performative requirements, generative and evaluative procedures while interacting directly with the formal representation. E, P and G and their linkages with the formal procedures illustrate the implicit part of the cognitive behavior of the designer (Oxman, 2006).

1.6.1.1 Grammatical transformative design models. Shape grammar as a generative mechanism based upon formal compositional rules is perhaps the most interesting case to examine the problematic of a priori formal content in digital design. Currently, with the change of design focus from spatial composition to tectonic and material qualities, emergent properties of tectonic and morphological design content are becoming incorporated with the mathematics of grammars. As such, shape grammars are presently considered one of the potentially significant models of generation for digital design. The type of interaction with the generative mechanism is a critical issue in designing a generative system in digital design. Shea (2004) has demonstrated the potential of such an approach in digital design generation. Grammar definitions here adapt a more abstract, less compositional and more topological character. Computational system is based upon three-dimensional, periodic spatial tiling and is an important contribution in the direction towards more topological and less compositional grammars. It is based on computational implementation of the mathematical description of the tiling material as a basic generative grammar related to shape-grammar principles and is employed as a generative tool for design (Oxman, 2006).

1.6.1.2 Evolutionary design models. In an evolutionary model of design, form

emergence is considered to be the result of an evolutionary process. Evolutionary techniques have been part of a long research tradition exploring computational mechanisms of form generation. Form generation is derived from an internal genetic coding that replaces traditional interaction with the form itself. There also exists a significant body of theory dealing with problems of emergence and the behavior of complex systems as related to evolutionary models (Oxman, 2006).

Figure 11: Generative Model

Source: (Oxman, 2006)


Genetic algorithms have become a major tool in various research areas. John Holland is the founder of the domain of genetic algorithms. These are parallel computational representations of the processes of variation, recombination and selection on the basis of fitness underlying most processes of evolution and adaptation (Holland, 1992). Genetic algorithms were first employed in a problem-solving and optimization context in which stated criteria and goals were defined and controlled by a fitness function. In this type of automatic generative process there was no interactive consideration. However, in design the provision of interactivity and the formulation and the type of interaction of a certain generative mechanism are essential (Oxman, 2006).

1.7 Conclusion

After reviewing that chapter, it could be concluded that the generative design is a new method of design which depends on computers which are used as a part of the generative process as they are used as a generative tool for generating many verities of solutions and that could be realized by writing the designer's idea in algorithms to produce a code of any idea and that code contains some variables and that variables depends on the type of the used approach which had been used to write down the idea in algorithms, that approaches could be algorithmic, parametric or formalisms which divide into four types, L-Systems, Cellular Automata systems, Fractal Systems, Shape Grammars. All of these approaches have algorithmic base, by changing the value of these variables, a new solution would be generated so that there would be a variety to out puts which would be evaluated by the designer in order to reach the desirable one. If the output didn't meet the designer's satisfaction, it would be easy for the designer to do some changes in the written algorithms or in the value of the variables in order to generate all the optional solutions until the designer choose one of them which realize the desirable one.


CHAPTER - 2 - COMPUTATION AND PROGRAMMING

“Design = Calculating” (Stiny, 2012)



Chapter 2: Computation and Programming 2.1 Introduction

''Computer is stupid, but it is fast'' (Bohnacker, Gross, Laub, & Lazzeroni, 2012)

A computer is a machine that transforms input data into output data. Thereby

data takes the form of a finite sequence of bits. Hence, data can be coded as a natural number and the transformation f can be viewed as partial function on the set of natural numbers N with output out ϵ N as result of a computation of the input in ϵ N that is f(in) = out (Kotnik, 2007).

"Computers have come to stay; they are changing the world whether we like it or not, and gradually they will find their way into the offices of architects and the schools of architecture all over the world." (Sudbo, 1988). This quote was extracted from a report of an international forum held in Zurich

in 1987, on 'architectural education and the information explosion'. It sets the background of the general feeling concerning computers 'overture' in architectural practice and education. There are several reasons to support such a view. Some are related to developments in computers technology, whereas others are associated with our understanding of the computer's role in design (Sudbo, 1988).

The computer, as a tool, is similar to an extension of the mind. Further, the computer may be situated as the mind of other tools. It encourages a repetition and variation that affects the making of many distinct things. This mind tool can be integrated into a critical process between the designer, the visualization software, and the fabrication processes. Certainly, the software programmer plays a growing role in the relationship of form generation and direct translation to fabrication techniques (Klinger, 2001).

Computing technology has achieved in the last two decades a tremendous

advance; for example processing speed and circuit density which have been increased by the

Figure 13: Algorithmic Process Done by Using A Computer Source: (The Researcher based on (Bohnacker, Gross, Laub, & Lazzeroni, 2012), 2015)

Figure 14: The Computation Process Source: (Kotnik, 2007)


order of magnitude. The software field has also progressed considerably, with new software development tools, programming languages and methodologies. This new powerful computing environment is packaged and made available to individual users in the form of 'Personal Computers', and to engineers or designers in the form of the new generation of 'Graphical Workstations' (Belhadj, 1989).

Developments in the field of computer modeling, computer graphics, and more

recently in cognitive psychology and artificial intelligence provide the theoretical basis to build fundamentally new tools to support the architectural design process, in particular for design abstraction and evaluation (Schmitt, 1987).

For the past 10 years, emerging computational tools and techniques are having a

strong impact on architectural design. Since then, architects and students of architecture are trying to embed digital methods into the design process, exploring new possibilities and challenges occurring (Agkathidis, 2011).

Such development in using computers in the field of architecture imposed some questions like;

How computation changes both Architecture and its relation to the human subject? What computers do to Architecture? Which type of programming could be used?

All these questions would be answered during that chapter.

2.1.1 Differences between Computation and Computerization. Computation is a term that differs from, but is often confused with, computerization. While computation is the procedure of calculating, i.e. determining something by mathematical or logical methods, computerization is the act of entering, processing, or storing information in a computer or a computer system. Computerization is about automation, mechanization, digitization, and conversion. Generally, it involves the digitization of entities or processes that are preconceived, predetermined, and well defined. In contrast, computation is about the exploration of indeterminate, vague, unclear, and often ill-defined processes; because of its exploratory nature, computation aims at emulating or extending the human intellect. It is about rationalization, reasoning, logic, algorithm, deduction, induction, extrapolation, exploration, and estimation. In its manifold implications, it involves problem solving, mental structures, cognition, simulation, and rule based intelligence, to name a few (Terzidis, 2006).

The dominant mode of utilizing computers in architecture today is that of

computerization; entities or processes that are already conceptualized in the designer’s mind are entered, manipulated, or stored on a computer system. In contrast, computation or computing, as a computer-based design tool, is generally limited. The problem with this situation is that designers do not take advantage of the computational power of the computer. Instead some venture into manipulations or criticisms of computer models as if they were products of computation. While research and development of software involves extensive computational techniques, mouse-based manipulations of 3D computer models are not necessarily acts of computation. For instance, it appears, from the current discourse, that mouse-based manipulations of control points on NURBS based surfaces are considered by some theorists to be acts of computing (Cuff, 2001). While the mathematical concept and


software implementation of NURBS as surfaces is a product of applied numerical computation, the rearrangement of their control points through commercial software is simply an affine transformation, i.e. a translation (Terzidis, 2006).

2.1.2 Different Visions about Using Computers in the Design Process.

“At the birth of computer graphics, it was professed that this new instrument could liberate us from the T square and that we could finally design and live in doubly curved surfaces. I do not believe that the lack of “intestinal” architecture comes from a lack of necessary tools” (Negroponte, 1975). Negroponte explained that hard technology is a means to make architecture

softer; he envisioned that computers are machines and they are the way towards a more human environment. He pointed to a new humanism, through partnership with problem-worrying by depending on those machines which enabling architects to go beyond the simplifications of the middle scale (the average man, statistics) and be responsive to the very small and the very big simultaneously (Vardouli, 2011).

The primary obstacle towards this vision is the conflict which arises between the

metaphor-rich, human oriented capital architecture and the contextual computational algebras which are yet incapable of having empathy to things important for people, like place and meaning. The consideration of this difficult question is impeded by the fact that computers actually have results (Vardouli, 2011).

“General feeling of discomfort passing through universities” (Negroponte, 1975) He said that about a work whose rapid results do not leave time to reflect on the

human in design (i.e. how people and machines deal with the built environment) (Vardouli, 2011).

“The promises and the disappointments of computer-aided Design are indicative of this tendency” (Bazjanac, 1975). Vladimir Bazjanac witnesses himself having been carried away by the

emergence of a new technology promising of a new future for mankind, in and outside architecture (Vardouli, 2011).

“Added to that is the excitement of getting into something really new, something no architect of the past knew anything about. How could he not become a believer? My early enthusiasm was really tremendous” (Bazjanac, 1975) Bazjanak located the source of his disbelief from the realms of architectural

practice. Coming in contact with the inertias of what was earlier referred to as the world’s “messy realism”, he conjured that the change in the way of architecture is exercised significantly less drastic than expected. In fact, he warned that the automation of the design process can lead to regression instead of innovation through channeling the architect’s


thought into metaphors and formal models which are imposed by the technology (Vardouli, 2011).

“The main direction of work at the Royal College of Art’s Department of Design Research is the use of computer simulation models of design processes and design organizations in the evaluation of CAD systems. The development of these computer models is based on empirical studies of a range of live design projects” (Purcell, 1975). Patrick Purcell Considered that is computer is as an alien medium, whose

incorporation in the design process has socio-anthropological implications which require intensive research (Vardouli, 2011).

“The goal of design methodology should not be systems that can design better than the humans (Make the creative leap) but rather systems that help humans design better (Computer aided design)” (Milne, 1975). Murray Milne called for a settling down from the initial enthusiasm with

computers in order to rethink about the implications of the computer in the design process, both esoterically and externally. Asserting that design methodology had been the study of methods, principles and rules for regulating the science and art of design, especially architectural design (Vardouli, 2011).

“In asking how the computer might be applied to architectural design, we must, therefore, ask ourselves what problems we know of in design that could be solved by such an army of clerks” (Alexander, 1964). Christopher Alexander considered that those computers couldn't design better

than human and they would be systems to help humans to design better (Vardouli, 2011). “Lady Lovelace Objection” (Turing, 1950). Alan Turing explained that machines couldn't be creative; this approach takes a

distance from Negroponte’s visions of machine intelligence and computer-designer partnership and places them in the level of tools for tedious, unimaginative tasks, while the human designer maintains the privilege of authorship and creativity (Vardouli, 2011). The main points which emerge from these discussions could be condensed to the following:

First, although computer aided design performs satisfactorily in controlled, constructed problems and hypothetical questions in the lab, it fails when faced with the complexities of the real world which cannot be reduced to descriptions that can be processed by a machine.

Second, the automation of the tedious stages of the design process impedes creative thinking by obligating the architect to operate within the boundaries and the language of the technology at hand

Third, before computational tools have been made for architects it is needed to understand the design process from a socio-anthropological and cognitive


perspective so as to allow for qualitative and not just quantitative changes in architecture through the use of computers (Vardouli, 2011).

The battle seemed to be lost from the beginning; human and context responsive

computer aided architecture requires science fictional artificial intelligence in order to be achieved, the morphogenetic potential of CAD is discarded as almost ludicrous and there is a commonly shared skepticism around the possibility to automate aspects of the design process in a productive way, which probably makes CAD resort to its most usual use today, that of an architectural representation. However, the dynamics of computation had been identified, carrying away the architects into “A new method and making them easily forget the old” (Negroponte, 1975). Besides this skepticism, one can discern a powerful impact of this new tool, which creates a de facto demand for digitization of architecture somewhere, somehow (Vardouli, 2011).

2.1.3 Computational Design. Computational design is an approach that operates mostly through the facilities of mathematical thinking due to the calculation skills of computers. It requires a mode of thinking, based on well-defined steps, algorithms and parameters, which are necessary for the design strategy to be developed at the initial phase of design process (Çinici, Akipek, & Yazar, 2008).

2.1.3.1 Computational design techniques. For at least twenty years now, emerging computational design and manufacturing techniques have entered the world of architecture. Since the early days of “visionary” computational architectural project proposals by Greg Lynn and NOX among others appeared, the debate about blob versus box, the notion of form, the digital esthetics and the effects of such an architecture on the city has been running. Technology moves fast, thus the early 3d modeling software such as 3d studio max, alias wave-front and others, based on animation, are now more and more being replaced by rhino and grasshopper, which make programming and parameterization of design models easier than ever (Agkathidis, 2011).

Furthermore, digital fabrication techniques are becoming widely accessible and affordable. Digitally fabrication buildings are no longer expensive, but often more affordable and efficient than traditionally planned and produced buildings. At the same time, the critique on such a design approach becomes louder: formalism, alienation to the city and the user, loss of materiality are among the strongest arguments used against the emerging so called parametric architectural examples. But there is something not easy to deny: emerging design and production technologies are having a non-reversible impact on the evolution of architectural production today and the coming future (Agkathidis, 2011).

2.1.3.2 Characteristics of computational design techniques. It should be viewed that computational design is as part of a normal progression in which the designer and the artifact are separated by an increasing number of levels of indirection, that in turn introduce higher levels of expression and control. Opponents of this may question whether introducing these levels of indirection is in fact progress, arguing that intuition and spontaneity will be inhibited with the increased remoteness between the designer and artifact. Happily these layers of indirection are not arranged linearly, but can be configured to form a closed loop. The advent of digitally controlled fabrication means that the geometrically aware and computationally enabled designer is as close to the materialization


as in the original craft process, but with precision and control and the ability to explore variation which was previously unimaginable. The question now is: what are the characteristics of computational design tools that facilitate this approach to design and what are the corresponding abstractions which need to be internalized and perationalized by designers? (Aish, 2005). The essentially themes are:

• Geometry • Composition • Algorithmic thought

2.1.3.2.1 Geometry. It is needed to start with a fundamental understanding of geometric primitives: points, planes, coordinate systems, line arc, curves, surfaces and solids. It is needed to understand what the order of a curve means, how curves and surfaces are parameterized. It is needed to understand geometric operations on these primitives: projection, intersection, union, difference, transformation. It is needed to use these primitives and operations to define relationships. It is needed to understand the stability of these geometric relationships under certain modifications and configurations (Aish, 2005).

With this understanding, there would be the opportunity to build the long chain

dependencies which would create interesting geometric configurations. What is important is not the static configuration, but the way in which some change, for example to the location of a key point or parameter, can create alternative configurations (Aish, 2005).

What becomes apparent is that the geometry of the artifact is not being designed, but

rather a control rig is being constructed, some geometry that would never be built or seen, but which indirectly controlling what would be constructed and experienced. It was the development of this sense of indirection or control through geometric dependency which is being emerged as a key design skill. By building and exercising these systems of geometric dependency it would be able to explore variation in design, indeed to explore the solution space, and to discover and validate the configuration that would finally be constructed (Aish, 2005).

2.1.3.2.2 Composition. It is pretty rare to find a building which is a realized as a

single discrete object. Normally assemblies of components are being considered to be at intermediate levels of aggregation and form identifiable sub-systems. While these

Figure 15: Computational Design Techniques Source: (The researcher based on (Aish, 2005), 2015)


components may be pre-defined, or the subsystems may follow established industry conventions, there are increasing opportunities for each design to use mass customization and digital fabrication to define project specific components. The question then is: how could the total building concept been broken down into sub-systems and components? What are the conceptual or practical fault lines which might suggest this decomposition? There may in fact be multiple decompositions, some to be used in the conceptual, form finding phase, and others for realization and fabrications which, for example, might impose dimensions constraints associated with different materials or fabrications processes. Certainly, that developing and refining compositional strategies are a key aspect of design skills. There is a tremendous advantage in using computational design tools which directly support the idea of ‘composition’ and which allow these strategies to be developed and tested (Aish, 2005).

2.1.3.2.3 Algorithmic thought. At one level these is a desire to explore geometric subtleties which go beyond what hand-eye coordination can deliver. At another level there is a desire to apply ideas of consistency or controlled unpredictability over large data sets, for example representing a building facade. Essentially this geometry cannot be drawn. It has to be computed. If it is to be computed, then there has to be an algorithm. To be original and to be in control, the designer has to understand, if not originate, his own algorithm, and know how to drive it (i.e. know what are valid inputs and know how to interpret, verify and validate the results and know the limits to the solution space) (Aish, 2005).

Does this mean that the designer of the future has to be a programmer? No, but

it might help. Certainly, developing an ability to think algorithmically will emerge as a key design skill. But how can we encourage the development of these skills without demanding that designers become programmers? A potentially fruitful approach is to introduce the necessary logical formalism in very small doses. This has the important advantages for the designer in that he can discover the value of embedding ‘logic’ in his design model in a ‘declarative’ form without having to completely master all the constructs normally associated with a procedural programming language. But what is being learnt is not expressed in some ‘cut-down’ over simplified syntax, but uses established programming conventions, so that as the designer becomes more computationally expressive, he can build on these initial steps (Aish, 2005).

Most importantly, algorithmic design does not imply that subjectivity is out of

the loop, or even that ‘hand-eye coordination’ is redundant. What has been facilitated is the ability for the designer to embed his design logic within an interactive design system which is driven by the designer’s hand and evaluated by the designer’s eye. This follows the fundamental precept of design that of the combining intuition and precision into a single process and with the results of that process integrated and embodied in the same artifact (Aish, 2005).

At the foundation of computational design is the relationship between tools and skills. It is should matching tools to the concepts around which designers want to build their skills. The expectation is that geometric skills, compositional skills and algorithmic skills will be the key to future design (Aish, 2005).


2.1.4 Differences between Conventional Design and Computational Design. A comparison was made between conventional design and computational design, the latter design approach has been differentiated as an indirect one, where the designer did not directly draw the geometry, but has an indirect, more arguably and more powerful way of controlling that geometry using computational design tools (Aish, 2005).

On the other hand, these levels of indirection could be seen as cognitive

obstacles, since the traditional design has been based on direct hand-eye coordination. This led to think on design pedagogy, and its adaptation process to the contemporary approaches in design. Studies on tools development seem to seize an intermediate level of computation, where the geometric constructs of visual computation, are equally operative as script-based algorithmic operations. In the perceptual level, it offers an instant visual platform of design besides coding. The intermediate level of computation is an important attempt to ease computation by making it more user-friendly even in it’s the highest level of use (Aish, 2005). 2.2 Algorithms

2.2.1 The Origin of the Word Algorithm and Definitions. The word Algorithm

is not Greek. Its origin is Arabic, based on a concept attributed to an 8th century Persian mathematician named Al-Khwarizmi (Terzidis, 2006).

An algorithm is a procedure for addressing a problem in a finite number of steps using logical if-then else operations (Terzidis, 2006).

An algorithm is a procedure to accomplish a specific task (Skiena, 2008).

An algorithm is the idea behind any reasonable computer program (Skiena, 2008).

An algorithmic problem is specified by describing the complete set of instances it must work on and of its output after running on one of these instances (Skiena, 2008).

2.2.2 Expressing Algorithms. Reasoning about an algorithm is impossible without a careful description of the sequence of steps to be performed.

The three most common forms of algorithmic notation are (1) English (2) Pseudo code (3) A real programming language. English is the most natural but least precise programming language, while Java

and C/C++ are precise but difficult to write and understand. Pseudo code is generally useful because it represents a happy medium (Skiena, 2008).


The choice of which notation is best depends upon which method is most comfortable. The ideas of an algorithm in English is being described, moving to a more formal, programming-language-like pseudo code or even real code to clarify sufficiently tricky details (Skiena, 2008).

Pseudo code is perhaps the most mysterious of the bunch, but it is best defined

as a programming language that never complains about syntax errors. All three methods are useful because there is a natural tradeoff between greater ease of expression and precision (Skiena, 2008).

2.2.3 Algorithmic Design. Algorithmic design enables the role of the designer

to shift from “architecture programming” to “programming architecture.” Rather than investing in arrested conflicts, computational terms might be better exploited by this alternative choice. For the first time perhaps, architectural design might be aligned with neither formalism nor rationalism but with intelligent form and traceable creativity (Terzidis, 2006).

Algorithm design and analysis is not just theory, but an important tool to be

pulled out and used as needed (Skiena, 2008).

2.2.3.1 Algorithmic design requirements. The techniques of algorithm design form one of the core practical technologies of computer science. Designing correct, efficient, and implementable algorithms for real-world problems requires access to two distinct bodies of knowledge:

Techniques Resources

2.2.3.1.1 Techniques. Good algorithm designers understand several

fundamental algorithm design techniques, including data structures, dynamic programming, depth-first search, backtracking, and heuristics. Perhaps the single most important design technique is modeling which is the art of abstracting a messy real-world application into a clean problem suitable for algorithmic attack (Skiena, 2008).

2.2.3.1.2 Resources. Good algorithm designers stand on the shoulders of giants. Rather than laboring from scratch to produce a new algorithm for every task, they can figure out what is known about a particular problem. Rather than re-implementing popular algorithms from scratch, they seek existing implementations to serve as a starting point. They are familiar with many classic algorithmic problems, which provide sufficient source material to model most any application (Skiena, 2008).

2.2.4 Algorithm Problems. In practice, algorithm problems do not arise at the beginning of a large project. Rather, they typically arise as sub-problems when it becomes clear that the programmer does not know how to proceed or that the current solution is inadequate (Skiena, 2008).


2.2.4.1 Algorithmic problems classification. The design techniques are very important for other algorithmic problems. Skiena has classified the common algorithmic problems arose in practice into the following types. It should be started with data structure design, because one of the most dramatic algorithmic improvements via appropriate data structures occurs in sorting. Selection sort is a simple-to-code algorithm that repeatedly extracts the smallest remaining element from the unsorted part of the problem:

2.2.5 Problem Solving. People make decisions every day to solve problems that affect their lives. The problems may be as unimportant as what to watch on television or as important as choosing a new profession. If a bad decision is made, time and resources are wasted, so it’s important that people know how to make decisions well (Sprankle & Hubbard, 2012).

This is a catalog of algorithmic problems that arise commonly in practice. It describes what is known about them and gives suggestions about how best to proceed if the problem arises in your application (Skiena, 2008).

There are six steps to follow to ensure the best decision. These six steps in problem solving include the following:

1. Identify the problem. The first step toward solving a problem is to identify the problem. If the problem hasn't been identified, it cannot be solved.

2. Understand the problem. It must be understood what is involved in the problem before continuing toward the solution. This includes understanding the knowledge base of the person or machine for whom the problem are being solved. When working with a computer, its knowledge base is the limited instructions which the computer can understand them through the particular language or the application used to solve the problem.

3. Identify alternative ways to solve the problem. This list should be as complete as

possible. It is wanted to talk to other people to find other solutions than those which have been identified. Alternative solutions must be acceptable ones.

4. Select the best way to solve the problem from the list of alternative solutions. In

this step, it is needed to identify and evaluate the pros and cons of each possible solution before selecting the best one. In order to do this, it is needed to select criteria for the evaluation. These criteria will serve as the guidelines for evaluating each solution.

1. Data Structures 2. Numerical Problems 3. Combinatorial Problems 4. Graph Problems: Polynomial-Time 5. Graph Problems: Hard Problems 6. Computational Geometry 7. Set and String Problems 8. Algorithmic Resources

Figure 16: Algorithmic Problems Classification Source: (Skiena, 2008)


5. List instructions that enable to solve the problem using the selected solution. These numbered, step-by-step instructions must fall within the knowledge base set up in step 2. No instruction can be used unless the individual or the machine can understand it. This can be very limiting, especially when working with computers.

6. Evaluate the solution. To evaluate or test a solution means to check its result to see

if it is correct, and to see if it satisfies the needs of the person(s) with the problem. If the result is either incorrect or unsatisfactory, then the problem solver must review the list of instructions to see that they are correct or start the process all over again (Sprankle & Hubbard, 2012).

2.2.5.1 Types of problem solution 2.2.5.1.1 Algorithmic solution. Problems do not always have straightforward

solutions. Some problems can be solved with a series of actions. These solutions are called Algorithmic solutions. Once the alternatives have been eliminated, for example, and once one has chosen the best among several methods of balancing the checkbook, the solution can be reached by completing the actions in steps. These steps are called the Algorithm (Sprankle & Hubbard, 2012).

2.2.5.1.2 Heuristic solutions. The solutions of other problems are not so straightforward. These solutions require reasoning built on knowledge and experience, and a process of trial and error. Solutions that cannot be reached through a direct set of steps are called Heuristic Solutions (Sprankle & Hubbard, 2012).

The problem solver can use the six steps for both algorithmic and heuristic solutions. However, in step 6, evaluating the solution, the correctness and appropriateness of heuristic solutions are far less certain. It’s easy to tell if the completed checkbook balance is correct and satisfactory, but it’s hard to tell if the chosen solution is the best one. With heuristic solutions, the problem solver will often need to follow the six steps more than once, carefully evaluating each possible solution before deciding which is best.

Furthermore, this same solution may not be correct and satisfactory at another time, so the problem solver may have to reevaluate and resolve the same problem later. The chosen solution that did well in January may do poorly in June. Most problems require a combination of the two kinds of solutions (Sprankle & Hubbard, 2012).

2.2.5.2 Computers as a tool to solve problems. Computers are built to deal with

algorithmic solutions, which are often difficult or very time consuming for humans. People are better than computers at developing heuristic solutions. The difficulty of using computers in solving problems lies in the programming (Sprankle & Hubbard, 2012).

The field of computers that deals with heuristic types of problems is called

artificial intelligence. Artificial intelligence enables a computer to do things like build its own knowledge bank and speak in a human language. As a result, the computer’s problem-solving abilities are similar to those of a human being. Artificial intelligence is an expanding computer field, especially with the increased use of Robotics (Sprankle & Hubbard, 2012).


Until computers can be built to think like humans, people will process most heuristic solutions and computers will process many algorithmic solutions. Heuristic problem solving can help to determine alternative solutions. However, for computer use, they must be transformed into an algorithmic format (Sprankle & Hubbard, 2012).

2.2.5.3 Difficulties with problem solving. The problem-solving process is not easy. It takes practice and time to be perfect, but in the long run the process proves to be of great benefit. When solving problems on the computer, one of the most difficult tasks for the problem solver is writing the instructions. The computer is a tool that will perform only tasks that the user can explain (Sprankle & Hubbard, 2012).

The computer has a specific system of communication that programmers and

users must learn. This system demands that no step in the solution to a problem be left unstated and that all steps be in the proper order. It is must assumed the computer knows nothing except what it is told and think of it as an ignorant but efficient aid to problem solving (Sprankle & Hubbard, 2012).

2.2.6 Algorithms in Computational Design. There are different levels of using computational capabilities in custom computer aided architectural design tools. According to that, the lowest level for the use of computation is computerized design, in which computer algorithms are used only for drafting functions (Aish, 2005).

No or only limited computational power is used in this most common utilization.

Hence, custom CAD tools are examples of lowest algorithmic level in design, and the parametric modeling skills are not capable enough. High level of parametric modeling skill means using the computational power in a design process. This level requires the use of explicit definitions, algorithms and thus a dynamic design computation strategy. The question is the use of scripting and programming as computational design technology and its pedagogical consequences. But it also brings the question of ‘Is designer becoming a coder?’ as one of the most mind-busying concerns in the schools of architecture. Thus, one of the most important aspects of computational design is the increasing number of levels of indirection. These levels of indirection mean the introduction of higher levels of expression and control (Aish, 2005).

2.3 Programming

2.3.1 Introduction. In the field of Generative Design (GD), Visual

Programming Languages (VPLs), such as Grasshopper, are becoming increasingly popular compared to the traditional Textual Programming Languages (TPLs) provided by CAD applications, such as Rhino Script. This reaction is explained by the relative obsolescence of these TPLs and the faster learning curve of VPLs. However, modern TPLs offer a variety of linguistic features designed to overcome the limitations of traditional TPLs, making them hypothetical competitors to VPLs. It is reconsidered the role of TPLs in the design process and a comparative study of VPLs and modern TPLs is presented. It is found that modern TPLs can be more productive than VPLs, especially, for large scale and complex design tasks (Leitão, Santos, & Lopes, 2012).


2.3.2 Coding. Throughout architecture history, coding has been a means of

expressing rules, constraints and systems that are relevant for the architectural design process. Among other meanings (e.g., statutory, representation and production codes), coding in architectural design can be understood as the representation of algorithmic processes that express architectural concepts or solve architectural problems (Leitão, Santos, & Lopes, 2012).

Even before the invention of digital computers, algorithms were applied and

incorporated in the design process (Coutinho, Costa, Duarte, & Kruger, 2011). Computers popularized and extended the notion of coding in architecture by

simplifying the implementation and computation of algorithmic processes (Rocker, 2006). As a result, increasingly more architects and designers are aware of digital applications and programming techniques, and are adopting these methods as generative tools for the derivation of form (Kolarevic, 2000). Even though the improvements of direct manipulation in CAD applications led many to believe that programming was unnecessary, the work of Maeda shows the exact opposite (Maeda & Antonelli, 1999).

2.3.3 Scripting. With scripting, computer programming becomes integral to the

digital design process. It provides unique opportunities for innovation, enabling the designer to customize the software around their own predilections and modes of working. It liberates the designer by automating many routine aspects and repetitive activities of the design process, freeing-up the designer to spend more time on design thinking. Software that is modified through scripting offers a range of speculations that are not possible using the software only as the manufacturers intended it to be used. There are also significant economic benefits to automating routines and coupling them with emerging digital fabrication technologies, as time is saved at the front-end and new file-to-factory protocols can be taken advantage of. Most significantly perhaps, scripting as a computing program overlay enables the tool user (designer) to become the new tool maker (software engineer). Though scripting is not new to design, it is only recently that it has started to be regarded as integral to the designer's skill set rather than a technical specialty. Many designers are now aware of its potential, but remain hesitant (Davis, Burry, & Burry, 2011).

The biggest disadvantage of using a scripting language is the need to follow its

syntax very strictly. Although most scripting environments, such as VBAIDE, highlight mistakes and have debugging tools, such as flags and variable watches, certain syntax mistakes are not automatically detected and can take too long to be found (Celani, 2012).

Computational design methods allow automation of the design process and extension

of the standard features of CAD applications, thus transcending their limitations (Killian, 2006).Therefore, CAD software shifts from a representation tool to a medium for algorithmic computation, from which architecture can emerge (Terzidis, 2003). To apply computational methods, one must first translate the thought process into a computer program by means of a Programming Language (PL) (Leitão, Santos, & Lopes, 2012).


2.3.4 Modeling Methods in Architecture. Different methods can be used for modeling architectural form. Mitchell categorized them in three types: iconic, analogue and symbolic.

Iconic models are very literal. Typical examples of their use in architecture are plans, elevations and scale models. These models involve scale (enlargements and reductions) and projection (3D to 2D) transformations Mitchell emphasizes the role of this type of model in the generative process; according to him, in iconic models “a particular state of the system actually ‘looks like’ the potential solution which it represents”. By looking at an iconic model it is able to foresee how a building will look like when ready (Mitchell, 1978).

In analogue models, one set of properties is used to represent another analogous set of properties of the item being designed. Analog representations allow easy manipulation as Analogue generative systems often represent potential designs by settings of wheels, dials, sliding columns, etc. The operations performed to change the state of the system (that is to describe a new potential design) are thus mechanical, for example, the spinning of wheels, setting dials, sliding columns alongside each other (Celani, 2012)

Symbolic models use symbols, such as words, numbers and mathematical operators. In architecture, symbolic models are used mainly for simulations and evaluations of structural, acoustical, lighting and thermal performance. Symbols are typically displayed as mathematical formulae, tables, arrays and algorithms (Celani, 2012).

The three representation methods described by Mitchell have different abstraction

levels: iconic representations are closer to reality while symbolic representations are very abstract. Analogue representations are in between.

Figure 17: Three Different Types of Representation of Computational Design Concepts, with Different Abstraction Levels Source: (Celani, 2012)


Computational design concepts can be represented in the three ways, with different levels of abstraction. At a more concrete level, parametric relations can be specified directly on iconic representations. This is possible, for example, in certain CAD software that allows to visually specifying parametric relations between drawing entities directly on the graphic screen, such as Micro Station and the latest versions of AutoCAD (Celani, 2012).

Visual programming languages use analogue representation, in which icons are

used to indirectly represent and manipulate drawing entities. Two examples of this type of representation are Generative Component’s Symbolic Diagram and Grasshopper. These environments allow to visually describing relations between entities, without the need to write code. Textual programming languages use symbolic representations, such as text and numbers, to describe and perform operations on drawing entities. Examples of this type of representation are all CAD scripting languages, such as Rhino Script, Auto-Lisp and Visual Basic for Application (VBA) (Celani, 2012).

2.3.5 Scripting Languages or Programming Languages. Scripting languages are programming languages that allow control within a program. Differently from most programming languages, they are interpreted by the software, and do not need to be compiled. Scripting languages can vary a lot in terms of syntax and structure, depending on the software for which they were developed (Celani, 2012).

A programming language is more than just a means for instructing a computer to perform tasks: it is a formal medium for expressing ideas. Therefore, languages should match the human thinking process, including the ability to combine simple ideas and abstract complex ones. Languages conforming to these principles provide (1) primitive elements, (2) combination mechanisms, and (3) abstraction mechanisms (Abelson & Sussman, 1996).

Some examples of scripting languages for CAD are Rhino ceros, Rhino Script, Maya´s MEL, and 3DMax´s MaxScript.

Figure 18: Different Types of Programming Languages Source: (Bohnacker, Gross, Laub, & Lazzeroni, 2012)


2.3.5.1 Programming languages classification. The most used programming languages for Generative Design (GD), dividing them in two groups: Visual Programming Languages (VPLs) and Textual Programming Languages (TPLs) (Leitão, Santos, & Lopes, 2012).

2.3.5.1.1 Visual Programming Languages (VPLs). Visual programming languages or VPL’s, also called “diagrammatic programming”; allow users to create programs by moving and putting together program elements graphically rather than by typing code (Celani, 2012).

In a VPL, programs consist of iconic elements that can be interactively manipulated according to some spatial grammar (Myers B. A., 1990).

VPLs are, at least, two-dimensional (Leitão, Santos, & Lopes, 2012).

Several studies comparing VPLs and TPLs show that there is no conclusive evidence regarding their relative advantages. However, it is generally admitted that VPLs are more productive and motivating for beginners (Menzies, 2002).

VPLs scripting only contains the elements that are relevant to the design task, namely, input sliders, range components, functions that map over sequences of values, and wires establishing dataflow between components (Leitão, Santos, & Lopes, 2012).

There are several advantages of using a modern VPL instead of an old TPL (1) Less background knowledge. (2) Presentation of all language elements in the Interactive Development Environment (IDE). (3) Immediate visual feedback, facilitating defect detection and adjustment of input parameters, and allowing incremental/interactive development (Leitão, Santos, & Lopes, 2012).

Nevertheless, VPLs also have problems (1) VPL programs scale poorly with the complexity of the design task, for example, as programs grow it becomes increasingly difficult to understand what they do. (2) The absence of (sophisticated) abstraction mechanisms forces users to rely extensively on copy/paste, introducing redundancy. In turn, redundancy leads to maintenance problems because modifications in

duplicated components must be manually propagated to all instances. These problems might explain the small size and throwaway nature of the majority of visual programs when compared to the size and longevity of textual programs (Park & Holt, 2010).

Although there are many VPL alternatives for GD, Grasshopper is the most used one. This can be explained in part by the simplicity and attractiveness of its programming model and Graphical User Interface (GUI). Moreover, there is a general perception among designers that VPLs are more productive than TPLs. It is claimed that this perception is a natural response to two problems:

(1) Traditional TPLs lack domain-specific concepts. (2) They make it difficult for the user to define them (Leitão, Santos, & Lopes,

2012).


Examples of those programming languages and their programs: c, Hyper-graph for Maya, and Grasshopper for Rhinoceros3D.

2.3.5.1.2 Textual programming languages (TPLs). In a TPL, programs are a

linear sequence of characters. They are one dimensional. TPLs are considerably more productive for dealing with large-scale and complex problems and, in fact, most languages are TPLs and most programs are textual (Menzies, 2002).

Nevertheless, traditional TPLs require mastering a large set of concepts that, in many cases, are just limitations of the language. In order to understand any written Script, the reader must know:

(1) Function syntax (2) Zero-based index arrays (3) Array declaration (4) Re dimension of non-statically sized arrays. Additional knowledge is required to understand the complete example (Leitão, Santos, & Lopes, 2012).

Most TPLs have additional drawbacks: (1) The absence of a (good) IDE requires users to either remember the functionality or read extensive documentation. (2) An iterative write-compile-execute cycle results in non-interactive development (Leitão, Santos, & Lopes, 2012).

Figure 19: An Example VPL in Grasshopper Interface. Source: (Celani, 2012)


Examples of those programming languages and their programs: Rhino Script for Rhinoceros3D, MEL for Maya, Haskell & Python in Visual Basic, and JavaScript, Auto LISP, Racket and visual Scheme in CAD applications.

2.4 Conclusion

After reviewing that chapter, it could be concluded that the computer has already penetrated the design process and has become a part of it in the new architecture as it aims to emulate or extend the human intellect so it helped to generate a computational design approach which differs from the conventional design approach in depending on a computer as a apart of the design process. There are some tools of the computational design which facilitate that approach to design which need to be internalized and operationalized; Geometry, Composition and Algorithmic Thought. There is an approach of design which also depends on algorithmic thought which is called Algorithmic design. It enables the role of the designer to be shifted from Architecture programming to Programming Architecture. In order to depend on algorithms in architecture, it is important to have a background about the field of programming either coding or scripting and that could be done by dealing with any of the programming languages either VPLs or TPLs. It is found that modern TPLs can be more productive than VPLs, especially, for large scale and complex design tasks.

Figure 20: An Example of TPL in AutoCAD Interface Source: (Leitão, Santos, & Lopes, 2012)


PART-2- Bio Inspired Design and Morphogenesis


CHAPTER-3- BIO-INSPIRED DESIGN

‘From my designer’s perspective, I ask: Why can’t I design a building like a tree? A building that makes oxygen, fixes nitrogen, sequesters carbon, distils water, builds soil, accrues solar energy as fuel, makes complex sugars and food, creates microclimates, changes colors with the seasons and self-replicates. This is using nature as a model and a mentor, not as an inconvenience. It’s a delightful prospect…’

(Mcdonough & Braungart, 1998)



Chapter 3: Bio-Inspired Design

3.1 Introduction

‘It will be soft and hairy.’ (Dalí, 1922) Design is not what it used to be. In schools and in studios, in corporations and in

political institutions, designers are using their skills to tackle issues that were previously out of their bounds, from scientific visualization to interfaces, from sociological theories to possible applications and consequences of nanotechnology. They do so by teaming up for every case study with the right experts, who often seek designers’ help in order to connect their theories with real people and the real world. In the late 1960s, Ettore Sottsass famously declared that design ‘is a way of discussing society, politics, eroticism, food and even design. At the end, it is a way of building up a possible figurative utopia or metaphor about life. Design is indeed about life and, at a time of accelerated technological evolution and dramatic political, environmental, demographic, and economical concerns, designers’ presence guarantees that human beings are always kept at the center of the discussion (Myers W. , 2012).

Over the past few decades, it has been experienced dramatic changes in some of the most established dimensions of human life: time, space, matter and individuality. Today our minds must be able to synthesize such transformations, whether they are working across several time zones, traveling between satellite maps and nano-scale images, gleefully drowning in information or acting fast in order to preserve a bit of down-time. It is very important to focus on the ability of designers to grasp momentous advances in technology, science and social mores, and to convert them into useful objects and systems (Myers W. , 2012). 3.2 Definitions

3.2.1 Biology. The word biology is derived from the Greek words (bios) which

means (life) and (ologoy) which means (the study of) so it is defined as,

''It is the scientific study of life and living organisms, from one-celled creatures to the most complex living organism of all the human being.'' (An organism is a living entity consisting of one cell e.g. bacteria, or several cells e.g. animals, plants and fungi).

Biology includes the study of genes and cells that give living things their special characteristics (Simpson & Weiner, 1989).

3.2.2 Architecture. Architecture (Latin architectura after the Greek ἀρχιτέκτων – arkhitekton – from ἀρχι- "chief" and τέκτων "builder, carpenter, mason") is both the process and the product of planning, designing, and constructing buildings and other physical structures. Architectural works, in the material form of buildings, are often perceived as cultural symbols and as works of art. Historical civilizations are often identified with their surviving architectural achievements (Simpson & Weiner, 1989).


It is a general term to describe buildings and other physical structures (Simpson & Weiner, 1989).

The art and science of designing buildings and (some) non-building structures

(Simpson & Weiner, 1989). Architecture was the art which so disposes and adorns the edifices raised by men

... that the sight of them contributes to his mental health, power, and pleasure (Ruskin, 1849). "You employ stone, wood, and concrete, and with these materials you build houses and palaces: that is construction. Ingenuity is at work. But suddenly you touch my heart, you do me good. I am happy and I say: This is beautiful. That is Architecture". (Corbusier, 1927)

"Architecture starts when you carefully put two bricks together. There it begins.'' (Mies van der Rohe, 1959)

3.3 Integration between Architecture & Biology

Architecture being important organism has attracted much attention with the usage "biology" in the early 19th century by "Lamarck". Generally, the only important biological reality with regard to modern architecture was the relation between form and function. As the functional analogies, the relationship between form and function means "existence" (Bell, 2012). This fact that "form follows function" or" function follows the form" was first brought up in biology and debated for more than half a century. And this eased the propagation of biological analogies because the only way to compare architecture and the city, from the body point of view, with a living creature is to rely on the relation between form and function. The other expression, which has been borrowed from biology in architecture causing discussion on form, shape and relation, is the word "organic" that can be used in studies and researches about the structure and skeleton of animals and plants (Pourjafar, Mahmoudinejad, & Ahadian, 2011).

3.3.1 Biological analogy in Architecture. The biological discussions interpret the relations of small parts to the same organs that create a thing (Calinez, 1996). The beginning of such biological analogies can be attributed to ―Wright" and "Sullivan". While "Sullivan" first put forward these analogies, "Wright" created a kind of organic architecture by designing non-symmetrical plans, creating movement, using the environment‘s materials, and composing the architecture with the nature According to him, organic architecture has to be devoid of useless and superfluous forms (Aguar & Aguar, 2003). A biological analogy is one of the most fundamental bases of theoretical functionalism in modern architecture. However, it has ever been formal and substantial who's every organ is compared with the other, without paying attention to the soul and concept inside the organ (Pourjafar, Mahmoudinejad, & Ahadian, 2011).

3.3.2 Bio-Architecture. Bio-architecture is the art and science of designing and building spaces which create, support and enhance life and living systems (Htin & San, 2002).


Bio-Architecture is the principle ideas and key applications of organic architecture, comparing built structures to forms and patterns found in nature. It includes an exploration of local history, tradition, and cultural roots that have influenced organic architecture. In the other hand, Bio-Architecture studies the natural principles of animal and human constructions from several different perspectives, and presents a great part of the knowledge that gives origin and shape to build form. Organic architecture offers a design approach arising from natural principles, bringing us back to local history, tradition, and cultural roots to give us built forms which are in harmony with nature (Mahmoudinejad, 2010). 3.4 Towards Sustainable Development

Sustainable development is development that meets the needs of the present without compromising the ability of future generations to meet their own needs (World Commission on Environment and Development (WCED), 1987).

The concept of sustainable development does imply limits - not absolute limits

but limitations imposed by the present state of technology and social organization on environmental resources and by the ability of the biosphere to absorb the effects of human activities. But technology and social organization can be both managed and improved to make way for a new era of economic growth (World Commission on Environment and Development (WCED), 1987).

Figure 22: Integrated Design Approaches and Concepts of Sustainability Source: (The Researcher adapted from (Jenkin & Zari, 2009))


3.4.1 Differences between the Conventional Design and the Integrated Approaches of Design (Bio-Design)

3.4.1.1 Conventional design approach. Architects put the idea of the building, then it would be transformed into three dimensional building after that they give it to the mechanical engineers, structural engineers, etc. All of them are working separately far from the others (Tom, 2010).

3.4.1.2 Integrative design approaches (Bio-design).

Figure 24: Integrated design process and how the team works

Source : (High Performance by Integrative Design, 2010- video)

Figure 23: Conventional Design Process and How the Team Works

Source: (High Performance by Integrative Design, 2010- video)


Integrative design is could be summarized in four words and all start with the letter (E): Everyone Engaging Everything Early (Tom, 2010).

It comes down to an isolating rhythm of research and analysis by individuals on the team and then they come together for all hands team workshop to compare and look for interactions from that analysis (Tom, 2010).

Go off again to more research and analysis and go back again to workshop. They always look to keys into relationships between systems and systems components (Tom, 2010).

One of those approaches to the integrative design is a bio inspired design.

This new approach is often a response to the growing urgency to build and manufacture more sustainably in light of the climate crisis. This, in turn, leads to unprecedented collaborations between designers and life scientists, such as biologists who increasingly understand how organisms function to the molecular level. That collaboration offers thrilling new possibilities for design, art, and architecture. The recent proliferation of such cross disciplinary activity is occurring in schools, labs and even in garage work benches around the world (Myers W. , 2012).

3.5 Bio Design

“The biggest innovations of the twenty-first century will be the intersection of biology and technology. A new era is beginning.” (Isaacson, 2011)

Bio Design featuring fabric grown from food waste, self-healing concrete, leaves

that glow in the dark and DNA that stores data which explores a future closer than we think (Isaacson, 2011).

Bio-Design is the integration of design with biological systems, often to achieve better ecological performance. In contrast to design that mimics nature or draws on biology

Figure 25: Bio-Design Approach Source: (Myers W. , 2012)


for inspiration, Bio-Design incorporates living organisms into design as building blocks, material sources, energy generators, digital storage systems and air purifiers, just to name a few possibilities. Bio-Design is both opportunistic and logical in recognizing the tremendous power and potential utility of organisms and their natural interaction with larger and ever-changing ecosystems around them. Bio-Design can also be a means of communication and discovery, a way to provoke debate and explore the potential opportunities and dangers of manipulating life, particularly through synthetic biology, for human purposes (Myers W. , 2012).

Bio design is an emerging and often radical approach to design that draws on

biological tenets and even incorporates the use of living materials into structures, objects, and tools. It goes further than other biology-inspired approaches to design and fabrication (Myers W. , 2012).

3.5.1 Differences between Bio-Design and Bio-Mimicry. Bio-design goes further than other biology-inspired approaches to design and fabrication. Unlike bio-mimicry, cradle to cradle, and the popular but frustratingly vague ‘green design,’ bio-design refers specifically to the incorporation of living organisms as essential components, enhancing the function of the finished work. It goes beyond mimicry to integration, dissolving boundaries and synthesizing new hybrid typologies. Bio-design also aims to replace industrial or mechanical systems with biological processes (Myers W. , 2012).

3.5.1.1 Beyond bio-mimicry. Designers face an unprecedented urgency to alter

their methods and reprioritize their goals to address the accelerating degradation of the environment. This new pressure which is intellectual and ethical is regulatory demanding recognition of the fragility of nature and feelings of responsibility to preserve it for future generations. Under such shifting and intensifying constraints, designers are beginning to go beyond emulation to harness processes observed in the living world, where systems achieve perfect economies of energy and materials. Within this pursuit, working to achieve enhanced ecological performance through integration with natural systems, designers are turning to biologists for their expertise and guidance (Myers W. , 2012).

This contrasts markedly with the design approach that characterized the 20th century: the mechanization of functions in order to overpower, isolate, and control forces of nature, usually by utilizing advances in chemistry and physics (Myers W., 2012).

The integration of life into design is not a magic bullet to solve these pressing

issues. Nor will it be free from harmful missteps, deliberate misuses, or controversy. Dystopian visions of the future awash in bio-design gone awry are credible possibilities (Myers W. , 2012).

Beyond growing structures with trees or integrating objects with algae

bioreactors, bio-design includes the use of synthetic biology and thereby invites the danger of disrupting natural ecosystems. These technologies will be wielded by people who are the same biased and frail creatures who designed the world into a desperate mess in the first place. But the potential benefits, and the need to reform current practices toward an approach more in tune with biological systems, far outweigh these risks. Ultimately, design’s embrace


of nature—even coupled with the inevitable hubris that we can redesign and outdo it—is long overdue and the most promising way forward (Myers W. , 2012)

The focus of cross-disciplinary collaborations and their outcomes will, as

always, depend on societal priorities and an array of market signals. Today there is a notable absence of the kind of regulation or system of incentives and disincentives that might lead to the eventual design and creation of environmentally remedial or zero-carbon objects and structures. The use of taxes and subsidies to spark such changes, for example, is still in its infancy. While Germany and Norway have made early and effective steps with policies that prioritize ecologically effective design, most of the industrialized world lags behind, especially the United States, where even the legitimacy of the federal agency to protect the environment is vulgarly challenged in political discourse (Myers W. , 2012).

3.5.2 Divisions. Bio design is Cross-Pollination of

Nature Science Creativity

3.5.2.1 Nature

''The Stone Age did not end because humans ran out of stones. It ended because it was time for a re-think about how we live.''

(McDonough, 2002). 3.5.2.1.1 History of nature in design. Although architecture has embodied a

variety of different designs and styles throughout the ages, the most successful buildings and urban environments have an essential commonality with living forms, i.e. material properties and an assembled nature. It is important, however, to distinguish between superficial resemblance, which can lead to dysfunctional and inhuman buildings, and an approach based upon a genuine understanding of life processes (Salingaros & Masden, 2006).

The desire to follow nature, to adhere to its underlying forms in the pursuit of

harmony, can be traced back to antiquity, to the writings of Vitruvius, as well as to Goethe’s work on morphology and the Romantic motion that certain truths were observable in nature and unknowable to reason. The close examination and formal mimicry of nature by designers reached a height in the late 19th century, in the Art Nouveau style in France and in its iterations across Europe, coinciding with the work of naturalists and pioneers of biology, like Ernst Haeckel, who meticulously described, named, and illustrated thousands of new species. Shortly thereafter in On Growth and Form (1917), D’Arcy Thompson described numerous links among biological form, physics, and mechanics, and highlighted how optimization was frequently achieved in nature. This also coincided with the First World

Figure 26: Bio-Design System

Source: (Myers W. , 2014)


War, and the rapid rise of mechanized industry as a dominant feature of economic, aesthetic, and political life in Europe and the United States (Myers W. , 2012).

Interest in nature as a model or tool for design remained a consistent, if minor,

current in architecture of the early 20th century. This was particularly so in the work of figures such as Frank Lloyd Wright, Alvar Aalto, and even Mies van der Rohe, for their focus on integration of indoor and outdoor spaces, use of natural materials, expression of structure, and consideration of architecture as a component of a larger whole, at least its immediate built surroundings. The idea of emulating nature on a larger scale emerged decades later in post-war Japan, articulated by the built and theoretical mega-structures of the Metabolism movement that embraced impermanence, citing the fluctuations of nature as a logical guiding principle for buildings and cities, which themselves undergo massive transformations that can be considered in terms of cycles, including destruction and rebirth (Myers W. , 2012).

Historically, building design evolved through the natural occurrences and processes of the earth and the structural principles of the physical world. Imbued with a deep understanding of human needs and activities, traditional methods of design and construction revealed an honest (real) expression of the built environment. As human beings came to master their natural environment, they began to extend their designs beyond the physical limits imposed by form and materials. Seeking to advance their architectonic expressions, master-builders raised their great cathedrals from the earth, reaching higher and higher (Salingaros & Masden, 2006).

3.5.2.1.2 How designers dealing with nature. For centuries, artists and designers have looked to nature for inspiration and for materials, but only recently have they become able to incorporate living organisms or tissues into their work. This startling development at the intersection of biology and design has created new aesthetic possibilities and helped to address a growing urgency to build and manufacture ecologically. Bio Design is considered to be a bio-integrated approach to sustainability which presents new innovations enabled by biotechnology (Myers W. , 2012).

Designers initiate interactions between people and nature, mediating a

historically troubled relationship and creating opportunities to connect in new ways for mutual benefit. Bio-design is an expression of this integration, of harnessing or altering nature for human purposes, foretelling beauties and new functions for design yet also warning of dangers (Myers W. , 2014).

3.5.2.1.3 Nature in bio-design. Designers initiate interactions between people and nature, mediating a historically troubled relationship and creating opportunities to connect in new ways for mutual benefit. Bio-design is an expression of this integration, of harnessing or altering nature for human purposes, foretelling beauties and new functions for design yet also warning of dangers (Myers W. , 2014).

This approach to working in partnership with biology contrasts with modern

conventions of subduing and exploiting the environment yet it also echoes traditional techniques such as fermentation that are as ancient as civilization (Myers W. , 2014).


3.5.2.1.4 From the natural to the unnatural. Unable to transcend human existence, yet still innately compelled by the need to overcome the limitations of the materiality of building, the study of architecture began to develop independently of its natural environment. Formalized within the condition of academic studies, architecture soon became the intellectualized property of the University. This set into motion a process that would ultimately render architecture as an artificial and abstract expression of man’s disconnected philosophical and ideological ponderings (Salingaros & Masden, 2006).

In an effort to better understand how architecture is fundamentally grounded in

the natural world, it is needed to delve further into biology. Curiously enough, many of the twentieth century’s pioneering architects have been strongly influenced by the same properties of living structure. Nevertheless, they only had a cursory understanding of the scientific basis of this body of knowledge. As a result, the built applications did not fully realize the intention. To make things worse, thoughtless imitation of such innovative prototypes reduced these ideas to superficial expressions, which ultimately gave way to one or more fashionable styles (Salingaros & Masden, 2006).

3.5.2.1.5 Properties of living structure. Living structure is known to satisfy

several natural properties such as: organized-complexity (information storage); metabolism (energy use); replication (self-reproduction); adaptation (the organism changes itself to better profit from its environment); intervention (the organism changes its environment); situatedness (embedded in the world through sensors); and connectivity (information processing). In biological entities, all processes usually occur together, but theoretically, these are separate concepts (Salingaros & Masden, 2006).

3.5.2.1.5.1 Organized-complexity. Biological and architectural order is being associated with the organization of complexity, which represents the compression of information. An ordered structure has to be complex, yet it is also ordered because it has a large number of correlations that lead to an overall coherence (Alexander, 2005). In architectural examples, correlations arise as visual symmetries and connections, which are easily perceived (Salingaros & Masden, 2006). Life, whether biological, artificial, or architectural, results from the physical concentration of information. A noncomplex structure, on the other hand, requires little mathematical information to create, leading to simplistic structures without any internal differentiations. The world of rectangular building blocks that characterizes industrial architecture and urbanism is mathematically empty. Many architects perceive a superficial “ordering” in this empty world because of alignment and lack of distracting substructure. Seeking uniformity in this way, however, can be seen as a misreading of the actualities of order (Salingaros & Masden, 2006).

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Organized -

Complexity

Figure 27: Properties of Living Structure Source: (The Researcher based on (Salingaros & Masden, 2006), 2015)


One particular insight of Stephen Wolfram is illuminating, because it surprisingly links uniformity with randomness. Wolfram points out that, uniformity of structure is not simple, but is instead the result of intentionally directed processes:

“But in nature uniformity often seems to be associated with quite complex microscopic behavior. Most often what happens is that on a small scale a system exhibits randomness, but on a larger scale this randomness averages out to leave apparent uniformity ...” (Wolfram, 2001) Here there is a perceptive statement of how uniformity arises from randomness

(i.e., disorganization). The implications for design are significant, since uniformity is thereby linked not to simplicity or order, but to disorganization (Salingaros & Masden, 2006).

3.5.2.1.5.2 Metabolism. Metabolism is a process by which existing sources of order are absorbed, and disorder is shed, so that the organism maintains its structural organization. In the case of a developing organism, such as an embryo or young animal, the entity metabolizes at the same time as it increases its organized-complexity until it reaches some optimal stable plateau. Towards the end of the organism’s natural lifespan, metabolism fails to maintain its organized-complexity at the optimal plateau for different reasons, which signals the onset of aging. Metabolism maintains the single individual, whereas replication maintains the design (i.e., template of structural information) after the individual dies (Salingaros & Masden, 2006).

The act of weathering and repair, therefore, can make a building more alive. This might shed some light on Japanese building tradition, in which some holy shrines are entirely rebuilt in the exact manner every few decades. There develops a psychological bonding between human beings and a structure that shows fractal patterns with weathering (but not if it becomes ugly or falls apart). In this analogy, minimalist, non-weathering structures do not metabolize. We are thus questioning the drive towards sleek building surfaces and geometries that oppose natural processes, and suggest that older techniques that accommodated the inevitable weathering are in fact more adaptive (Salingaros & Masden, 2006).

3.5.2.1.5.3 Replication. Replication is often considered as the main characteristic of living structure. Organisms reproduce by making copies of them. Nevertheless, it is possible to have a replicating structure that does not metabolize, as for example a virus (Salingaros, 2004). It is also possible to have an entity that metabolizes but cannot replicate; there are examples in animals such as mules, those exceptional typologies cannot propagate directly (Salingaros & Masden, 2006).

The simplest non-metabolizing templates (viruses) replicate more readily than animals with a higher complexity, because the latter’s investment in metabolic and connective systems raises their organized-complexity (Salingaros, 2004). Among

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Metabolism

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Replication


metabolizing organisms, again those with a lower degree of organized-complexity (e.g., bacteria) replicate much more readily than higher animals, and are thus more abundant (Salingaros & Masden, 2006).

3.5.2.1.5.4 Adaptation. There are several different types

of adaptation: an organism adapts to its environment by responding on the short term, and also the genotype (i.e., its DNA) adapts in the long term by evolving so as to better profit from existing or changing environmental situations. Short-term adaptation depends on connectivity to the environment being situated. Long-term adaptation follows a Darwinian selection process that culls portions of a population that are marginally worse adapted. Subsequently, survivors breed to define a new population having more of the positive adaptive trait (Salingaros & Masden, 2006).

The reason that a non-adaptive architecture was able to develop is that the selection process among buildings and architectural styles is not as direct as selection among organisms (Salingaros, 2007). Selection in architecture is driven by forces external to the natural process of adaptation, i.e. fashion, opinion, and politics (Salingaros & Masden, 2006).

3.5.2.1.5.5 Intervention. Another way that organisms

can act (when they are capable of doing so) is to change their environment to the organism’s advantage. This is in some ways the opposite of adaptation. Nevertheless, the interventive practices that have survived evolutionary (natural) selection always appear as combined adaptive/interventive applications. Animals build nests; beavers build dams; a squid ejects ink to help it escape from a predator; certain plants inject chemicals around them that prevent competing plants from growing; etc. Humans are champions at this: we applied our intelligence for clothing, shelter, hunting, and agriculture, which give us an unbeatable advantage over all other animals (Salingaros & Masden, 2006).

Traditional architecture and urbanism concisely

represent both adaptation and intervention. However, since about the middle of the twentieth century human constructions have become primarily intervention, with little or no attention paid to adaptation (Salingaros & Masden, 2006).

3.5.2.1.5.6 Situatedness. A living organism is naturally

embedded in the world, interacting directly with it via direct sensory mechanisms. External feedback from internal sensors dictates the organism’s behavior: recognition and pursuit of a food source; recognition and reaction to an environmental threat; fight or flight when faced with an aggressor; etc. An organism is situated in its environment, and is constantly sensing the state of the environment (Brooks, 2002).

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Adaptation

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Intervention

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Situatedness


Situatedness depends upon the existence of sensory mechanisms that provide information about the world, and those, in turn, require a connective framework. The opposite of being situated is to exhibit behavior that is decided on the basis of abstract descriptions. We are not aware of any lower organisms that can do this; it logically appears to be a capability of animals with sufficient neural development for memory storage. An organism cannot form and act on an internal representation of the world unless it has sufficient capacity to store it as memory (Salingaros & Masden, 2006).

3.5.2.1.5.7 Connectivity. In biology, correlations arise as connective mechanisms. These include structural ones, such as plant stems, animal bones, arteries, and ligaments; and informational ones such as in hormonal fields, nerves, eyes, and photosensitive surfaces on leaves. All of these are prime examples of organized-complexity, and each instance employs a complex physical network to perform a connective task (Salingaros & Masden, 2006).

An embryo develops by repeatedly splitting cells, so that its growth is obviously bottom-up, guided by genetic instructions in the DNA. Nevertheless, Alexander argues that embryonic development is impossible without a global control that keeps the growth from getting out of hand (Alexander, 2005). Whether this is due to a process of iteration in which each component helps to support and guide the development of other components, or to hormonal fields, what is important is that a global communication occurs. Each component (cell) of the embryo communicates chemically with the entire embryo existing at that time, so that each cell checks its position and future growth. In this way, embryonic cells develop either into muscle tissue or brain tissue, depending on their relative position at a particular time in the process (Salingaros & Masden, 2006).

A living system is one that acquires and actively uses information (Dyson, 2001).

Information transfer takes many different forms in biology. Hormonal and nervous systems in animals are essential for interacting with the external world, and also for communicating internally within the organism. Stored genetic information encodes templates that permit the replication of individual cells, which replace worn-out cells in the body on a regular basis. For example, all except brain cells are routinely replaced in a mammal. Inherited information (across generations) is also stored in the brain, enabling all the instinctive behavior routines that permit animals to function. As the evolutionary ladder is moved up, information and its processing plays an increasingly central role in life. The higher mammals are capable of learning, which is made possible by information storage mechanisms (Salingaros & Masden, 2006).

3.5.2.2 Science. 3.5.2.2.1 Science and biology. Over the past several decades, several industrial

revolutions took place including those in genomics, nanotechnology, and synthetic biology. In the 1990s, scientists sequenced the human genome in hope of providing medical cures through personalized medicine and DNA vaccines. However, genomic cures have yet to materialize, mandating more focus on translational genomics. An infrastructure to support nanotechnology is in place, and researchers are in various stages of product development (Mayes, 2010).

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Connectivity


(Biology is Technology) is the most comprehensive overview to date of the state

of the field of synthetic biology. Although Rob Carlson, a bioengineer and principal with Biodesic, has formal academic training in physics, his fellowship with the Molecular Sciences Institute and expertise on biotechnology make him uniquely qualified to analyze the field’s potential and the challenges to its future development (Mayes, 2010).

A crucial step to ensuring the success of the field is the development of enabling

technologies. This includes fast, powerful, and cost efficient computers. In addition, DNA sequencers and DNA synthesizers are necessary to identify genes and make synthetic DNA sequences (Mayes, 2010).

3.5.2.2.2 Importance of Science in bio- design and the integration between

nature and science. “Science... never solves a problem without creating ten more.”

(Shaw, 1950) Biology stands out among the sciences for its frequent, accelerating and

fundamental progress in recent years. The first industrially useful genetically modified organism was a bacterium made some thirty years ago to be a reliable and inexpensive factory for insulin. Only nine years ago the human genome was mapped at significant expense and effort over many years, and now a $1,000 genome sequencing technique appears to be around the corner, certainly within two years. And just in the fall of 2012 it was discovered that among the 98% of human DNA long thought to be “junk” left by our evolutionary legacy are in fact numerous, essential switches that control gene behavior. Meanwhile, the cost of genetic synthesis is falling rapidly, roughly following the phenomenon described by Moore’s Law, which holds that the number of transistors on integrated circuits doubles every two years, helping computers become continually cheaper and more powerful (Myers W. , 2012).

3.5.2.3 Creativity 3.5.2.3.1 What is creativity? ''Creativity is a distinguishing characteristic of human excellence in every area of behavior.'' (Torrance, 1970) Creativity is a natural part of being human. It is not reserved for those people

with some sort of special gift. This suggests that creativity exists in all people (at different levels and various styles). The challenge arises from learning how to understand and use the creativity someone has. This belief is fundamental for those who are interested in identifying what creativity is and understanding how it can be developed (Isakson, Dorval, & Treffinger, 2011).

Creativity was defined as novel associations that are useful (Gryskiewicz, 1987). This definition came as a result of interviews and analysis of stories of creative performance with approximately 400 managers in organizations. What it is liked about this definition is that it is simple and has a built-in tension between something being novel and useful. The novelty part of the definition appears to fit well with most people's perceptions of creativity. However, the usefulness part of the definition often stimulates questions in people's minds


about whether something needs to be useful in order to be creative. It also raises questions in general about who determines if something is novel or useful, and therefore, who determines if creativity is present or not (Isakson, Dorval, & Treffinger, 2011).

Ruth Noller, Distinguished Service Professor Emeritus of Creative Studies at

Buffalo State College, developed a symbolic equation for creativity. She suggested that creativity is a function of an interpersonal attitude toward the beneficial and positive use of creativity in combination with three factors: knowledge, imagination, and evaluation. Children are often viewed as naturally strong in imagination. They often need help in acquiring knowledge and expertise, as well as in understanding appropriate criteria for evaluating ideas or behavior. In comparison, practicing professionals often are seen as having a great deal of knowledge and evaluative strength but as needing help with imagination (Isakson, Dorval, & Treffinger, 2011).

It might be learned a number of lessons from Noller's equation. One is that

creativity is a dynamic concept. It changes through our experience. Also, creativity always occurs in some context or domain of knowledge. But, while expertise is important and necessary, it is not sufficient for determining creativity. Finally, creativity involves a dynamic balance between imagination and evaluation (Isakson, Dorval, & Treffinger, 2011).

3.5.2.3.2 What is a creative approach? An approach is a way of making change

happen. There are at least two different kinds of approaches to making change happen; creative and non-creative. A creative approach implies that there is attempt to advance toward an outcome that is new, unstructured, and open ended. These situations often involve an ill-structured problem and unknown solutions. Although it is needed to use knowledge and skills for evaluation, a creative approach requires to be engaged with imagination, as well as intelligence, during approach because no ready-made answer exists. It also requires taking a more comprehensive view and using the entire system of people, method, content, and context in the approach (Isakson, Dorval, & Treffinger, 2011).

Using a creative approach also implies that there is a courageous attitude; one that includes being open to new experiences, embracing ambiguity, and venturing into new and unfamiliar territory. This attitude is often necessary because creative approaches are about helping to move from a place with which is familiar to one that is different and potentially unknown, and the results of these efforts are potentially uncertain (Isakson, Dorval, & Treffinger, 2011).

3.5.2.3.3 Linking creativity and problem solving. Researchers have explored links between creativity and problem solving before and have come up with a variety of answers (Isaksen, 1995). For example, it was suggested that problem solving and creative

Figure 28: Noller's Symbolic Formula for Understanding Creativity Source: (Isakson, Dorval, & Treffinger, 2011)


thinking were closely related. Creative thinking produced new outcomes, and problem solving involved producing novel responses and outcomes to new situations. Problem solving often has creative aspects, but creativity is not always problem solving (Guilford, 1977).

"Creative activity appears ... simply to be a special class of problem solving activity characterized by novelty, unconventionality, persistence, and difficulty in problem formulation" (Newell, Shaw, & Simon, 1962)

Rather than keeping creativity separate from problem solving, that approach has

been to deliberately link the two. This approach is designed to apply both imagination and intelligence, to generate as well as focus, to use logic and memory as well as emotion and synthesis. The opportunity created by linking these two concepts is that there is a very diverse collection of strategies, tools, and approaches, enabling to handle a wide variety of challenges and opportunities (Isakson, Dorval, & Treffinger, 2011).

3.5.2.3.4 Creative problem solving. Creative problem solving was defined by

offering a definition of each of the three main words: creative, problem, and solving (Noller, 1979).

CPS equated with creative decision making, suggesting that "First speculate on what 'might be' ..., sense and anticipate all conceivable consequences or repercussions ... and choose and develop the best alternative in full awareness" (Parnes, Noller, & Biondi, 1977) CPS is a broadly applicable framework for organizing specific tools to help to

design and develop new and useful outcomes. The structure of CPS provides an organizing system. Using the system involves applying productive thinking tools to understanding problems and opportunities; generating many, varied, and unusual ideas; and evaluating, developing, and implementing potential solutions. The system includes the framework of components, stages, phases, and tools, as well as considering the involved people, the situation or context, and the nature of the content or the desired outcomes. CPS enables individuals and groups to recognize and act on opportunities, respond to challenges, and overcome concerns (Isakson, Dorval, & Treffinger, 2011).

3.5.2.3.4.1 Main purposes or CPS process components. Three important steps help to link the process effectively to the need (Isakson, Dorval, & Treffinger, 2011).

First, know what the need is and the best place to begin to address it. The need

may come from working on Appraising Tasks (particularly the Content element) or it may be evident from general understanding of the task (Isakson, Dorval, & Treffinger, 2011).

Second, know the specific purposes fulfilled by each CPS component and stage

(Isakson, Dorval, & Treffinger, 2011). And third, link the task need to the most appropriate component or stage based

on the purpose it fulfills (Isakson, Dorval, & Treffinger, 2011).


It is easiest to begin developing a link between CPS and the needs by considering the three process components. Each component and stage has a specific and unique purpose. At the component level, CPS can help to gain clarity about the challenge, generate ideas, or put ideas into action (using Understanding the Challenge, Generating Ideas, and Preparing for Action, respectively) (Isakson, Dorval, & Treffinger, 2011).

3.5.2.3.4.2 CPS process stages. These represent the three core purposes of the CPS process components. When what component to use is known, it will also be in a better position to identify what stage or stages to use. Each stage also has its own purpose that is linked to the component purpose. For example, the Constructing Opportunities stage helps to gain clarity about the future. The Framing Problems stage helps to gain clarity about the specific problems to address. The Developing Solutions stage helps to transform ideas into promising solutions. Finally, the Building Acceptance stage helps to transform ideas into promising action (Isakson, Dorval, & Treffinger, 2011).

3.5.3 Architecture and Biological Processes. Using science and technology constructively and humanely it has been begun to sense the intimate connection between living structure and architecture (Alexander, 2005). It is believed there is a direct analogy that can be drawn between metabolism in biological entities, and the process of maintaining complex structure (form) in non-biological ones. Buildings as non-natural artificial entities require varying degrees of repair by human beings after being built (Salingaros & Masden, 2006).

Figure 29: The Core Purposes or CPS Process Components

Source: (The researcher based on (Isakson, Dorval, & Treffinger, 2011),

2015)

Figure 30: The Core Purposes of CPS Process Components and Stages

Source: (The Researcher based on (Isakson, Dorval, & Treffinger, 2011), 2015)


Considering human dominance of the world, and the physiological dependence on the physical structures built around, it could be assumed that there is an inherent necessity for buildings to replicate (even though they are inanimate entities). Often the replication of form is seen in the built environment considered as a predicate of place, i.e. through indigenous localized forms. The replicating form is something that works within the limits of the material systems available in a certain region, and responds to local climatic conditions. So within a specific region very similar forms replicate and adapt to the programmatic differences and varying site conditions (Salingaros & Masden, 2006).

What are the forces that affect the survival of specific architectural templates?

For example, building glass-walled high-rise buildings in both hot and cold climates is disastrous from an energy point of view. And yet, large rectangular buildings were universally adopted as an early twentieth-century design typology. This and other industrial examples are nonfunctional, but are copied from templates that have no relevance to human needs. There is a contradiction here with biological replication (Salingaros & Masden, 2006).

Non-adaptive forces in the built environment (dominant in a culture of

architectural media-hegemony) give form to replicating structures around the world. Architectural and urban structures that simply replicate instead of growing out of very explicit local needs follow the architect’s internal visual template that was developed generically, and not adaptively. This seems to be the crucial disconnection. In deepening the biological analogy, Freeman Dyson identifies metabolism with the emergence of proteins (analogous to physical structure), and replication with the emergence of nucleic acids (analogous to a reproducible design typology). It is hoped to identify connectivity with the emergence of complex sensory organs and communicative pathways in biological structure. Thus, connectivity is a much higher system function than either metabolism or replication, and makes possible adaptation, intervention, and situatedness in organisms. The architectural analogues of these properties are essential for a human built environment (Salingaros & Masden, 2006).

Situatedness is necessary for several of the other properties to occur. An architect

who is not situated can respond neither to context, environment, nor the physicality of form. The architecture that comes out of this precondition turns out to lack connectivity and thus the ability to adapt (Salingaros & Masden, 2006).

3.5.4 Outcomes of Bio-Design. One important outcome of this new approach to

design has been the development of critical and narrative objects that blur the border between art and design and which envision the effects of new technologies and scientific research on human behavior and culture. But while Bio-Design does have enormous implications for the future of human interaction, it most immediately demonstrates its potential when the architect or designer taps into the expanding ocean of knowledge created by biologists and working in collaboration with them, trying to solve some of the world’s most pressing design problems (Myers W. , 2012).


3.6 Cases Studies

3.6.1 Example -1- Bridges of Meghalaya

3.6.1.1 Description. These bridges are found in northeastern Indian state of

Meghalaya, one of the wettest places on the planet, with up to 1,200 cm (470 in.) of rain annually. In the Khasi and Jaintia hills, this rain creates numerous swift-flowing rivers that are dangerous to cross and require bridges to afford basic mobility to the local people. In a predominately agrarian economy made up of tribes that have lived in the area for centuries, a natural and effective solution has been developed: bridges grown from the roots of rubber trees (Myers W. , 2012).

3.6.1.1 Origination. Within these communities made up of tribes that have lived

in the area for centuries, a natural and effective solution has been developed: bridges grown from the roots of rubber trees, shaped by people and strengthened over time. Without the need for specialized training and equipment that other types of bioengineering require, The Root Bridges of Meghalaya are coaxed from the natural growth of Ficus elastica—a rubber tree within the banyan group of figs. These trees thrive on the slopes of hills and have strong rooting systems (Myers W. , 2012).

Name Root Bridges of Meghalaya

Designers Numerous designers Place Khasi tribe, India Year 1500 – Ongoing

Concept Shaping and guiding biological processes is nothing new. These natural structures continue to grow and can last for hundreds of years

Figure 31: Bridges of Meghalaya Source: (Myers W. , 2014)


Although precise dating is difficult, it is widely accepted that many are more than 500 years old (Myers W. , 2012).

Sadly however, many of the region’s rivers have in recent years been

poisoned by the runoff from nearby illegal mines. If the disruption to local ecosystems continues unabated, these ingenious works of design that are engineered to live indefinitely may shrivel and die (Myers W. , 2012).

Figure 32: As with All Living Structures, The Bridges Rely on A Healthy Environment for Their Maintenance, Abundant clean air, water, and soil are essential. Source: (Myers W. , 2014)

Figure 34: Over Time, Bridges are Shaped from The Roots of Several Trees. These Natural Structures are Capable of Lasting for Hundreds of Years. Source: (Myers W. , 2012)

Figure 33: The Bridges are Ever Changing in Form and They are Strengthened by The Addition of Branch and Grass Clippings, Which Nourish The Roots. Source: (Myers W. , 2012)


3.6.2 Example -2- House of the Future

3.6.2.1 Description. The art of designing constructions that are made using

living trees has been called ‘Baubotanik’ or ‘Building Botany’ by a group of architects at the University Of Stuttgart, Germany. These demonstration projects explore engineering with living plants to integrate architecture into its immediate environment. They also blend research and application by uniting architects, engineers and natural scientists in an endeavor to create a structure and test new possibilities (Myers W. , 2014).

An important feature of these projects is the utilization of plants as load-bearing systems, taking advantage of what the architects call the “constructive intelligence” of trees: like human muscles, tree branches naturally strengthen in response to stress or increased loads. At the same time, this practice exposes researchers to the bio-dynamics and uncontrollability of natural growth. This lack of control inspires a form of architecture that is characterized by accidental processes, hope and risk. The architects also take a critical

Name Baubotanik Tower, Living Footbridge, House of the Future

Designers

Ferdinand Ludwig (Research Group Baubotanik, IGMA, University of Stuttgart), Neue Kunst am Ried, Cornelius Hackenbracht, Oliver Storz, Daniel Schoenle

Place Germany Date 2009

Concept A building method that makes use of the constructive intelligence of

trees Type of Material

Silver willow (Salix Alba), common osier (Salix viminalis) steel tubes scaffold

Figure 35: House of the Future Source: (Myers W. , 2014)


stance by embracing an “aesthetic of uncertainty” in the use of living materials (Myers W. , 2014).

3.6.2.2 Construction phase. The whole construction is supported by a

temporary steel tube scaffold which is embedded in the ground on a screw base – a structure which always can be removed again. The plant containers are constantly kept wet to ensure the necessary water for the plants. On that condition, all plants will completely intergrow with each other. Thereby it shall be examined how long it takes for the structure to get water and nutrients out of the ground independently. Due to its experimental character the structure is not designed as a publicly walkable facility. The zinc-coated steel-grating levels are basically used for maintenance and care. The load capacity of the vegetable supporting structure is at present difficult to prognosticate and shall be proved by weight tests (Myers W. , 2014).

3.6.2.3 Development. Traces are made out of two plants arranged in form of a

rhombus to create the plant structure. At their crossing points they are connected to the horizontal arranged levels. In process of time, the plants merge together and join to a vigorous connection with the levels. Thereby they develop a timber-framed supporting structure. As soon as the living structure is stable enough to support the ingrown levels and

Figure 39: Pre-Cultivated Plants in The Greenhouse Source: (Myers W. , 2014)

Figure 38: Screw Bases of The Temporary Scaffold Source: (Myers W. , 2014)

Figure 36: Assembly with The Crawler Crane Source: (Myers W. , 2014)

Figure 37: Connecting of Plants with Stainless SteelScrews Source: (Myers W. , 2014)


take over the loading capacity, the scaffold will be removed. Depending on many factors, this process can not been predicted. It shall be studied at this structure. Therefore a period of about 5 up to 10 years is expected. Then the plants will take up vertical forces and solely through the combination with the horizontal arranged technical modules a stiffening structure originates (Myers W. , 2014).

Figure 44: Winter 2010 Source: (Myers W. , 2014)

Figure 45: Spring 2010 Source: (Myers W. , 2014)

Figure 43: Early Summer 2010 Source: (Myers W. , 2014)

Figure 48: Last Summer 2010 Source: (Myers W. , 2014)

Figure 47: Autumn 2010 Source: (Myers W. , 2014)

Figure 46: Winter 2011 Source: (Myers W. , 2014)

Figure 42: Summer 2011 Source: (Myers W. , 2014)

Figure 41: Autumn 2011 Source: (Myers W. , 2014)

Figure 40: Spring 2011 Source: (Myers W. , 2014)


3.6.3 Example -3- Fab Tree Hab

3.6.3.1 Description. This Concept suggests an alternative to the sterile, stand-alone homes that are at odds with their immediate environment. It offers a method for growing residential accommodation from native trees that remain living and integrated with the ecosystem. Here, a growing structure is grafted into shape with prefabricated computer numerical controlled reusable scaffolds. Depending on the weather conditions and location, it should take approximately seven years to grow (Myers W. , 2012).

The creation of Fab Tree Hab relies heavily on ‘pleaching’, the ancient process

of tree shaping in which tree branches are woven together so that as they continue to grow they form archways, lattices, or screens. The trunks of inosculating (self-grafting) trees, such as elm, oak, and dogwood, form the load-bearing elements, while the branches provide a

Name Fab Tree Hab, Terre form One

Designers Mitchell Joachim, Lara Greden, Javier Arbona Place Massachusetts Institute of Technology, Cambridge, United States Date 2005 – Ongoing

Concept Computer numerical controlled produced scaffolds, a variety of native trees

Figure 49: By Directing Their Growth, Trees and Woody Plants can be Integrated into Built Structures. This Slow Construction Method Creates Living Architecture Integrated with—and Enhancing—The Environment



continuous crisscross frame for the walls and roof. Interlaced throughout the exterior is a dense protective layer of vines, which is interspersed with soil pockets that support growing plants (Myers W. , 2012).

Figure 51: Energy and Nnutrient Flows are Connected with The Natural Cycles of The Surrounding Ecosystem, Thereby Harnessing Both Cool Air and Rainwater Source: (Myers W. , 2012)

Figure 50: A variety of Plants Fill in The Gaps in The Façade, Encouraged By The Use of Perforated Scaffolding Through Which Stems and Leaves Can Intertwine Source: (Myers W. , 2012)


3.6.3.2 Construction phase. During the slow process of construction, the trees and plants are allowed to grow over a computer-designed removable plywood frame. Once the living elements are interconnected and stable, the wood is removed and can be reused. Research at the Massachusetts Institute of Technology, where the designers undertook their studies, has explored the potential of woody plants that grow quickly and develop an interwoven root system that is soft enough to ‘train’ over a scaffold but then hardens to be very durable. The inside walls would be made from conventional clay and plaster (Myers W. , 2012).

The interdependency between architecture and the environment, the underpins, the home is incentive to the preserve clean air, water, and soil (Myers W. , 2012).

Figure 52: The process of Composing A House by Depending on Planting Trees Source: (Myers W. , 2012)

Figure 54: The Final Predicted Product Source: (Myers W. , 2012)

Figure 53: Structure Development Process Source: (Myers W. , 2012)


Aliving structure is slowly grafted into shape with the help of prefabricated and reusable scaffolding. Organic processes and time together become the essential construction materials. Depending on the climate, it takes about 5 years of guided tree growth before the house is functional (Myers W. , 2012).

3.6.3.3 Innovation. Technical demonstration and innovation is still required for

some components—principally the bio-plastic windows that can adapt to growth of the house and the management of nutrient flows across the walls to ensure that the interior remains dry and free from insects. The time required for it to be habitable is approximately 5 years—far longer than for a more ‘traditional’ construction, but its health and longevity should be far greater. Above all, the ‘growth’ of such a home should be achievable for a minimal price, requiring little labor or fabricated materials. The realization of these structures will begin as an experiment but thereafter it is envisioned that the concept of renewal will take on a new architectural form—one of interdependency between nature and people (Myers W. , 2012).

3.6.4 Example -4- Dune

Name Three Invincible Cities: Sandra, Crystalia, Arachnia

Designers Ordinary Ltd., Magnus Larsson & Alex Kaiser Place Architectural Association, London, UK / Magnus Larsson Studio,

London, UK

Date 2013

Concept These imaginative urban strategies utilize bacteria, crystal formation and spider silk for structures

Figure 55: How to Stop Desertification Source: (Myers W. , 2014)


3.6.4.1 Description. This architect envisions building structures out of sand in the Sahara and forming a 6,000 km (3728 mile) barrier to protect against the spread of the desert. This speculative, audacious plan would harness the ability of a particular bacterium to perform construction by naturally converting dunes into sandstone (based on work by Jason De Jong’s team at the Soil Interactions Laboratory, University of California, Davis). During the process, the stone would be shaped to collect moisture, protect trees, and shelter thousands of people at relatively little cost (Myers W. , 2012).

The urgency of the

problem that this project attempts to address cannot be overstated. A United Nations study (Adeel, et al., 2007) concludes that ‘Desertification has emerged as an environmental crisis of global proportions, currently affecting an estimated 100 to 200 million people, and threatening the lives and livelihoods of a much larger number.’ The displacement of communities that is often generated by the spread of the desert regularly aggravates political instability in several of the affected countries, such as Sudan, Chad, and Nigeria (Myers W. , 2012).

Figure 56: The Wind and Sand That Result in Expansion of The Desert, Threatening Settlements and Arable Land, are Exploited in Biological Construction Source: (Myers W. , 2012)

Figure 57: Sand Solidified by Bacteria and Shaped by The Wind Eventually Allows Water to Accumulate and Forms A Barrier Against The Spread of The Desert Source: (Myers W. , 2012)


3.6.4.2 Inspiration. Dune was inspired by the ongoing project in the same area

to plant trees and vegetation across a dozen countries in the region, the goal of which is to protect the Sahel Belt—a stretch of dry savanna just south of the desert. Funds for this Great Green Wall are still being raised, but there has been progress in Senegal, where some 500 km (311 miles) of trees have been planted (Myers W. , 2012).

Figure 59: A Dune Cross-Section with Rigid Chambers Where Precious Moisture and Soil Might Be Preserved Source: (Myers W. , 2012)

Figure 58: The Shape of The Structure Here is Shown in A Tafoni Pattern—Characteristic of Rock That Has Been Eroded by Wind or Moisture for Many Years Source: (Myers W. , 2012)


Figure 60: Resisting The Spread of The Desert Becomes Ever More Difficult and Yet Important as The Climate Warms. The Vast Savanna of The Sahel Belt is One of Many Areas That are Currently Under Threat


Figure 61: The Architect‘s Proposal Stemmed from An Examination of Extreme Environments, Such As Desert, Ocean, and Tundra, Where Traditional Approaches to Building are Simply Unfeasible



3.6.4.3 Materials. Bacteria, water, urea, and calcium chloride would be injected into the sand-scape and would— via a process called microbial-induced calcite precipitation—produce calcite, a natural cement, that would cause the sand to solidify within 24 hours. By choosing where to apply the microorganism, the architect would have a degree of control over the process, but the final form would be heavily influenced by the environment. While the principal aim would be to produce a barrier against sand moved by the wind, the structure’s formation would be augmented by wind action. Thus the design elegantly harnesses the energy embodied in the problem to propose its solution (Myers W. , 2012).

3.6.5 Example -5- Filene's Eco Pods

Name Eco-pods: Pre-cycled Modular Bioreactor

Designers H ِ◌weler + Yoon Architecture and Squared Design Lab Place A stalled development in the center of Boston revived, United States

Date 2009

Concept By moveable modules

Figure 62: Microbially Induced Cementation is A Natural Process That Can Be Observed in Swamps and Lakes. It Is Not Harmful to Humans and Will Cease Once Available Nutrients Have Been Depleted


Figure 63: Future Eco Bods Source: (Myers W. , 2014)


3.6.5.1 Description. This vision of adaptable architecture echoes proposals and

structures of the Metabolist architects and theorists in post-war Japan. They conceived of urban growth as cycles in nature, undergoing periods of expansion, decline and rebirth (Myers W. , 2014).

3.6.5.2 Objectives and construction. The objectives of this proposal are to

stimulate the local economy and ecology of downtown Boston through the integration of energy production and architecture, while taking advantage of a stalled construction site known as Filene’s Development (Myers W. , 2014).

Figure 64: Filene's Eco Pods Source: (Myers W. , 2014)

Figure 65: Full Set Drawings for the Module Pod Source: (Myers W. , 2014)


3.6.5.3 Components. Eco Pod (Gen1) is a temporary vertical algae bio reactor and new public Commons, built with custom prefabricated modules. The pods will serve as bio fuel sources and as micro incubators for flexible research and development programs. The ability of these ‘pods’ to interlock and be moved around allows them to fill different types of space. For example, they can be affixed to vacant buildings or lots, and any space between them can be planted with productive gardens (Myers W. , 2014).

As an open and reconfigurable structure, the voids between pods form a network of vertical public parks/botanical gardens housing unique plant species a new Uncommon for the Commons. Micro algae is one of the most promising bio fuel crops of today, yielding over thirty times more energy per acre than any other fuel crop. Unlike other crops, algae can grow vertically and on non arable land, is biodegradable, and may be the only viable method by which we can produce enough automotive fuel to replace the world’s current diesel usage (Myers W. , 2014).

Figure 66: Grown Algae between Modules (Bioreactors) Source: (Myers W. , 2014)

Figure 67: Eco-Pod Process Source: (Myers W. , 2014)


Algae farming use sugar and cellulose to create bio fuels and simultaneously help to reduce Carbon Dioxide emissions, since it replaces CO2 with Oxygen during photosynthesis. While the bio reactor process is currently in an experimental phase, recent advances in single step algae oil extraction and low energy high efficiency LEDs make the algae bio reactor an extremely promising prospect on the renewable energy technology horizon (Myers W. , 2014).

3.6.5.4 Composition growth. The central location of the Eco Pod and the public

and visible nature of the research, allows the public to experience the algae growth and energy production processes. As a productive botanical garden, it also functions as a pilot project, a public information center and catalyst for ecological awareness. An on site robotic armature (powered by the algae bio fuel) is designed to reconfigure the modules to maximize algae growth conditions and to accommodate evolving spatial and programmatic conditions in real time. The reconfigurable modular units allow the structure to transform to meet changing programmatic and economic needs, while the continuous construction on the site will broadcast a subtle semaphore of constructional activity and economic recovery. This is anticipatory architecture, capable of generating a new micro urbanism that is local, agile, and carbon net positive (Myers W. , 2014).

Figure 68: Different Deformations of Modules Source: (Myers W. , 2014)

Figure 69: Robotic Armature (Powered by the Algae Bio Fuel) Source: (Myers W. , 2014)


This proposal envisions the immediate deployment of a “crane ready” modular temporary structure to house experimental and research based programs. Once funding is in place for the original architectural proposal, the modules can be easily disassembled and redistributed to other empty sites, testing new proposals, and developing initiatives with other communities. Designed with flexibility and reconfigure ability in mind, the modularity of the units anticipates future deployments on other sites. An instant architecture, designed with an intention towards its afterlife(s), this is pre cycled architecture. In our ongoing, synergistic scenario, the growth of the algae propels, and is propelled by, technologicallyenabled developments that literally and metaphorically “grow the economy” (Myers W. , 2014).

The architects propose prefabricated modules that can be used as incubators in

which to grow algae for bio-fuel. The ability of these ‘pods’ to interlock and be moved around allows them to fill different types of space. For example, they can be affixed to vacant buildings or lots, and any space between them can be planted with productive gardens (Myers W. , 2014).

3.7 Conclusion

After reviewing this chapter, it could be concluded that design in not what is used to be in schools and in studios, in corporation and in political institutions. Environmental degradation which occurs in the whole world obligated designers to rethink in their ways to design buildings and how their buildings harness the nature, so they should deal with nature as a part of their design process in order to meet the needs of the present but without compromising the ability of the future generations and that is called sustainable development. Towards sustainability, new trends of design appeared. One of these new trends is dealing with nature as a tool of design and depending on biological systems in

Figure 70: Different between New Trend of Buildings and the Ordinary Buildings Source: (Myers W. , 2014)


buildings that trend in design is called Bio- Inspired Design. Bio design could be generated by a complete integration between nature, science and creativity. Nature is the master of all designs and in that trend design of buildings starts by a biological base (biological organism). Science is playing an important role in that trend as by new technology which had been developed by scientists; let them be able to doing changes in the DNA of any biological organisms do. Those changes opened the field to invent new materials by changing the behavior of any other materials and then using these materials in a proper use to make full use of their specialized characteristics. Third, creativity and its important role in dealing with designing building as a way to solve problem so there would be a creative approach to solve any problem with a scientific method. After that integration, there would be the relationship between that integration and biological systems to generate bio-inspired design. Finally, there would be some examples to explain how that integration could be realized and the predicted out comes by depending on a bio- inspired trend in design.


SMORPHOGENESI TOWARDS -4-CHAPTER

''When nature continues as architecture it means that natural forms, or more correctly; their morphology, the metamorphoses caused by natural forces, etc, are incorporated into our architectural idiom, parallel to Euclidean form language, or even as replacement for it.'' (Pietilä, 1966)

Figure 71: Chapter (4) Structure Source : (The Researcher, 2015)


Chapter 4: Towards Morphogenesis 4.1 Introduction

The field of architecture is going through a shift where its basic principles are being challenged by the changes that are happening around us. The abundance of new techniques and technologies in architectural design, as well as in fabrication and construction, force us to rethink our design methods and processes. The global changes that drive us toward an ever-growing need for technology and insulation in our buildings provide us with the opportunity to search for new holistic solutions. But new solutions cannot be made with obsolete tools. It was stated that the direct emulation of the past is fruitless, yet it should be learned from the lessons it provides (Weinstock, 2008).

“Instead of trying to validate conventional architectural thinking in a different realm, our strategy today should be to infiltrate architecture with other media and disciplines to produce a new crossbreed.” (Zellner, 2000). The Information Age, like the Industrial

Age before it, is therefore not only challenging what it is being designed but also how it could be design. The generative and creative potential of digital media is opening up new emergent dimensions in architecture (Kolarevic, 2000).

“Architecture is recasting itself, becoming in part an experimental investigation of topological geometries, partly a computational orchestration of robotic material production and partly a generative, kinematic sculpting of space.” (Zellner, 2000).

New architectural paradigms are forming with the help of the transition to digital

design; new tools help to find new sources of inspiration and solutions. Parametric design software has already established itself and it is now common that designs incorporate computer modeling. But these tools only mimic old design processes and do not themselves any new possibilities or inspiration for design. It is stated that they offer the benefits of computerization but not the over whelming opportunities of computing (Terzidis, 2006).

Digital infrastructures are being inscribed into cities and buildings, new forms

and methods of spatial organizations are being emerged (Mitchell W., 1995). Technological architectures are being replaced by computational architectures of topological, non-Euclidean geometric space, kinetic and dynamic systems, and genetic algorithms (Kolarevic, 2000).

Figure 72: Generate from Algorithm to Structure - Exhibition Structure

Source: (Österlund, 2010)


Procedural, parametric and generative computer-supported techniques in combination with mass customization and automated fabrication enable holistic manipulation in silico and the subsequent production of increasingly complex architectural arrangements (Roudavski, 2009).

4.2 Definitions of Morphogenesis

Morphogenesis is a concept used in a

number of disciplines including biology, geology, crystallography, engineering, urban studies, art and architecture. This variety of usages reflects multiple understandings ranging from strictly formal to poetic. The original usage was in the field of biology and the first recorded instances occur in the second half of the 19thcentury. An earlier, now rare, term was morphogeny, with the foreign-language equivalents being morphogenie (German, 1874) or morphogénie (French, 1862). Geology was the next field to adopt the term in the 20th century (Roudavski, 2009).

Morphogenesis is automating parts of

the design process; computers make it easier to develop designs through versioning and gradual adjustment (Roudavski, 2009).

Natural morphogenesis is a process of

evolutionary development and growth that causes an organism to develop its shape through the interaction of system-intrinsic capacities and external environmental forces (Hensel & Menges, 2008).

Morphogenesis is one of the major

outstanding problems in the biological sciences. It is concerned with the shapes tissues, organs and entire organisms and the positions of the various specialized cell types and the fundamental question of how biological form and structure are generated (İcmeli, 2014).

Morphogenesis encompasses a broad scope of biological processes. It concerns adult as well as embryonic tissues, and includes an understanding of the maintenance, degeneration, and regeneration of tissues and organs as well as their formation. It also addresses the problem of biological form at many levels, from the structure of individual cells, through the formation of multi-cellular arrays and tissues,

Figure 73: Performance Building For the Oulu Music Video Festival; Competition Entry and

3rd Prize for Ideas for Yard and Environmental Constructions Held by Kainuun Etu Oy

Source: (Österlund, 2010)


to the higher order assembly of tissues into organs and whole organisms. While related to the field of developmental biology with its traditional emphasis on the control of gene expression and the acquisition of cell fates, morphogenesis investigates how this regulation of cell fates contributes to the form and structure of the organism and its component parts (İçmeli, 2014). 4.3 Computational Models and Morphogenesis Types

Plant morphogenesis is the formation of shape and structure by Co-ordination of cell shape, growth, and proliferation by mitosis. Computational and mathematical models are used as a tool in biology field because of complex mechanism of morphogenetic growing (Rudge & Haseloff, 2005).

Each cell has own parameters (contains morphogen levels, growth rate etc.) and a boundary which define its limits. All the situations; state or transformation status is determined in these parameters in mathematical formula. Architecture is used these computational models as a generative tool in form-making process (Rudge & Haseloff, 2005).

Morphogenesis can be categorized in four according to their transformation

types which are; Proliferation Coordinated growth Cell lineage Cell position specification

(Rudge & Haseloff, 2005).

4.3.1 Proliferation

Simple cell colonies were generated from initial conditions of a single unit square cell. All cells were grown at the same rate and divided when their volume doubled. Cell growth was isotropic (İçmeli, 2014).

Figure 74: Cell Arrangements in Plant Tissues Source: (Rudge & Haseloff, 2005)


4.3.2 Coordinated Growth. There are several examples of processes in plants in which a zone of proliferating cells is established within a mature or slowly growing region. Growth was polar, and all cells divided on doubling their initial volume (Rudge & Haseloff, 2005).

4.3.3 Cell Lineage and Positional Information. The relative roles of cell lineage or inheritance, and cell-cell signaling mechanisms and their interactions are important in understanding plant development. The morphogen was used to trigger growth and division in 1-dimension. This maintained an active cell at the end of a line of in active cells, in a similar manner to a plant root or shoot meristem (İçmeli, 2014). 4.4 Architecture & Biology

While as disciplines, architecture and biology share some similarities like,

Both deal with entities operating in context Both use computational models

The differences are in

Goals, Epistemology, Knowledge Base, Methods, Discourse and

Institutional Organization are significant.

These differences are making communication and collaboration difficult.

Despite the differences and difficulties, direct collaborations between biology and architecture are necessary not only in the narrow context of the present discussion but also because they can help to orient designing towards ecologically compatible outcomes. Another, equally exciting outcome of such collaborations will be in further contributions towards creative inspiration (Roudavski, 2009).

Unlike scientists such as biologists (but not unlike biotechnologists and

bioengineers who are also designers), designers (including architects) focus not on the study of the existing situations but on the consideration of possible futures. Working in complex situations and typically looking for futures that cannot be derived from the past or from the laws of nature, designers search the present for variables that can be modified. Variables accessible (known, found) to a designer in a given situation add up to a design space (MacArthur & Crist, 2003).Unconventional, lateral, associative moves are often necessary to expand this space and to find in its innovative outcomes. As history and the recent experimentation confirm, bio-inspiration can be a rich and rewarding source of such innovation (Roudavski, 2009).

4.4.1 Morphogenesis in Architecture & Biology. In architecture, morphogenesis often used as an inspiration for built form as a group of methods in digital media. It works not also representational tools but also generative tool for derivation and transformation of the form (Roudavski, 2009).


Understanding of morphogenesis in biology and architecture with comparing them; helps to conceive similarities and differences for these fields. It indicates potentials and advantages for the two research communities (Roudavski, 2009).

A better understanding of biological morphogenesis can usefully inform architectural designing because

Architectural designing aims to resolve challenges that have often already been resolved by nature.

Architectural designing increasingly seeks to incorporate concepts and techniques, such as growth or adaptation that have parallels in nature.

Architecture and biology share a common language because both attempt to model growth and adaptation (or morphogenesis) in silico (Roudavski, 2009).

In a reverse move, architecture and engineering can inform the studies in biology

because Components of organisms develop and specialize under the influence

of contextual conditions such as static and dynamic loads or the availability of sun light.

In biology as in architecture, computational modeling is becoming an increasingly important tool for studying such influences.

Architecture and engineering have developed computational tools for evaluating and simulating complex physical performances (such as distribution of loads, thermal performance or radiance values).

Such tools are as yet unusual or unavailable in biology.

According to advocates of morphogenetic design, they not only focus on study of the existing situation but the consideration of possibilities of nature. Morphogenetic design has the capability to sustain various functions (Roudavski, 2009). 4.5 Morphogenesis in Architecture (Digital Morphogenesis)

In contemporary architectural design, digital media is increasingly being used

not as a representational tool for visualization but as a generative tool for the derivation of form and its transformation and that is called with the digital morphogenesis. In a radical departure from centuries old traditions and norms of architectural design, digitally-generated forms are not designed or drawn as the conventional understanding of these terms would have it, but they are calculated by the chosen generative computational method. Instead of modeling an external form, designers articulate an internal generative logic, which then produces, in an automatic fashion, a range of possibilities from which the designer could choose an appropriate formal proposition for further development (Kolarevic & Malkawi, 2005).

The predictable relationships between design and representations are abandoned

in favor of computationally generated complexities. Models of design capable of consistent, continual and dynamic transformation are replacing the static norms of conventional


processes. Complex curvilinear geometries are produced with the same ease as Euclidean geometries of planar shapes and cylindrical, spherical or conical forms. The plan no longer 'generates' the design; sections attain a purely analytical role. Grids, repetitions and symmetries lose their past raison d'être, as infinite variability becomes as feasible as modularity, and as mass-customization presents alternatives to mass-production (Kolarevic & Malkawi, 2005).

The digital generative processes are opening-up new territories for conceptual, formal and tectonic exploration, articulating an architectural morphology focused on the emergent and adaptive properties of form. The emphasis shifts from the 'making of form' to the 'finding of form' which various digitally-based generative techniques seem to bring about intentionally. In the realm of form, the stable is replaced by the variable, singularity by multiplicity (Kolarevic & Malkawi, 2005).

4.5.1 Computational Architectures. Computational architectures refer to the

computationally based processes of form origination and transformations - the digital morphogenesis. Several computational architectures are identified based on the underlying concepts such as topological space (topological architecture), isomorphic surfaces (isomorphic architecture), motion kinematics and dynamics (animate architecture), key shape animation (metamorphic architecture), parametric design (parametric architecture), and genetic algorithms (evolutionary architecture) (Kolarevic & Malkawi, 2005).

4.5.1.1 Topological architecture. Greg Lynn’s essay on “architectural curvilinearity” is one of the first examples of the new topological approach to design that moves away from the then dominant deconstructivist “logic of conflict and contradiction” to develop a “more fluid logic of connectivity,” manifested by continuous, highly curvilinear surfaces (Kolarevic & Malkawi, 2005).

The defining element of the topological architecture is its departure from the

Euclidean geometry of discrete volumes represented in Cartesian space, and the extensive use of topological, “rubber-sheet” geometry of continuous curves and surfaces, mathematically described as NURBS - Non-Uniform Rational B-Spline curves and surfaces. In the topological space, geometry is represented not by implicit equations, but by parametric functions, which describe a range of possibilities (Piegl & Tiller, 1997).

Figure 75: Homeomorphic (Topologically Equivalent) Figures Source: (Kolarevic & Malkawi, 2005)


4.5.1.1.1 Topology. The notion of topology has particular potentiality in architecture, as emphasis shifts away from particular forms of expression to relations that exist between and within an existing site and the proposed program. These interdependences then become the structuring, organizing principle for the generation and transformation of form (Kolarevic & Malkawi, 2005).

4.5.1.1.2 Non-euclidian

geometries. Euclid's Elements proposed five basic postulates of geometry, of which all were considered self-evident except the fifth postulate of ''parallelism'' which asserts that two lines are parallel, i.e. non intersecting, if there is a third line that intersects both perpendicularly (Kolarevic & Malkawi, 2005).

Such a design is based on parameters and statistics, and enables a spatial

morphogenesis in a non-Euclidean 'environment'. Through the use of calculus-based tools, architectural design may become more abstract and less representational, at least in comparison to its traditional and standard types of predecessors (Lynn, 1999).

4.5.1.1.3 NURBS. NURBS are a digital equivalent of the drafting sp-lines used to draw the complex curves in the cross-sections of ship hulls and airplane fuselages. Those sp-lines were flexible strips made of plastic, wood or metal that would be bent to achieve a desired smooth curve, with weights attached to them in order to maintain the given shape. The term sp-line (the .S. in NURBS) actually has its origin in shipbuilding, where it was used to refer to a piece of steamed wood shaped into a desired smooth curve and kept in

Figure 76: Homeomorphic (Topologically Equivalent)

Source: (Kolarevic, 2005)

Figure 77: Spatial Computing with Conformal Geometric Algebra Source: (Rudge & Haseloff, 2005)


shape with clamps and pegs. Mathematicians borrowed the term in a direct analogy to describe families of complex curves (Kolarevic & Malkawi, 2005).

The main reason for their widespread adoption is the ability of NURBS to construct a broad range of geometric forms, from straight lines and Platonic solids to highly complex, sculpted surfaces. From a computational point of view, NURBS provide for an efficient data representation of geometric forms, using a minimum amount of data and relatively few steps for shape computation, which is why most of today's digital modeling programs rely on NURBS as a computational method for constructing complex surface models and, in some modelers, even solid models (Kolarevic & Malkawi, 2005).

The shape of a NURBS curve or surface is controlled by manipulating the

location of control points, weights, and knots. NURBS make the heterogeneous, yet coherent forms of the topological space computationally possible. By changing the location of control points, weights, and knots, any number of different curves and surfaces could be produced (Kolarevic & Malkawi, 2005).

Figure 78: A Composite Curve Constructed from Tangent Circular Arcs and Straight Line Segments Source: (Kolarevic & Malkawi, 2005)


4.5.1.2 Isomorphic architecture. Isomorphic surfaces represent another point of departure from the Euclidean geometry and the Cartesian space. Blobs or meta-balls, as isomorphic surfaces are sometimes called, are amorphous objects constructed as composite assemblages of mutually inflecting parametric objects with internal forces of mass and attraction. They exercise fields or regions of influence, which could be additive (positive) or subtractive (negative). The geometry is constructed by computing a surface at which the composite field has the same intensity - hence the name - isomorphic surfaces (Kolarevic & Malkawi, 2005).

Isomorphic surfaces open up yet another formal universe where forms may undergo variations giving rise to new possibilities. Objects interact with each other instead of just occupying space; they become connected through logic where the whole is always open to variation as new blobs (fields of influence) are added or new relations made, creating new possibilities. The surface boundary of the whole (the isomorphic surface) shifts or moves as fields of influence vary in their location and intensity. In that way, objects begin to operate in a dynamic rather than a static geography (Kolarevic & Malkawi, 2005).

Figure 79: Varying the Degree of A NURBS Curve Will Produce Different Shapes Source: (Kolarevic & Malkawi, 2005)

Figure 80: Isomorphic Surfaces Source: (Kolarevic & Malkawi, 2005)


4.5.1.3 Animate architecture. Greg Lynn was one of the first architects to utilize animation software not as a medium of representation, but of form generation. According to Lynn, the prevalent “cinematic model” of motion in architecture eliminates the force and motion from the articulation of form and reintroduces them later, after the fact of design, through concepts and techniques of “optical procession.” In contrast, animate design is defined by the co-presence of motion and force at the moment of formal conception. Force, as an initial condition, becomes the cause of both motion and particular inflections of a form. According to Lynn, while motion implies movement and action, animation implies evolution of a form and its shaping forces (Kolarevic & Malkawi, 2005).

In his projects, Lynn has utilized an entire repertoire of motion-based modeling techniques, such as key-frame animation, forward and inverse kinematics, dynamics (force fields) and particle emission. Kinematics is used in animation in its true mechanical meaning: to study the motion of an object or a hierarchical system of objects without consideration given to its mass or the forces acting on it. As motion is applied, transformations are propagated downward the hierarchy in forward kinematics, and upward through hierarchy in inverse kinematics. In some of Lynn’s projects, such as the House Prototype in Long Island, skeletons with a global envelope are deformed using inverse kinematics under the influence of various site induced forces (Kolarevic & Malkawi, 2005).

In contrast to kinematics, the dynamic simulation takes into consideration the effects of forces on the motion of an object or a system of objects, especially of forces that do not originate within the system itself. Physical properties of objects, such as mass (density), elasticity, static and kinetic friction (or roughness), are defined. Forces of gravity, wind, or vortex are applied, collision detection and obstacles (deflectors) are specified, and dynamic simulation computed. Greg Lynn’s design of a protective roof and a lighting scheme for the bus terminal in New York offers a very effective example of using particle systems to visualize the gradient fields of “attraction” present on the site, created by the forces associated with the movement and flow of pedestrians, cars, and buses on the site (Kolarevic & Malkawi, 2005).

4.5.1.4 Metamorphic architecture. Metamorphic generation of form includes several techniques such as key-shape animation, deformations of the modeling space around the model using a bounding box (lattice deformation), a sp-line curve, or one of the coordinate system axis or planes, and path animation, which deforms an object as it moves along a selected path (Kolarevic & Malkawi, 2005).

Figure 81: Animate Architecture: Lynn’s Port Source: (Kolarevic & Malkawi, 2005)


In key shape animation, changes in the geometry are recorded as key frames (key shapes) and the software then computes the in-between states. In deformations of the modeling space, object shapes conform to the changes in geometry of the modeling space (Kolarevic & Malkawi, 2005).

4.5.1.5 Parametric architecture. In parametric design, it is the parameters of a particular design that are declared, not its shape. By assigning different values to the parameters, different objects or configurations can be easily created. Equations can be used to describe the relationships between objects, thus defining an associative geometry, i.e., the “constituent geometry that is mutually linked” (Burry, 2000). That way, interdependencies between objects can be established, and objects’ behavior under transformations defined. As observed by Burry (1999), the ability to define, determine and reconfigure geometrical relationships is of particular value (Kolarevic & Malkawi, 2005).

Parametric design often entails a procedural, algorithmic description of geometry. In algorithmic spectaculars, algorithmic explorations of “tectonic production” using mathematical software, Marcos Novak had constructed mathematical models and generative procedures that are constrained by numerous variables initially unrelated to any pragmatic concerns. Each variable or process is a ‘slot’ into which an external influence can be mapped, either statically or dynamically. In his explorations, Novak is concerned less with the manipulation of objects and more with the manipulation of relations, fields, higher dimensions, and eventually the curvature of space itself. The implication is that the parametric design doesn’t necessarily predicate stable forms. As demonstrated by Burry, one can devise a paramorph - an unstable spatial and topological description of form with stable characteristics (Kolarevic & Malkawi, 2005).

Figure 82: Parametric Architecture: Marcos Novak‘s “Algorithmic spectaculars” Source: (Kolarevic & Malkawi, 2005)

Figure 83: Paramorph by Mark Burry Source: (Kolarevic & Malkawi, 2005)


4.5.1.6 Evolutionary architecture. Evolutionary architecture proposes the evolutionary model of nature as the generating process for architectural form (Frazer, 1995). In this approach to design, architectural concepts are expressed as generative rules so that their evolution and development can be accelerated and tested by the use of computer models. Concepts are described in a genetic language which produces a code script of instructions for form generation. Computer models are used to simulate the development of prototypical forms which are then evaluated on the basis of their performance in a simulated environment. Very large numbers of evolutionary steps can be generated in a short space of time and the emergent forms are often unexpected (Frazer, 1995).

The key concept behind evolutionary architecture is the genetic algorithm which

is a class of highly parallel evolutionary, adaptive search procedures (Frazer, 1995). Their key characteristic is ''a string-like structure'' equivalent to the chromosomes of nature, to which the rules of reproduction, gene crossover, and mutation are applied. Various parameters are encoded into the “a string-like structure” and their values changed during the generative process. A number of similar forms, “pseudo-organisms,” are generated, which are then selected from the generated populations based on predefined “fitness” criteria. The selected “organisms,” and the corresponding parameter values, are then crossbred, with the accompanying “gene crossovers” and “mutations”, thus passing beneficial and survival-enhancing traits to new generations. Optimum solutions are obtained by small incremental changes over several generations (Kolarevic & Malkawi, 2005).

In the process of genetic coding, the central issue is the modeling of the inner logic rather than external form. Other equally important issues are the definition of often ill-defined and conflicting criteria and how the defined criteria operate for the selection of the “fittest”. Equally challenging is the issue of how the interaction of built form and its environment are transcribed into the morphological and metabolic processes (Kolarevic & Malkawi, 2005).

4.5.2 Implications. Digital morphogenesis in architecture links it to a number of concepts including emergence, self-organization and form-finding (Hensel, Menges, & Weinstock, 2004). Among the benefits of biologically inspired forms, their advocates list the potential for structural benefits derived from redundancy and differentiation and the capability to sustain multiple simultaneous functions (Weinstock, 2006). In contrast to homogenized, open-plan interior spaces produced by modernist approaches, the implementation of locally-sensitive differentiation, achieved through morphogenetic responsiveness, can produce more flexible and environmentally sound architecture (Hensel & Menges, 2008).

4.5.2.1 Dynamics and the fields of forces. Greg Lynn’s work on “animate form” was very much inspired by D’Arcy Thompson “On Growth and Form”, in which Thompson argues that the form in nature and the changes of form are due to the “action of force.” With his work on using motion dynamics to generate architectural form, Lynn has compellingly demonstrated what Nicholas Negroponte had only hinted at in his seminal work from some thirty years ago, “The Architecture Machine,” also acknowledged in Lynn’s writing (Kolarevic & Malkawi, 2005).


Physical form, according to D’Arcy Thompson, is the resolution at one instant of time of many forces that are governed by rates of change. In the urban context the complexity of these forces often surpasses human comprehension. A machine, meanwhile, could procreate forms that respond to many hereto un-manageable dynamics. Such a colleague would not be an omen of professional retirement but rather a tickler of the architect’s imagination, presenting alternatives of form possibly not visualized or not visualizable by the human designer (Kolarevic & Malkawi, 2005).

Lynn argues that traditionally, in architecture, the abstract space of design is conceived as an ideal neutral space of Cartesian coordinates, but that in other design fields, design space is conceived as an environment of force and motion rather than as a neutral vacuum. There was an argument that while physical form can be defined in terms of static coordinates, the virtual force of the environment in which it is designed contributes to its shape, thus making the forces present in the given context fundamental to the form making in architecture. Lynn attributes to this position the significance of a paradigm shift from a passive space of static coordinates to an active space of interactions, which was described as a move from autonomous purity to contextual specificity. Instrumental to this conceptual shift is the use of digital media, such as animation software, which were used as tools for design rather than as devices for rendering, visualization, and imaging (Kolarevic & Malkawi, 2005).

4.5.2.2 Emergence and the fields of indetermination. Topological space opens

up a universe where essentially curvilinear forms are not stable but may undergo variations; giving rise to new possibilities, i.e., the emergent form. Designers can see forms as a result of reactions to a context of “forces” or actions, as demonstrated by Lynn’s work (Kolarevic & Malkawi, 2005).

There is, however, nothing automatic or deterministic in the definition of actions and reactions; they implicitly create “fields of indetermination” from which unexpected and genuinely new forms might emerge. The capacity of computational architectures to generate “new” designs is therefore highly dependent on designer’s perceptual and cognitive abilities. Their generative role is accomplished through the designer’s simultaneous interpretation and manipulation of a computational construct (topological surface, isomorphic field, kinetic skeleton, field of forces, parametric model, genetic algorithm, etc.) in a complex discourse that is continuously reconstituting itself - a ‘self-reflexive’ discourse in which graphics actively shape the designer’s thinking process (Kolarevic & Malkawi, 2005).

4.5.2.3 Mass customization. The numerically controlled production processes of the past decade, which afforded the fabrication of non-standardized repetitive components directly from digital data, introduced into architectural discourse the “mass-customization” (Mitchell, 2000) and the new logics of seriality, i.e., the local variation and differentiation in series. In process, building construction is being transformed into production of the differentiated components and their assembly on site, instead of the conventional manual techniques. This transformation of building design and construction into digitally driven production processes was famously manifested in Frank Gehry’s buildings, with his Guggenheim Museum in Bilbao being the most dramatic recent example (Kolarevic & Malkawi, 2005).


In parametric design, objects are no longer designed but calculated, and that allows the design of complex forms with surfaces of variable curvature that would be difficult to be represented using traditional drawing methods, and laying the foundation for a nonstandard mode of production. These objectiles are non-standard objects, mainly furniture and paneling, which are procedurally calculated in Micro-station and industrially produced with numerically controlled machines (Cache, 1995).

It is the modification of parameters of design, often random, that allows the manufacture of different shapes in the same series, thus making the mass-customization, i.e., the industrial production of unique objects possible (Cache, 1995). In other words, it is now possible to produce “series-manufactured, mathematically coherent but differentiated objects, as well as elaborate, precise and relatively cheap one-off components (Zellner, 2000). It was argued that in the process the “architecture is becoming like ‘firm ware, ’the digital building of software space inscribed in the hardware of construction.” (Zellner, 2000). 4.6 Morphogenesis in Biology

In biology, the word morphogenesis is often used in a broad sense to refer to

many aspects of development, but when used strictly it should mean the molding of cells and tissues into definite shapes (Waddington, 1956). In accordance with this strict definition, botany understands morphogenesis as the formation of shape and structure via a coordinated process that involves changes in cell shapes, enlargement of cells and proliferation by mitosis (Rudge & Haseloff, 2005). Furthermore, in biology the word morphogenesis can be used to refer either to

(I) The structural changes observed in tissues as an embryo develops. (II) The underlying mechanisms responsible for the structural changes

(Cowin & Doty, 2007).

Both understandings can be of interest and inspiration for architects, despite the fact that a literal importation of biological structures or processes into architectural design is usually not feasible, meaningful or desirable (Roudavski, 2009).

Morphogenesis is one of several processes typical for living organisms. Apart from morphogenesis, these processes include growth, repair, adaptation and aging. Transferring knowledge of these processes into designing might be also productive,

Figure 84: Bernard’s Cache “Objectiles.” Source: (Kolarevic & Malkawi, 2005)


especially in relationship to architectural structures with dynamic capacities (Roudavski, 2009).

Plant morphogenesis is a very complex process that involves many types of control mechanisms. The study of these mechanisms via direct experimentation and reverse engineering is very difficult and time consuming. Therefore, developmental biologists increasingly experiment with mathematical and computational models that allow them to simulate, understand and predict control mechanisms. This existing interest in computational modeling can serve as a translating device between the relevant processes in biology and architecture (Roudavski, 2009).

Biological morphogenesis is a difficult subject to study because it is very complex and dynamic. In the comparatively recent era of molecular biology, “morphogenesis, the deep developmental question that held the centre stage of embryological thought for over two millennia, has been somewhat eclipsed” by the more manageable studies of signaling, pattern formation, and gene control (Davies, 2005).

4.6.1 Computational Models of Plant Morphogenesis. The structural organization of plants features units of various types and sizes, for example cells, tissues and organs. Interactions between these entities combine into various regulatory mechanisms (Dupuy, Mackenzie, Rudge, & Haseloff, 2008). Multiple conceptual descriptions of plant organization can be attempted and a rigorous, formal description of such an organization is a necessary prerequisite for the computational modeling of interactions between various parts of a plant (Roudavski, 2009).

Contemporary biology employs computational modeling of its processes in combination with experiments verifying the resulting hypotheses. Experimental verification is necessary because “morphogenetic processes cannot be deduced from final form. The fact that a mechanism works on a computer is not, however, itself strong evidence that it works in life; usually, many possible mechanisms will produce the ‘correct’ result, and only observation of the real embryo will indicate which is used” (Davies, 2005).

This danger of making misleading post-hoc conclusions in biology serves as a reminder that architects, as non-specialists, should be particularly careful when claiming that developmental processes in biology are precursors to their designs (Roudavski, 2009).

4.6.2 Characteristics

4.6.2.1 Focus and limitations. Biological morphogenesis takes multiple forms that differ between kingdoms, phyla, classes, orders, families, genera and species. This diversity provides an overwhelming number of examples that is further multiplied by the co-existence of alternative conceptual understandings. Computational modeling of morphogenesis in biology is a recent approach. Consequently, and despite the natural diversity, only a limited number of available working models is available. At the moment, the existing models tackle simple organisms, often the ones used as models by many biologists (Roudavski, 2009).

In botany, plants such as Arabidopsis thaliana and Coleochaete orbicularis are commonly used to study generic processes because they are simple and already well


researched. Furthermore, Coleochaete orbicularis is a 2D species and the computational modeling of its morphogenesis is geometrically less complex (Roudavski, 2009).

Given this situation, the biological examples were selected both for simple pragmatic reasons as well as for their conceptual suitability:

A pragmatic stance suggested the selection of models that were sufficiently generic, publicly available and interesting for comparison.

Conceptually, a comparison between architectural structures, that are

typically immobile, and plants that are also comparatively static seemed less problematic than that with, for example, animals (Roudavski, 2009).

4.6.2.2 Multi-scale hierarchy. The structure of a plant had been formalized by

subdividing it into multiple scales. In their model, cell-walls are described at scale 1, cells are objects described at scale 2 and tissues are described at scale 3. Entities at different scales of description belong to the same plant and the relationships between them can be described as a hierarchy: cells are made of walls; tissues are made of cells and so on (Dupuy, Mackenzie, Rudge, & Haseloff, 2008).

Figure 85: Conceptual Diagrams Based on Photomicrograph of Coleochaete Orbicularis Source: (Dupuy, Mackenzie, Rudge, & Haseloff, 2008)


(A) Cellular architecture of plants can be conceptually subdivided into several scale levels represented in this diagram by horizontal planes. This conceptual subdivision helps to formalize the structure and functioning of plants.

(B) The entities in each level of description establish interactions with other plant constituents, and it is possible to determine a topological neighborhood for any entity: a cell is related to its neighboring cells horizontally, it belongs to an organ in a vertical upward relationship and to the walls that define its boundaries via a vertical downward relationship.

(C) The evolution of such properties is determined by autonomous inter-cell

functions and by the functions that determine interactions between entities in the topological neighborhood.

(D) Changes in the network of interactions are due to growth mechanisms and can

be broken down into birth and death operators: the division of a cell results from the deletion of four walls and the creation of ten new walls (eight subdivisions from previous walls plus the two new walls separating the newly created cell). Entities associated with new walls are then defined through one inheritance function and those associated with the two daughter cells through another (Dupuy, Mackenzie, Rudge, & Haseloff, 2008).

Interactions between components in complex structures can be expressed as

horizontal and vertical relationships. Related components can exchange information. In plants, signaling processes, for example those sustained by chemical transport, can influence cell development, positioning, patterning and differentiation. In architecture, deeper hierarchies of interconnected elements could support similar form-making effects simultaneously supporting continuous automated development, local responsiveness and targeted, non-destructive controlling (Roudavski, 2009).

4.6.2.3 Dynamic structure. Plants’ organizations are highly dynamic both in terms of chemical transport between cells and the architectural dynamics of cell development, growth and proliferation. In the architectural context, a functional analogue to the dynamic transport of chemicals through cells could account for the adaptable properties of cell congregations and the influence of this effect could be combined with other influences on cell properties (Roudavski, 2009).

In addition to the dynamic diffusion of chemicals between cells, there is a model which is responsible for dynamic structural changes in the system, for example those occurring when cells divide or die (Dupuy, Mackenzie, Rudge, & Haseloff, 2008). That model modifies the cellular structure through operations of creation and deletion. The operation of creation is also responsible for the initiation of cell properties that are controlled by the inheritance function able to account for such concepts as asymmetric division, lineage and other mitotic events. In the architectural context, this capability would be able to support generation of varied geometries in response to explicit instructions or local conditions (Roudavski, 2009).


Another dynamic attribute of plant cells is the capability for expansion under turgor pressure. The actual physics behavior of viscous plant cell-walls can be relevant in architecture only in the application to similar materials. However, the general concept of an expandable cell can further support the dynamic adaptability of the computational model (Roudavski, 2009).

4.6.2.4 Processual continuity. As is true of all natural processes, biological

morphogenesis is continuous. Its processes occur at varying speeds but they never completely halt. Once an organism develops into an adult specimen it continues changing into its phenotype or, "the observable characteristics of an individual resulting from the interaction of its genotype with the environment”. Furthermore, once the phenotype has been established, there is further interaction with the genome for regeneration, repair and possible further development (Cowin & Doty, 2007).

This processual continuity allows a high degree of individual adaptability. As discussed above, greater continuity similar to the one characteristic of living organisms can be beneficial to generative processes in architecture. It is even more interesting to consider how this continuity could be extended beyond the confines of a single design so that architects could both experiment with multiple architectural equivalents of genotypes and extend adaptive capabilities into inhabitable places (Roudavski, 2009). 4.7 Conclusion

After reviewing that chapter, it could be concluded that the field of architecture is going through a shift by depending on new techniques and the new technologies in architectural designing. This could be done by depending on using the digital media not only as representational tools for visualization but also as generative tools for the derivation of form; this is what is called morphogenesis. Morphogenesis concept was used in numbers of disciplines like biology, geology, crystallography, engineering, urban studies, art and architecture. The original usage was in the field of biology so it had been discussed the

Figure 86: Biomechanical Model for Cell Expansion in Morphogenesis: Cell Wall Response to Turgor Pressure Through A Viscous Yielding of The Cell Wall, Compensated at The Same Time by Thickening to Maintain A Constant Cross-Section Source: (Dupuy, Mackenzie, Rudge, & Haseloff, 2008)


relation between biology and architecture and got the similarities and differences between them and how it is easy to realize a complete integration between them in order to make full use of them. How architects and biologists think, the way that architecture dealing with problems and trying to solve them; however nature has already solved all problems. It was found that all of them depend on computational models during studying.

When looking to the meaning of morphogenesis in architecture which also could

be called digital morphogenesis; it means to use digital media and in the design process and dealing with variables through machines in order to get lots of alternative solutions for the design problems with different forms. These types of forms differs between each other and that depends on the trend used to get the form of the design as when using computers in the design process in the field of architecture, it opened doors to generate more and more new trends in architectural designing which could be called computational architecture like, Topological architecture, Isomorphic architecture, Animate architectures, Metamorphic architecture, Parametric architecture, Evolutionary architecture, performative architecture and genetics. These new trends have their specifications and their way followed to design and generate forms.

When looking to the meaning of morphogenesis in biology and specifically in botany field, it means there would be a deal with many types of control mechanisms and variables like growth, repair, adaptation and aging. To deal with those variables there should be a computer system to computational models of plants to deal with during studying. These variables help to generate more alternative of forms. Biological morphogenesis takes multiple forms that differ between kingdoms, phyla, classes, orders, families, genera and species. This diversity provides an overwhelming number of examples that is further multiplied by the co-existence of alternative conceptual understandings.

Finally, after studying those two types of morphogenesis in architecture and in biology, it is a must to realize a complete integration between biology and architecture. Despite the differences and difficulties, direct collaboration between them is necessary not only in the narrow context of the present discussion but also because they can help to orient designing towards compatible outcomes and towards creative inspiration. By realizing the complete integration between architecture and biology and putting in mind that both of them depends on computational models, so through the derivation of form process there would be a complete integration also between digital morphogenesis and morphogenesis in biology and that would open the doors to generate a new type of architectural design trends which could be called bio-digital morphogenesis. This new trend aims to generate forms for designs depending on digital media and also starting with a biological base even it could be of plants or any organism.


Bio Digital Morphogenesis PART -3-


CHAPTER -5- BIO-DIGITAL ARCHITECTURE

“Natural spiraling & twirling (Genetic & Environmental) are growth strategies conceptually understood & sometimes viewed across scales – cosmological to quantum- from galaxies, ocean waves, trees, insect flight paths to shells, & molecular orbits. Spirals are the universe's embedded locomotion.”

(Dollens, 2009)



Chapter 5: Bio Digital Architecture 5.1 Introduction

It is being associated with Sir Charles Sherrington’s more ornate and not

meaningless metaphor for thought that; “The brain is an enchanted loom where millions of flashing shuttles weave a dissolving pattern.” (Byatt, 2004) In one of the most appealing

conjectures for the birth of architecture, Gottfried Semper outlined a series of hypothetical developments in which he saw a fundamentally different order from that of earlier theorists who claimed the mere hut as architecture’s starting point. Semper speculated that ancient technology in the form of craft production like pottery, weaving and knotting; held a key that then opened the way to conceptual development of a frame covered with woven walls and roof (Herrmann, 1984).

Technology, as manifested in

weaving, brought forth the transformation of plant fiber into rigid, semi-flexible, or flexible rugs, mats, lattices (planar geometric objects serving to clad matrices) that could then be conceptualized as partitions or walls. With the wall, the potential division and subdivision of otherwise abstract space, virtual space became physical; and here, in the spatial matrix, divided and articulated, architecture began to breathe; a breath filtered through botanical-technological construction (Herrmann, 1984).

Semper saw weaving as an architectural act, not as a metaphor. Additionally he saw knotting, lashing, braiding, and banding as related crafts joinery pointing to complementary technological developments where woven panels could be connected sequentially—tiled—to make spatial partitions modular—a global practice continuing today, from the marshlands of Iraq to spontaneous squatter cities around the world (Herrmann, 1984).

Figure 88: Photograph of Woven, Urban Walls in Peru’s Pueblos Nuevos

Source: (Dollens, 2009)

Figure 89: Semper’s Braids Source: (Dollens, 2009)


From this most organic and technological view of the birth of architecture, sometimes, referencing Sempers' ideas in a historic vein and sometimes in a new context of weaving & knotting information; sometimes, more metaphorically, looking to instances where informational, scientific, and computational developments are leading to the generation of new ideas that, in turn, power generative visions, technologies, or strategies for architecture; for example, through biotechnology, algorithmic growth, or bio-mimetic design (Herrmann, 1984).

5.1.1 Different Points of View of Architecture Dealing with Plants

Semper’s vision of architecture pictured man manipulating plant matter with analog technologies (Dollens, 2009)

Dollens's view will include another look at plants with the benefit of digital technologies from mimetic morphology to platonic forms sculpted by induced evolutionary forces forming new types of digital and analog cellular life and genetic-related geometries (Dollens, 2009).

Figure 91: Dollens's Vision of Architecture Source: (The Researcher based on (Dollens, 2009), 2015)

Figure 90: Semper‘s Vision of Architecture Source: (The Researcher based on (Dollens, 2009), 2015)


5.2 Approaches to the Bio Digital Architecture

5.2.1 Virtual Reality. If virtual reality has become a pop cliché, it is needed to remember that its visualization and rendering technologies as well as their generating computational systems were among the first to cross mainline, analog perception with demonstrations that other realities exist (ironically, still just a little beyond grasp), digitally guided realities, not merely computerized mechanical systems and labor-saving machines. Still, cyberspace would remain a poor intellectual cousin to Surrealism except for the fact that ultimately its “consensual hallucination” can and will be rationalized, built, experienced, and retooled as a conditioner for nano and bio-generated architectures. Even if virtual place is now emerging from cyberspace, its manifestation for architecture (outside the game world) is still on the horizon. After all, being “everywhere and nowhere” (a claim made for cyberspace) currently ends you up in something as exciting as spam land (Vidler, 2001).

Nevertheless, the idea of virtual place has deeply inflected, infected, and influenced the thinking of a sufficient number of architects, artists, and theorists to push spatial reality through new filters, to hybridize thoughts so that they begin to grow new forms and that these new forms, structures, and materials can fuse with the promise of earlier VR experiments that will, in fact, be grown physically and eventually be inhabitable. Currently, such investigations are taking place in many areas; some that look to medical technologies, game development, compression and algorithmic generation as well as to digital-analog botanic growth. All the experimental work looks to generate ideas, theories, and (or) structures lodged in the folds of digital visualization, computational botany, biology, programming, medicine, physics, history, and philosophy. A couple of further notes will open some of the folds and clarify some metaphors of this new view of a digital-botanic architecture, permitting a deeper look into the inner folds. Most essential in this regard is a working understanding of the terms meme, monad, and meme-monad in relation to, but different from, mimetic and biomimetic, and they will be taken as they come (Vidler, 2001).

5.2.2 Live Architecture. The idea of live architecture has existed for a long time. In the literature of architecture, building and body as organism have been identified, organized, and categorized together for centuries—a trail of thought built, written, and published. This concept, though widely distorted by 17th- and 18th-century Cartesian perspectives (when it was believed that the universe, excepting the human soul, could be mechanically explained) ultimately survived to infuse, insert, and/or infect a hybrid notion of machine/ organism (Dollens, 2009).

Cartesian perspective slowly evolved by means of the thoughts and theories of

Leibniz, Darwin, Einstein, and Watson and Crick (and, of course, many others), splicing an organic perspective back to the mechanical. Even so, It is speculated today, most people

-1- Virtual Reality

-2- Live Architecture


consider architecture’s position unshakably mechanist, and it is only with effort that this view can be contested by suggesting in its place an evolutionary pedigree by which architecture is a kind of biologic organism and a potential, if mostly unacknowledged, near-life or semi-life form to be investigated in the animating force-field and particle-universe represented in quantum theory and demonstrated in physics, biochemistry, biotechnology, cellular automata, and nanotechnology. It must be known at least that architecture is not inert objects (Dollens, 2009).

5.2.3 Theory of Monads and Theory of Memes. Furthermore, it is important to recognize that there is an entertainment for a conceptual possibility of architecture, technology, and human thought being biologically linked and that the link might be constituted through some undiscovered properties that can be outlined and hybridized as an architectural metaphysics conceptualized with the aid of Leibniz’s theory of monads, which provides a unit of universal perception and mirroring knowledge yoked to Richard Dawkins’s theory of memes: ideas as live, contagious, transmissible units of perception, information, and culture that can be embedded in architecture. Dawkins’s memes provide a hypothetical agent of transmission akin to germ theory, at the same time that they suggest that thoughts and representations of thoughts as cultural units are infectious and potentially viral when seen in the light of genetic, cultural inheritance (Dawkins, 1976).

5.2.3.1 Theory of meme-monad. Conceptually, the meme-monad begins to

foreground a mechanism for transmission and implantation of cultural memory that, when contemplated in harmony with something like Luis Fernandez-Galiano’s brilliant concept of architecture (Fire and Memory: On Architecture and Energy) as an entropic system (and therefore molecularly alive), further suggests architecture’s potential as a kind of intelligence or intelligence device (Galiano & Cariño, 2000).

5.2.4 Architecture Re-conceptualization

“The tenacious survival of urban schemes or building typologies, the rare consistency of some formal layouts, and the continued adherence to certain construction solutions are evidence of the existence of a morphological memory: a memory that does not rest only in the heads of builders, inhabitants, or spectators, but is present as well in the architecture itself.” (Galiano & Cariño, 2000). Fernandez-Galiano’s “morphological memory” is compatible with the use of

meme-monad and clearly hints at “architecture itself” being infectious. What is being driven at is that architecture deserves to be re-conceptualized in a biologic frame, not merely in a frame of materials, systems, and aesthetics. Through such a re-conceptualization, the notion of a botanic or biologic architecture will no longer seem marginal (Dawkins, 2000).

-3- Theory of Monads

and Theory of Memes

Architecture Re-conceptualization


In brief, architecture, reduced to the concept of a machine or object has lost

biologic connections that once adhered it to us and to nature as closely as shells, dens, nests, and boroughs to the species that respectively inhabited them. This current architectural disconnect fosters a false sense of humans as species-independent from building and environment. In fact, architecture is part of an ecosystem and, more specifically, is a symbiotic growth dependent on human intelligence and muscle (or its mechanical replacement). To use another of Dawkins’s phrases, architecture is an “extended phenotype,” which can be explained by Matt Ridley’s words: “The nest of a bird is just as much a product of its genes as its wings are.” In this conceptual frame, architecture can be seen as evolving biologically (at least mimetically) as evolving (Dawkins, 2000).

Even before Semper’s thesis, architecture had been divorced from the notion of

an organism. It hadn't been said that it stopped evolving mechanically or aesthetically, but that the practice of making buildings has not kept pace with other cultural evolution specifically, capitalistic and scientific evolution. Simply stated humans make buildings (our nests) and animate them with mechanical systems and think of them as real estate; yet slowly, as wetware and software are been evolved with the capacity to think, a sentient or semi-sentient, self-assembling architecture could be contemplated, also infusing skyscraper nests could be contemplated with the potential for thought or responsive environmental intelligence. Equally slowly, but more and more conceivable as our mechanical systems come to function like and resemble biological organisms, we can begin to appreciate architecture as more than materially entropic, looking instead to architecture as systems entropic, and seeing in the systems’ interdependent workings relationships similar to those seen in organic nature, say in an air-cooled termite tower (Dawkins, 2000).

Without any over stress on a realm of science fiction (SF), there was a scant public imaging of advanced architecture with this exceptional passage from William Gibson’s Idoru: “You mean the nanotech buildings? . . . Virtually had failed to convey the peculiarity of their apparent texture, a streamline organism. . . . The entire façade of one of the new buildings seemed to ripple, to crawl slightly. . . . They slid apart, deliquesced, and trickled away, down into the mazes of an older city.” Clearly, a seed of biological- computational architecture growing in the dark of Tokyo nights filters into popular culture through Gibson’s novel. So, growth of structures is not a totally foreign notion for general contemplation (Dawkins, 2000).

5.3 Botanic Digital Architecture

As the 17th-, 18th-, and 19th-century morphological study of plants evolved along with the technology of the microscope’s improving optics, studies that ultimately emerged as botany, modern biology, and microbiology, so too, these same sciences continue to evolve in the 20th and 21st centuries, radically transformed by quantum mechanics and the discovery of DNA/RNA. Each successive technological development in this historical progress yielded science a deeper view into the process of living organisms and each introduced a new direction and a wider conceptualization of botanic and biological life that led, only recently, to the idea of biological products and genetic manufacturing determined, not by evolution, but by laboratory manufacturing and boardroom decisions. The concept of cellular development now includes the concept of cellular redevelopment and creative


mutation. Yet, such scientific transformations are not limited to the world of science, they are rippling through the art world and popular media, creating and affecting the way of thinking about nature and the way of producing culture. If man’s phenomenal success in colonizing all parts of the globe is specifically owing to technology—sanitary or health, heating or cooling, and transportation systems, etc. then it makes at least partial sense to look to technology for evolving and correcting the seemingly uncorrectable mess that success has caused. In a sense, to regrow or overgrow development (Dollens, 2009).

Furthermore, bio-mimetics, the scientific method of studying, for example,

plants, animals, minerals, shells, etc., for an understanding of a specific quality like hardness, softness, reflectivity, self-assembly, etc. That can then be applied to industrial and design production, applies directly to architecture and technology by teaching

How to look to plants (and nature in general) in order to extrapolate a

desirable quality. How to use technology in order to realize that extrapolated property in

another form, scale, and/or material (Mattheck, 2004).

Possibly, a digital-botanic architecture may emerge, first, as a series of biomaterials before those materials are synthesized as a building life-system. Importantly, bio-mimetic investigation can be used to produce architectural and design prototypes where morphological qualities of a plant, say leaf overlap, or asymmetric harmonic proportion (Fibonacci phyllotaxis) can be applied to the shape and function of potential architectural structures and surfaces while maintaining a linked consideration of the new material properties intended to bring the structure into being as a bio-animate environmental participant and sensor (Dollens, 2009).

Figure 92: Digital-Botanic Architecture Source: (The Researcher based on (Dollens, 2009), 2015)


Paralleling and sometimes intersecting this view to botany and technology as sources of potential architecture stands computationally grown architecture, which translates information through a coding process into potentially habitable spaces by means of genetic algorithms, cellular automata, or artificial intelligence, all potentially realized through CAD/ CAM or AAD production or, eventually, nanotechnology. In what is becoming known as genetic or evolutionary architecture, this process of design results in a formerly almost unthinkable quality for architecture (but an indispensable quality for biologic life): self-replication and the ability to evolve (Frazer, 1995).

while genetic or evolutionary architecture (like Gibson’s Nano-buildings) seemingly has the ring of SF, it has moved beyond dreams and at this moment is slowly creating virtual models and being theoretically articulated so that resulting structures, spaces, and prototypes are as much a matter of time and financial support as technological advancements. So while many aspects of a digital-botanic and a computationally generated architecture remain theoretical today, there is no reason to doubt that future technologies will grow living cells (silicon and carbon) that can be directed by genetic architectural programming. Given such a scenario, one will see the melding of inorganic computation with organic life, resolving and producing a new vision of habitable space (Frazer, 1995).

Figure 93: X-frog Truss-Frame Grown from A Tree (Top Left) to Study Possible Structural Articulations for A Building Frame and Columns

Source: (The Researcher adapted from (Dollens, 2009), 2015)


5.3.1 Seeding Digital-Botanic Architecture.

''We must be clear that, when it comes to atoms, language can be used only as in poetry.'' (Bohr, 1971) Louis Sullivan’s A System of Architectural Ornament is analog, transcendentally

poetic, quasi-scientific, and ornamental. His System establishes a series of steps, a recipe and formula—loosely, an algorithm—for the generation of geometric surface volumes and plant-like growth as an initial push toward design development and, maybe, a seed of botanic architecture. After evolving geometries or, as Sullivan says, the development of a blank block through a series of mechanical manipulations, a progression of physical and metaphorical steps had been outlined that lead toward the growth of ornamental botanic life invading the “blank block” (Dollens, 2009).

Figure 94: Part of the A System of Architectural Ornament – Plate 2 Source: (The Researcher adapted from (Dollens, 2009), 2015)

Figure 95: Tumble Truss Project Lexicon, Observational Biomimetics Leading to Physical Models Source: (The Researcher adapted from (Dollens, 2009), 2015)


By discussing these first seven sketches for Plate 2, Manipulation of the Organic, any of these forms may be changed into any of the others through a series of systematic organic changes technically known as ‘morphology’. Sullivan articulates his experiments in an attempt to develop his thesis into a hybrid textual/graphic hypothesis, suggesting that for him architectural form has inherent “organic” real life, not merely metaphoric or ornamental suggestion. He had, in fact, already laid groundwork for such suggestion when he began the System with a little sketch of a germinating seed (Sullivan, 1967).

Figure 96: Growing with Digital Model Source: (The Researcher adapted from (Dollens, 2009), 2015)

Figure 97: Xfrog Grown Structural Truss Based on

Physical Tumble Truss Model Source: (The

Researcher adapted from (Dollens, 2009), 2015)


5.3.2 Sullivan's Concept for Development

Above is drawn a diagram of a typical seed with two cotyledons. The cotyledons are specialized rudimentary leaves containing a supply of nourishment sufficient for the initial stage of the development of the germ (Sullivan, 1967).

The Germ is the real thing; the seat of identity. Within its delicate mechanism lies the will to power: the function which is to seek and eventually to find its full expression in form (Sullivan, 1967).

The seat of power and the will to live constitute the simple working idea upon which all that follows is based—as to efflorescence.

Sullivan establishes growth, change, mutation, and will to power as his Nietzscheian, transformative criteria for the development of architectural thought, which then could be applied to ornament and may be also applied to architectural production. The seed or seat of future identity/form that firstly developed in the graphic theory is literally a polyline, a drawing of a graphic cell and then a series of polylines or cells containing and expressing instructions much simpler but metaphorically similar to a gene’s encapsulation of biological instructions. If expressing instructions through poetic transliteration and interpretation as new codes, they can power, in Sullivan’s terms, impulse, growth, and creativity in digital software (Dollens, 2009).

Figure 98: A Typical Seed with Two Cotyledons from Part of The A System of Architectural Ornament – Plate 2 Source: (Dollens, 2009)

Figure 100: Nietzscheian, Transformative Criteria Source: (The Researcher based on (Dollens, 2009), 2015)


Now, such instructions may be read as metaphorical equivalents of protein instruction or, more prosaically, elements of a grammar and may then be translated, rewritten, edited, and regrown in digital realms, in cellular automata, in artificial life, and in algorithmic and textual programming (Dollens, 2009).

5.3.2.1 Efflorescence. Sullivan’s choice of efflorescence, this code word for a process of life and growth, instills botanic transformation in both a physical and metaphorical sense, while, in sum, the iconic drawing of a seed with two cotyledons (dicotyledon). There is no doubt that there is an intention to create a transforming, botanically-based growth system expressed in graphic icons and supplemented with text, a grammar and lexicon with instructions which could be called as a system’s code. Sullivan created a series of poetic, graphic and text algorithms constituting the metaphoric design, which had been previously used in buildings, then redirected as drawn ornament whose imbedded code sprouted this System; that system is now capable of sprouting, inspiring, digital growth (Dollens, 2009).

5.3.2.2 Applying growth and generation to architectural design. A botanic

underpinning established, Sullivan then set out to describe and illustrate how growth and generation may be applied to architectural design through the development of a series of cellular drawings (genotypes), each linked to the preceding and each leading to the next, a visual progression developing this geometric and botanic lexicon into a transformative evolutionary process that could be artistically determined and transformed while autonomously efflorescing (living), flowering through will to power expressed as an architecturally extended phenotype. Furthermore, the three dicotyledon paragraphs hint (the completed System vindicates) that form follows function, was, in Sullivan’s 1924 organic theory, still a living, progressive principle by which the process of design links botanic as well as biologic life with geometry (not merely reductive, spatially programmatic requirements, such as a floor plans) (Dollens, 2009).

Figure 99: Applying Growth and Generation to Architectural Design Source: (The Researcher based on (Dollens, 2009), 2015)


5.3.2.3 Inspiration in architecture. Sullivan, the architect-pioneer of the skyscraper as well as the transcendental architectural theorist/poet, found inspiration in cell morphology, plant and human anatomy, engineering, and science, and there might not be any protest of the inspiration which has been sparked in the digital architecture (Dollens, 2009).

“. . . Architecture will be the emanation of what is going on inside of us at present, the character and quality of our thoughts and our observations, and above all, our reflections.” (Sullivan, 1967).

There was no protest of being associated with the experimental use of software

intended more for pastoral 3D generation of natural forms, such as oak trees, than as a tool for investigating architectural space based on botanic growth (Dollens, 2009).

Nowadays it could be seen and thought of segments of the System as germinators

whose genetic expression reached one threshold in Sullivan’s lifetime and whose unexpressed potential, like that in DNA, may continue to reveal itself in future growth and morphosis. Sullivan’s System knots a developmental thread for articulating static graphics as dynamic, serial genotypes that then articulate forms found in natural systems capable of being woven as experimental, structurally generated, extended phenotypes (Dollens, 2009).

Beyond the craft metaphor employed by Semper, it must be acknowledged that

Sullivan’s weaving would integrate the loom with the warp and weft. The threading vines curved from warp to weft infected geometry and botanically colonized this architecture, blurring and conjoining cage-structure (the loom), walls and ornament (the thread and fabric) as plant architecture (Dollens, 2009).

5.3.2.4 Integration between Sullivan ideas and meme monad compounds

Figure 100: Collaboration between Sullivans' Ideas and Meme-Monad Source: (The researcher based on (Dollens, 2009), 2015)


With these observations in mind and cross-fertilizing them with the notion that Sullivan’s ideas are alive, transmitted through meme-monad compounds, new ideas that lead to designs and forms are being grown. In a sense which has been entered into a one-sided collaboration with idea-seeds (meme-monads) embedded in Sullivan’s physical and theoretical work that is, to an extent, infected by Sempers' thoughts about architectural origins in organic craft and botanic materials. These reconstituted ideas are in turn organized and interpreted through mechanisms postulated by Leibniz and Dawkins, which, when joined, they could constitute a new metaphysical strain of information transference by meme-monad, making Sullivan Semper ideas available for a kind of opportunistic, infectious, genetic-idea mutation—a benign idea-virus. The infectious nature of memes has allowed the replication and the transmission of Sullivanesque ideas, while the quantum-scale qualities of universal perception and mirroring found in monads has kept them conceptually and environmentally clear and available (Dollens, 2009).

5.3.2.4.1 Example of collaboration

Figure 101: X-frog Growth with Pod Dispersion; Inspired by Sullivan’s A System of Architectural Ornamentand His Merchant’s National Bank, Grinnell, Iowa Source: (The Researcher adapted from (Dollens, 2009), 2015)


Example clarifies that when collaboration is been realized between Sullivan

ideas which is symbolized in his Merchant’s National Bank and the meme-monad compounds (seeding ideas) when starting from a seed of a plant and starting simulating Sullivan's design in order to get a new growing design which is grown from a plant depending of Sullivan's ideas of growth and generation when they are being applied to the design through a transformative evolutionary process (The Researcher, 2015).

Figure 102: Xfrog Growth Developed As A Tall Building Inspired by Sullivan’s A System of Architectural Ornament and His Merchant’s National Bank

Source: (The Researcher based on (Dollens, 2009), 2015)


5.4 Application

5.4.1 Hypothesis. In the merger of botanic and digital production it has been discovered potentials inherent in software such as X-frog when hybridized with other software such as Rhino or Maya, etc. In such hybridized cases, digitally realized volumes mimic or simulate organic growth; or, more interestingly, make possible the application of growth simulation for volumetric shapes, and these grown shapes can then be engineered and detailed as architecture.

Imbedded through this simulation of growth is cognitive and biological learning

growth of these thoughts manifesting themselves in the resulting sculptural and architectural production. While relying on metaphor, it also had been trusted that the hypothesis of growing forms and geometries from System-seeds, combined with information applied from botanical observation and earlier Tumble Truss Project experiments.

Figure 103: Hypothesis Source: (The Researcher, 2015)


“The gene specifies how development occurs, and that in turn specifies how behavior occurs. The spooky truth is dawning on scientists that they can regard behavior as just an extreme form of development.” (Ridley, 2003)

This growth process has been chosen to be attempted with observational, biomimetic botany. Yet the process is as fully open to other visualization methods or information patterns where software integrates and fuses botanic information with geometry—growing geometrics in place of branches, but able to algorithmically establish sub-branching, budding, and flowering; for example, in simulated architectural growth (Dollens, 2009).

Such procedures, establish the claim that Sullivan’s System harbors live, genetic

information. If so, then his drawings (and many other drawings by implication) are the equivalent of Jurassic amber encasing DNA. So, if entertaining such a scenario, a mechanical reproduction, such as an edition of A System of Architectural Ornament, carries Sullivan’s genetic code-seed, implanted with his pencil in the original drawings, his genetic-graphic imprint, transported through space and time, into new designs where it confers powers of inheritance and morphing (in his sense) to new work, while equally insuring offspring (Dollens, 2009).

This process as analogous to, or at least as an offshoot of, the concept that live,

cultural units of transmissible information—meme-monads—can be carried through history and infect and/or bequeath, a gene-like system of cultural and physical transmission (Dollens, 2009).

The hypothesis that architecture, as a living system of expression, is continuous;

that it is a biological, intellectual, and philosophical expression of its builders; and that tools such as computers are today’s looms for digital, virtual weavings.

5.4.2 Introduction for Examples. There have been a series of experiments with simulated digital trees, hybridized into architectural elements, illustrates botanic forms and their morphological and mathematical attributes applied to design systems and structures. Using this generative process demonstrates how the transference of some biological properties, held in algorithmic notation, such as phyllotaxy, allometry, and phototropism, may be inherited by architectural and design elements derived from plant simulations and their corresponding biological math (Dollens, 2009).

5.4.3 E-Trees & E-Plants. It had been called the plant simulations eTrees to distinguish between living trees and the models. The programs which had been used most are Xfrog and Rhino. Xfrog is frequently used to computationally “grow”—simulate—lifelike digital trees and flowers for films. It can produce forms based on botanic growth, imparting to its 3D files selected attributes of living organisms—for example logarithmic proportion, branching, gravitropism, sequencing, and spiraling. But its design-growth parameters can also be tasked to generate original structures based on the organically derived algorithms it uses to mimic, say, an oak or an elm. Or, Xfrog can substitute solids—spheres, cubes, cones—for leaves, stems, or branches. Figuratively, such manipulation results in generic species of digitally grown branch structures. For example, tree branching may be transformed—computationally hybridized—to produce experimental forms with botanic heritage (Dollens, 2009).


5.4.4 Examples

5.4.2.1 Example -1- E-Tree anatomy & morphology.

Figure 104: Using X-Frog to Generate a Plant Source: (The Researcher adapted from (Dollens, 2009), 2015)


Figure 105: Converting This E Tree to Be a Building

Source: (The Researcher adapted from (Dollens, 2009), 2015)


5.4.2.2 Example -2- E-Tree column. Following the lessons of Sullivan’s system but moving away from digital

mimesis, this project segment looks to generate a growth that could, in itself, become a basic design element like one of Sullivan’s underlying blocks. A tree and a leaf were grown in Xfrog. The tree was begun as a dual-rooted trunk, and then inverted to transform the roots into branches (Dollens, 2009).

Figure 106: X-frog Grown Tree-Column Source: (The Researcher adapted from (Dollens, 2009), 2015)


Figure 107: STL Tree Branches Supporting Leaf Grown Floors Source: (The Researcher adapted from (Dollens, 2009), 2015)


5.4.2.3 Example -3- E-Tree branch and tendril morphology

5.4.2.3.1 STL & SLS E-tree models. Branch and tendril development are evolving as multi-directional, flexing structural trusses that gradually erase the digital tree trunks. Simultaneously, the branches sprout secondary growths based on flowers, leaves, tendrils, and pods that are eventually reprogrammed as living or mechanical spaces for prototype buildings (Dollens, 2009).

Figure 108: E-Tree Branch & Tendril Morphology Source: (The Researcher adapted from (Dollens, 2009), 2015)


5.4.2.4 Example -4- E-tree animation: Arizona tower An STL model of the Arizona Tower sprouts roots and branches at forking

nodes, from which, over scaled pods and cubes were reprogrammed into room like volumes. Software-grown e-Tree programmed to grow branches into a self-supporting structure with outstretched branch tips defining a point-cloud for later glass skin generation and, finally, Para Cloud generated components derived from almond shells as 3D surface components (Dollens, 2009).

Figure 109: E-Tree Animation: Arizona Tower Source: (The Researcher adapted from (Dollens, 2009), 2015)


5.4.2.5 Example -5- Self-shading tower for Los Angeles. As already seen, the E-tree which generating this tower’s cylinder is also a

component of other projects—a kind of spine whose structural code lends itself to multiple design paths resulting in different kinds of structural leafing and branching forms. While prominent in the developmental stages of the tower’s panels, the E-tree is eventually repressed in favor of the load-bearing monocoque facade supporting the building and held in compression and tension by the fifteen floor planes (Dollens, 2009).

Figure 110: Self-Shading Tower for Los Angeles Source: (The Researcher adapted from (Dollens, 2009), 2015)


5.5 Recommendations

It would be recommended that, by depending on Louis Sullivan's system of architecture ornament through the development of a blank block, there is a series of steps in order to generate a bio-digital building.

1- Simulating Sullivan's system of development of a blank block. 2- Apply this system digitally, not by drafting manually, by applying the concept of

growth in a biological element. 3- Depending on X-Frog program in order to investigate (notice) the development of

the plant by changing the variables of the different parts of the plant. 4- Changing these values of the variables in order to produce new different generations

of one building family. 5- After this development of the plant, one of these generations would be chosen in

order to be applied in the building. 6- After being settled on one of them, it would be engineered and detailed in an

architectural program in order to be used in a building.

Figure 111: Steps to Produce A Bio-Digital Building Source: (The Researcher, 2015)


5.6 Conclusion

After reviewing this chapter, it could be concluded that Gottfried Semper saw that weaving could be considered to be an architectural act not as a metaphor, as it is one of the most appealing conjectures for the birth of architecture. Semper's vision of architecture is that the architect could deal with the nature by analogy in order to design a building and there are many different visions for architecture. One vision of those is for integrating buildings and biological design includes inventing new architectural systems—thinking of them as natural; thinking that architecture is part of nature. A parallel strategy fosters collaborations between design, biology, and industry thereby encouraging designers to enter industrial and manufacturing production in order to create new biomaterials.

When looking at biology and architecture it was found that they both has

potential inherent so by assuming that when collaboration is done between them in software depending on those potential inherent in software such as between( x frog) as a biological software and (Maya or Rhino ceros) as architectural software. By that hybridization there would be digitally produced volumes that mimic or simulate organic growth in order to realize self-replication in the form and confirming the ability to evolve.

Biology and technology will define buildings’ increasing ability to interact with

nature. Such buildings are likely to be nurtured, and their functions guided, from software, computation, environmental sensors and actuators, and later from living systems. In this scenario, software and scripting become interpretive tools for generating, analyzing, and integrating design into nature.

But morphogenesis in architecture is understood as a group of methods that

employ digital media not as representational tools visualization but as generative tools for the derivation of form and its transformation.

When looking at biology and architecture it was found that they both have similar potential inherent so that encourage for collaboration between them. By assuming that when collaboration is done between them in software depending on those potential inherent in software such as between (x frog) as a biological software and (Maya or Rhino ceros) as architectural software. By that hybridization there would be digitally produced volumes that mimic or simulate organic growth in order to realize self-replication in the form and confirming the ability to evolve.

When that hybridization is done that could produce a bio digital design approach

which aims to start designing depending on computers simulating a biological element growth digitally and its structure in order to produce volumes that are able to be evolved, could replicate itself and its structure concept would be the same structure for the building then, these volumes would be engineered and detailed in order to use them in architecture.

By depending on computers as a generative system of design by analyzing the

structure of the biological element to be a structure of a building by analogy and that structure depends on range of variables which could be changed by changing the value of these variables to produce generations of one building family, that is called bio-digital morphogenesis, that what is this research aims to reach.


Conclusion This thesis has discussed a new approach of design which is called a bio digital

design. This approach is trying to solve thesis's problems which are; how to start a design process from a biological base and how to apply one of plants' Fibonacci phyllotaxis to the generated building in order to generate new trends of forms which are being generated digitally.

By reviewing this thesis, it would be found that it consists of three main parts which contains five chapters.

The first part consists of two chapters. It is discussing the generative design approach and how could the design process be achieved through depending on a set of rules or an algorithm in order to generate forms in the first chapter. Then, it could be concluded that the computer would be a generative tool which depends on a generative system in order to generate forms. What would make that easier is that computers are depending on algorithms which the designers are required to translate their origin ideas to be written in a set of rules. After that, there would be a code of each concept which has many variables that could be changed by the designers to generate new different forms belong to one family.

In order to translate the designer's ideas to be written as a set of rules that has been discussed in chapter two, in the first part. It has been concluded from that chapter that, there is many programming languages and each one has its advantages and drawbacks. They are being developed by time. A new type of them has been generated latterly which is called visual programming language (VPLs). It consists of sliders and looks like a flowchart. Dealing with that new type is easier than the old textual language. After that, it has become important for the old textual language to be developed so, the modern one has been generated. It has been proved that the modern textual programming languages are easier than the visual ones.

After reviewing what has been concluded from those two chapters, there would be a main conclusion of this first part. The main conclusion of that part is that depending on a computer as a generative tool which depends on a programming language using algorithms which are considered to be the main connector between the human mind and the computer system so, computers has been become part and parcel of any design process.

The second part is discussing the main relationship between architecture and biology. Starting with a new design approach which has been generated after the trend of bio-mimicry has been developed. This new approach is being inspired from nature so it has been called, bio inspired design approach. This new approach differs from bio-mimicry approach as it is not cradle to cradle; it is related deeply to nature and depends on it in everything not just simulating it like bio-mimicry. Bio inspired design approach considers a human is a part of the design process and each decision in the design process should be taken in order to benefit human and nature and not to harm each of them. Bio inspired approach of


design is considered to be a complete integration between nature, science and creativity. By looking to nature, it is the main source of all designs. Depending on nature to solve all the problems which are facing designers through the design process and all that problems have been solved before by nature so that, there is no reason to rethink for solutions for problems which has been solved. By looking to science, it is important to develop biological materials and controlling their behavior in order to generate new biological materials. By looking to creativity, it is playing an important role in the designer's way of thinking and the idea which is being assumed to be realized in a building.

When it comes to the ability of generating forms and their transformation, there must be computers in order to simulate models. Depending on the digital media in order to generate forms is called morphogenesis. When it is used in architecture field, it is called digital morphogenesis, but when it is used in the biological field, it is called biological morphogenesis. What distinguishes the digital morphogenesis is that, its study of form depends on different approaches like topology, non-Euclidian geometries or NURBS. When studying biological morphogenesis, it depends on studying plant's life for example; their variables are called Fibonacci phyllotaxis like growth, overlapping, hierarchy or dynamic structure. Each one of them has its different variables and its way of dealing to realize full use of it characteristics.

After reviewing what has been concluded from these two chapters. The main conclusion of this second part is that the design process must be oriented to be biologically as that would be very useful for nature. It became important to depend on a bio inspired design approach as a new approach for designing. The forms which are being generated from that approach are being distinguished with one of plant's Fibonacci phyllotaxis.

The third part is discussing the complete integration which is expected to be realized between the first part which is specified for generative design and programming and the second part which is specified for bio inspired design approach and morphogenesis.

Finally it has been concluded that using computers as a generative tool to generate forms depending on a programming language, besides following a biological approach of design through making full use of the similarities between architecture and biology. They both deal with inputs and producing outputs, and both need a computer for simulating models. When the designer follows the bio inspired design approach of designing, a proto type is being produced, then, trying to apply one of plant's Fibonacci phyllotaxis in the prototype. All these operations are being simulated by using a computer so that, there would be variety of the outcomes but they all belong to one family. After selecting the building, it would be engineered and detailed through an architectural program in order to be implemented.


Using programs There are three categories of programs which have been used during this

research

2D Architectural Drawings Programs Biological Simulation Programs Parametric Design Programs

In the first category, there are a lot of programs but, AUTOCAD is the one which

has been used in this research. AUTOCAD is an architectural program which is used in all 2D drawings like diagrams, analysis or any 2D architectural drawings.

In the second category, there are a lot of programs but, X-frog is the one which

has been used in this research. X-frog is a biological program which is used to express the idea of branching system. Usually this program is being used in order to simulate the plants life but, it has been used in a different way in this thesis as it is used to became a new approach of designing buildings by starting form a biological object. By making deformations on the biological element for example starting from a tree depending on the available variables exist in that program like the length of the tree which indicates the tall of the building, shape of the stem and its width and many variables that make deformation of the tree shape easier. After finishing deformation and settled on the form, the role of architectural drawings appeared by depending on the third category of programs.

In the third category, Rhino Ceros and 3ds Max is architectural programs which

are consider to be 3D parametric programs which are mainly used in 3d drawings to generate forms. In this research these programs have been used to make detailed drawings for the forms generated from X-frog program.

Figure 112: Programs Timeline Source: (The Researcher, 2015)


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Appendix X-frog | Reference Manual Interface

The main X-frog interface is divided up into six sub windows;

1) The Hierarchy Editor 2) The Model view window 3) The Parameter editor 4) Libraries window 5) The Animation editor 6) The Animation Control

1-The hierarchy Editor

The “Hierarchy Editor” is the place where the structure of the model is being created. The structure is set up by linking different components to the model hierarchy.

Title Bar. The title bar of the “Hierarchy Editor”

displays its name and allows the editor to be extracted from the main window.

Show Components radio button. It displays the

icons of the different components in the “Hierarchy Editor”.

Show Primitives radio button. It displays the icons of the primitives that are assigned to the components in the “Hierarchy Editor” window.


Editing Space. In the “Editing Space” the actual model hierarchy is built by creating and linking components. The “Editing Space” provides scroll bars view large hierarchies.

Link pull down menu. Allows to change the type of link connecting two

components. Every component that is linked to the hierarchy will use the link type specified in the pull down menu. If this link type is not available with the current components the default link type of the parent component will be applied. The default link type of the Link pull down menu is multiple. The “Link” pull down menu has the same functionality as the “Set Link Type” command in the “Edit” menu.

Link types. The model hierarchy is set by linking components together. Thus

the structure of a model is determined by which components are connected and how they are connected. The link type specifies the way in which components are connected. There are two different link types in X-frog, the “Simple” link and the “Multiple” link.

Each of the different components in X-frog provides structural information on how to place geometry in space. Every component generates one or more origins where this geometry is created. For example, a “Simple” component generates only one origin and a ”Tree” component creates several of them used to multiply branches. In every origin it is possible either to create geometry (primitives) or to connect a new component.

Connecting one component to a second with a simple link will connect the new component to the last origin that is generated by the previous component. This means when you connect one “Horn” to a second the new component will be created on top of the first one. Connecting the two components with a “Multiple” link will create the new component in every origin generated by the first component. In the “Horn” example the second “Horn” will be connected to the first like ribs.


The choice between “Simple” and “Multiple” link is not available with every component. The “Simple” component provides only the simple link and there are others, like the “PhiBall” component, that only provide the “Multiple” link. With the two basic link types it is possible to turn the re-use function on or off. As Xfrog models can be very complex – just imagining a big tree with thousands of branches and leafs –the re-use function is being introduced.

ReUse check box. It switches the re-use function of the selected link on and off.

The “ReUse” check box has the same functionality as the “Re-Use Link” command in the “Edit” menu. When using a multiplier component such as the “Horn” in the previous example, a high number of subsequent components (the ribs) may be created. With the re-use function turned on, only one rib is calculated and then copied to the other origins. In this case all ribs look exactly the same. Turning the re-use function on allows to drastically reduce the amount of polygons in the model and, to speed up calculation time.

In some cases it is desirable that the multiplied instances look different. In a tree model, all branches are wanted to look different; it is wanted to scale them according to their location on the trunk etc. In this case it is necessary to turn the re-use function off and allow every instance to have its own parameters.

Copy button. It copies the selected component. The “Copy” button has the same functionality as the “Copy Component” command in the “Edit” menu.

CopyAll button. It Copies the selected component and all subsequent components. The “CopyAll” button has the same functionality as the “Copy Component And Children” command in the “Edit” menu.

Hide button. It Hides the selected component and all subsequent components. The “Hide” button has the same functionality as the “Hide” command in the “Edit” menu.


Components that are hidden in the “Hierarchy Editor” are also removed from the model exported with one of the “Export” or “Export Sequence” functions.

Group button. It combines the selected component and all subsequent components in a group. The “Group” button has the same functionality as the “Group” command in the “Edit” menu.

Delete button. It deletes the selected component. Components can also be

deleted by pressing the “Delete” key. The “Delete” button has the same functionality as the “Delete Component” command in the “Edit” menu.

2- Libraries Window

The “Libraries” window gives access to all constructive elements in Xfrog. It provides two tabs: the “Components” tab and the “Primitives” tab. By switching between these tabs, it has either direct access to all available components or to all available primitives. To create a new component, the component should be dragged from the “Libraries” window into the “Hierarchy Editor”. To assign a new primitive to a component, drag the primitive from the “Libraries” window onto the component.

Xfrog provides on one hand the normal geometrical primitives such as cube,

sphere etc. and, on the other hand it provides components that define how the geometry is structured in space. All geometry is bound to components. This means that when it is

wanted to create just a single sphere, firstly it has to define how the sphere is organized in space. This could be done by linking a component to that model hierarchy and then

assigning the desired primitive to the component. The sphere for example is made by creating a “Simple” component and assigning the “Sphere” primitive to it.


3-Model View Window

In the center of the interface, it is found the “Model View” window. This is the window where the graphical output of X-frog is displayed and where the model could be viewed.

Navigation

The following are the possibilities for interactive navigation in the “Model View”.

Rotation. It can be achieved by holding down the left mouse button and drag to rotate the view. The center of the rotation is the origin of the global coordinate system.

Shift. Hold down the right mouse button and drag to shift the view sideways.

Dolly. Hold down both mouse button and drag to dolly in and out.

Menu Bar. The menu located in the upper part of the “Model View” window provides functions to control how the model is displayed in the “Model View” window. It provides the topics “Shading”, “Display”, “Background” and “Camera”.


Wireframe Displays the triangle mesh of the model as a wireframe. The wireframe can be combined with a shaded display.

Shading Displays the model flat shaded.

Gouraud Displays the model with smooth shading.


Display Menu

Show/Hide Vertices. Switches the display of the vertex points of all primitives on and off. The vertex points are the corner points of the triangles your model consists of.

Show/Hide Normals. Switches the display of the Normals of all surfaces in your model on and off. The Normals are vectors defining which direction the surface will reflect light.

Show/Hide Local Axis. Switches the display of the axis of the local coordinate system of all objects in your model on and off. Every component has its individual coordinate system which is relative to the orientation of the component in the global coordinate system.

Show/Hide World Axis. Switches the display of the axis of the global coordinate system on and off.

Show/Hide Splines. Switches the display of the vector along which point list primitives are multiplied on and off.

Show/Hide Attractors. Switches the display of all “Attractor” primitives in your model on and off.

Show/Hide Textures. Switches the display of all textures used in your model on and off.

Edit Background Color. Opens a color editor window to specify the background color of the “Model View” window.

Camera

Store View. Saves the current view. Recall View. Recalls a previously saved view. Reset View. Resets the view to the parameters specified in the “Camera”. Fit To Window. Dollies the view so that the entire model is displayed in the “Model

View" window. Lock X Axis. Constrains the rotation to the X Axis. This can be useful to prevent

unintentional changes of the interactive camera in other directions than the desired one. The locking function works as a toggle switch.

Lock Y Axis. Constrains the rotation to the Y Axis. The locking function works as a toggle switch.

Lock Z Axis. Constrains the rotation to the Z Axis. The locking function works as a toggle switch.


4- Parameter Editor Window

The “Parameter Editor” window gives access to all parameters of the different components. It is context sensitive and displays always the parameters of the selected component. If no component is selected the window is empty.

Normally the “Parameter Editor” provides four tabs except for the “Simple” component and the “Camera”).

The first one is named according

to the selected component type and contains all parameters that are specific to this component.

The second to fourth tabs are

common to all components. The second tab is called “Basic” and contains basic parameters such as placement in 3D space etc.

The third tab is called “Primitive” and contains all parameters concerning the primitive assigned to the component.

The fourth tab is called

“Material” and contains all parameters concerning color and texture assigned to the component.

Controls The “Parameter Editor” window provides several different controls to specify values.

Text fields

Text fields are used to type in text or numbers. Place the cursor in a text field

and it changes to a text cursor. Type in the value and press the return key to confirm the settings. If not confirmed the settings are not applied.

Sliders

Sliders are used to specify a numeric value. The value can either be set by clicking into the slider field and dragging or by typing them into the text field left from the slider field. The range of the slider is indicated by the two numbers above the slider ends. It can be changed by double clicking one of the numbers. The number turns into a text field allowing you to type in the new value. Pressing the return key confirms the settings and removes the text field.


Double sliders

Double sliders are used to specify a range value. They are used with multiplier components and allow to successively changing the multiplied instances. If for example it is wanted to multiply several boxes with decreasing size, define a scaling factor is used for the first box with the upper slider and a scaling factor for the last box. The intermediate values are interpolated and produce an evenly decreasing size of your boxes.

A mathematical function that is used to calculate the intermediate values could

be assigned. The function can be selected from the pull down menu left from the double slider. The menu offers a number of predefined functions and, also allows specifying the functions by selecting “custom...” from the menu.

Pull Down Menus

Pull down menus are used to

select from a choice of predefined possibilities. Click the menu field to make a list of available options appear. Select the desired option.

Radio Buttons

Radio buttons are used to exclusively switch between several options. Click the

corresponding button to turn the desired option on and all others off.

Graph Editors

Graph editors are used to specify values depending on two variables. They are only used in the “Tree” component where it is necessary to specify a certain value for a specific location.

The X-axis of the graph editor is referring to the length of a branch or trunk and the Y-

axis is referring to the value that is specified. The settings are changed by dragging the points defining the graph.

The graph editor in the “Parameter Editor” window is only for rough editing. Clicking

the “Edit” button left from the graph editor open a separate window where the graph can be edited more precisely.


Here one or more points can be selected by clicking (for multiple selection shift-clicking) them and move them around by dragging them.

Points could be added to the graph by double clicking at the location where it is wanted to insert a point.

Points are deleted by selecting them

and pressing the backspace key. To deselect points click somewhere in the window.

Points can be inserted and removed

by adjusting the “Resolution” slider at the bottom of the window.

Spline Editor

Some components like the “Tree” component provide spline editors for certain parameters. The curvature of a tree’s trunk can be defined by a spline. Toggling the “Spline” option in the “Tree” component’s parameters to “on” brings up a button called “Points”. Clicking this button opens the spline editor window.

The navigation inside the “Spline Editor” is the same like in the “Model View” window: Left mouse-button for rotation, right mouse-button for translation and both mouse-buttons for zooming.

The editing process of the spline is the almost same as in the “Graph Editor”: Points can be selected by clicking them and moved by dragging the selected point. It is possible to select several points at a time by shift-clicking them. New points can be added by double-clicking onto the spline. Points can be deleted by selecting the point(s) to be deleted and then pressing the backspace-button.


In the bottom area of the Spline Editor window are three button labeled “View X”,

“View Y” and “View Z” which allow constraining the view to the corresponding axis.

Material Parameters

The “Material” tab contains all parameters concerning color and texture. Colors and textures can either be inherited from the parent component or they can be assigned explicitly for a component. By default colors and textures are inherited and passed through the whole hierarchy. This is done as long as no other color or texture is defined in a subsequent component.

Name

Indicates the name of the selected component. The name can be changed in the text field.

Color

Provides two radio buttons to switch between color inheritance and local color definition. If “Color” is set to “inherited”, the component will use the color definition made in one of the parent components. If “Color” is set to “set”, several controls to define the color are displayed.

Name

Provides a text field where a name can be specified for the color. This is useful when the model is being exported in order to recognize the color and indicate shaders after importing it into other modeling software.

Alpha Provides a slider to specify the degree of transparency of the component. The

limits of the slider are fixed to the range from 0 to 1. Diffuse

Allows to specify a color for the diffuse part of the light reflected by the component. The color is shown in a preview field. Left from the preview field is an “Edit” button that opens a color editor to specify the color. Ambient

Allows to specify a color for the ambient light that illuminates the component. The color is shown in a preview field. Left from the preview field is an “Edit” button that opens a color editor to specify the color.


Specular Allows to specify a color for the part of the light reflected by the highlights of

the component. The color is shown in a preview field. Left from the preview field is an “Edit” button that opens a color editor to specify the color. Emission

Allows to specify a color for the light emitted by the component. The color is shown in a preview field. Left from the preview field is an “Edit” button that opens a color editor to specify the color.

Texture

Provides two radio buttons to switch between texture inheritance and local texture definition. If “Texture” is set to “inherited”, the component will use the texture defined in one of the parent components. If “Texture” is set to “set”, several controls to assign and control the texture for the component are displayed.

Name Provides a text field where a name can be specified for the texture. This is useful

when the model is being exported in order to recognize the texture after importing it into other modeling software.

FileName

Provides a text field to specify the name of the image which to be assigned as a texture to the selected component. Clicking the “Browse” button left from the text field opens a dialog box where the image file could be selected to be assigned. Xfrog supports PNG files and RGB files that can contain alpha channels. Shift U

Provides a slider to specify a value to shift the texture in direction of the U-axis. Textures have an individual coordinate system with the U-axis and the V-axis referring to the flat image. This allows to easily displace textures independently from the coordinate system of the model. Shift V

Provides a slider to specify a value to shift the texture in direction of the V-axis.

Scale U Provides a slider to specify a value to scale the texture in direction of the U-axis.

Scale V Provides a slider to specify a value to scale the texture in direction of the V-axis.

Mapping

Provides a pull down menu to specify the way in which the texture is applied to the model. In “none” mode the texture is mapped onto the surface of the object and scaled


so that it fits exactly on the surface. In “linear” mode the texture is repeated on the object’s surface as often as it fits onto it. The texture is not scaled. In “reflection” mode the texture is projected onto the object’s surface and scaled to fit onto it. In this mode the texture stays fixed to the environment of the object and is reflected by the object as if it had a mirroring surface. When the object is turned in space the texture does not turn with it but remains in its initial position.

Color Editor

Clicking the “Edit” button in the “Material > Color” section opens the “Color Editor”. The editor provides several controls to define a color.

Clicking into the rainbow color field or into one of the fields containing plain color allows to select a color. The brightness of the selected color can be adjusted with the gradient slider at the right side of the editor window. The selected color is displayed in the preview field at the bottom of the editor window.

A color can be specified by typing either the RGB values or the HSB values into the fields below the rainbow color field. The color that is visible in the preview field can be added to the list of custom colors by clicking the “Add To Custom Colors” button. Clicking the “OK” button assigns the color to your model.


5- Animation Editor Window

The “Animation Editor” window is the place where adding life to the Xfrog models. It is possible to animate nearly every parameter of Xfrog models. The only properties that cannot be animated are material parameters such as colors and textures.

The “Animation Editor” window and the “Animation Control” window are

tightly connected as the “Animation Control” window provides all the controls to edit and view the animation sequence that is built in the “Animation Editor” window.

The “Animation Editor” consists of the timeline and the animation track. The

timeline provides a timeslider (the little black triangle) that can be moved back and forth to view the animation and to access different times. The animation track contains the keyframes of the animation.

The timeline ranges between 0 and 1. This timeframe can be subdivided into a

variable amount of frames. By default the amount is set to 100 frames. To speed up the animation you have to specify a smaller amount whereas a higher amount will slow it down. The amount of frames is set in the “Animation Control” window which is described below.

The amount of frames also influences the number of images or models that are exported when one of the “Export Sequence” functions is being selected in the “File Menu”. A value of 100 frames will produce 100 images or models, while a value of e.g. 50 frames will produce 50 images/models throughout the animation sequence. In both cases the whole animation sequence is exported but with bigger or smaller intervals. The timeline indicates the frames with tickmarks.

The limits of the animation sequence can be changed by moving the startand

end-marks of the timeline. Thus it is possible e.g. to export only a part of the entire sequence.


Left from the animation track are two check-boxes called “Edit” and “Cam”. Checking the “Edit” option makes the track editable, unchecking it prevents editing.

Checking the “Cam” option displays the camera positions that have been keyed, unchecking it, switches to the interactive camera display.

6- Animation Control Window

The “Animation Control” window provides all means that are necessary to control animation like playing the animation, setting keyframes, determining the speed etc.

Keyframe Section

New button Creates a new keyframe at the current position of the timeslider.

Cpy button Duplicates the selected keyframe.

Del button Deletes the selected keyframe.

Cam button Stores the position of the interactive camera in the currently selected keyframe.

Playback Section

Rewind button Moves the timeslider to the beginning of the animation sequence.

Step-back button Moves the timeslider one frame back.


Play-reverse button Plays the animation in reversed order.

Play button Plays the animation.

Step-forward button Moves the timeslider one frame forward.

Fast-forward button Moves the timeslider to the end of the aniamtion sequence.

Time Section

Frm field Displays the number of the frame at the current position of the timeslider. Typing

a number into this field moves the timeslider to the corresponding position. Frms field

Displays the amount of frames the animation sequence contains. The amount of frames determines the speed of the animation. The higher the value the slower and smoother the animation is. This value also determines the number of images or models that are exported when choosing the “Export Sequence” command.

Loop pull-down menu Determines if the animation is played back in a continuous loop which starts

always at the beginning of the animation and plays to the end; if the animation swings continuously back and forth from the beginning to the end and from the end to the beginning; or if the animation is played only once from the beginning to the end.

Time field Displays the time value of the current position of the timeslider. Typing a

number into this field moves the timeslider to the corresponding position. The time value will always be a number between 0 and 1.


Summary Design is the way of building up a possible figurative utopia or metaphor about

life, it is indeed about life and environment is part of life, so that designs should be biological, their forms could be inspired from any biological element, all technical systems could be biological systems, forms could be distinguished by the most important advantages of nature which are growth and adaptation.

Bio design goes further than other biology-inspired approaches to design and fabrication. Unlike bio-mimicry, cradle to cradle, and the popular but frustratingly vague 'green design,' bio-design refers specially to the incorporation of living organisms as essential components, enhancing the function of the finished work. It goes beyond mimicry to integration, dissolving boundaries and synthesizing new hybrid typologies.

Bio-design is a complete integration between 1. Nature as a source of all designs and had already solved all challenges that face designers during the design process so there is no need to search for solutions for that challenges. 2. Science which had a great effect with the new technology used in buildings and the revolution of using new materials and the science of genetics which enable doing modifications in the material behavior to realize the wanted specifications. 3. Creativity which had a great effect in the design process and in the final product like, when depending on nature in the design process that would give the design more flexibility in form as the designs would had the advantages of nature growth and adaptation which would distinguish them than any other design.

Besides that, using computers in different phases of architectural design to reach a complete digital design process is a big dream. After using computers in architecture as a representative tool and just for implementation, they must be used as a design tool in order to create a generative system which helps in architecture designing as they are needed to manage and express the increasing complexity of factors and variables that determine the design process. There must be a synergetic relationship between the human mind and the computer system and such synergy is possible only through the use of algorithmic strategies that ensure a complementary and dialectic relationship between the human to realize, overcome and ultimately surpass their own physical and mental limitation.

By automating parts of the design process, computers make it easier to develop designs through versioning and gradual adjustment. These approaches to designing have been described as morphogenesis.

Studying morphogenesis in biology and architecture as they share some similarities like: (both deal with entities operating in context and both use computational models), the differences in goals, epistemology, knowledge base, methods and institutional organization are significant. Despite the differences and difficulties, direct collaborations between biology and architecture are necessary not only in the narrow context of the present discussion but also because they can help to orient designing towards biologically compatible outcomes. Another, equally exciting outcome of such collaborations will be in further contributions towards creative inspiration.

Depending on computers in the bio design process is called biological morphogenesis as it concerns with studying 1) components of organisms develop and specialize under the influence of contextual conditions such as static and dynamic loads or the availability of sun light. 2) Evaluating and simulating complex physical performances.


الملخص باللغة العربية


م والتجاه المنتج للتصميم. يتم التعرف على نظام هذا التوجه وكيفية عمله والخطوات اإلتجاه التقليدى للتصميالرئيسية المتبعة من أجل التصميم بهذا اإلتجاه. إلقاء الضوء على بعض المفاهيم المختلفة مثل األنظمة المنتجة اللوغاريتمية

مبيوتر ى المختلفة المستخدمة فى كتابة الفكرة لكى يقوم الكواألنظمة البارامترية. هذا باإلضافة الى طرق التعبير اللوغاريتم بفهمها وتطبيقها , كما يتم عرض للنموذج المنتج وفئاته المختلفة وكيفية اإلستفادة منه.

التصميم اللوغاريتمى) حيث يبدأ هذا الفصل بمقدمة تشرح ماهية يأتى هذا الفصل بعنوان (الفصل الثانى:

دامه فى العمارة وأراء بعض العلماء فيه وكيفية توظيفه وامكاناته التى قد تفيد فى مجال العمارة. الكمبيوتر وكيفية استخومعرفة الفرق بينهما ثم )Computation & Computerizationيتم عرض الفرق بين مصطلحين متشابهين وهما (

وأراء الكثير من العلماء والمعماريين فى يتم النتقال لعرض الجدل الواسع من استخدام الكمبيوتر فى العمارة من عدمههذا األمر ومنهم من هو مؤيد ومنهم من هو معارض أو محددا للمجاالت التى قد يستخدم فيها الكمبيوتر فقظ وليس كاستخدام مطلق. يتم شرح لتوجه التصميم المعمارى الذى يعتمد على الكمبيوتر والطرق المختلفة لذلك وخواص تلك

بين التصميم التقليدى والتصميم باستخدام الكمبيوتر. باإلضافةالى عرض لفكرة اللوغاريتمات وكيفية الطرق والفرقكتابتها والتعبير عنها والتصميم اللوغاريتمى ومتطلباته وطرقه المختلفة. هذا باإلضافة للمشكالت اللوغاريتمية وتصنيفها

ت. هذا باإلضافة الى عرض مفصل للبرمجة وطرقها وكيفية حلها بإسلوب علمى وعرض لمختلف طرق حل المشكالالمختلفة وكيفية تحويل الفكرة الى اإلعتماد على بعض اللوغاريتمات واألدوات الرقمية وايضا عرض للغات البرمجة

المختلفة وانواعها حسب التصنيف الموضوع سواء كانت لغة البرمجة مرئية أو نصية.

تشكل الجزء الثانى: التصميم الحيوى وال

ياتى هذا الفصل بعنوان (التصميم الحيوى) حيث يبدأ هذا الفصل بمقدمة عن التصميم الفصل الثالث:المعمارى ومدى الحاجة للتفكير فى الطبيعة والبيئة المحيطة بنا أثناء عملية التصميم ومعرفة مدى تأثير هذا المبنى الجديد

من اجل توفير حياة أفضل للشخص كعامل أساسى وفعال فى عملية على بيئته المحيطة وكيفية اإلستفادة منها وذلكالتصميم مما يفتح المجال لظهور اتجاه ومدخل جديد من مداخل التصميم اال وهو التصميم الحيوى. يتم شرح لبعض

باإلضافة االمفاهيم الخاصة بالمدخل التصميمى الجديد مثل تعريف لعلم األحياء وتعريف للعمارة وكيفية التكامل بينهملكيفية التناظر بين العمارة وعلم األحياء والبحث عن التطور الطبيعى لفكرة اإلستدامة ,باإلضافة لتوضيح الفارق بين التصميم التقليدى والتصميم الحيوى ثم يتم عرض لمعنى التصميم الحيوى واختالفه عن التصميم المحاكى للطبيعة. عرض

كونة لهذا التوجه وماهية هذه العناصر وكيفية تعامل المصمم مع كل منهم باإلضافة الى لكيفية التكامل بين العناصر الم. يتم عرض للمخرجات ونتائج هذا التوجه فى التصميم من خالل عرض مفصل لبعض من األمثلة تحقيق التكامل بينهم

يم.التى توضح هذا التوجه وكيفية الوصول لهذه المبانى من خالل هذا اإلتجاه فى التصم

يأتى هذا الفصل بعنوان (التشكل) حيث يبدأ هذا الفصل بمقدمة عن مجال العمارة وتأثير الفصل الرابع:التكنولوجيا الجديدة فيه ومدى فاعليتها فى العمارة لتنحيها جانبا عن الفكر التقليدى, هذا باإلضافة الى كيفية استغاللها

ل وأنواعه وكيفيته والعوامل المساعدة على ذلك ومدى تأثير التشكل فى واإلستفادة منها. يتم عرض لتعريف معنى التشكالعمارة وعلم األحياء وهذا الذى دفع لظهور مفهوم جديد وهو التشكل الرقمى الذى يعتمد على الكمبيوتر فى عملية التطور

ير منهم باإلضافة الى تأث والتشكيل الخارجى , كما ايضا ظهر مفهوم اخر جديد وهو التشكل الحيوى وخصائص كل مفهوم ذلك على العمارة وكيفية اإلستفادة منه.

الجزء الثالث: التشكل الرقمى الحيوى فى العمارة

حيث يبدأ هذا الفصل بمقدمة عن نشأة (العمارة الرقمية الحيوية) يأتى هذا الفصل بعنوان الفصل الخامس:

لتطور ومن اين جاء ميالد العمارة وماذا أضافت التكنولوجيا العمارة وكيفية تطورها ورؤية بعض المعماريين لهذا االحديثة للعمارة وهل هذا بالفعل يعد اضافة ام ان ذلك ما هو إال استدعاء للماضى. يتم عرض لوجهات نظر مختلفة للتعامل

عمارة م عرض لفكرة المع النبات فى العمارة وايضا عرض إلهم المداخل المختلفة لإلتجاه الرقمى الحيوى فى العمارةز يتالرقمية النباتية وكيفية زرع فكرة هذا اإلتجاه المعمارى. باإلضافة لعرض فكرة التطور التى وضعها احد المعماريين ومحاولة تطبيقها ولكن رقميا باإلضافة لمحاولة تحديد المميزات التى توجد فى األجسام الحية والمراد تطبيقها فى المبنى

ل يأتى بعد ذلك المرحلة التطبيقية والتى تستعرض الفرضية البحثية الخاصة بالرسالة باإلضافة الى تحلي وكيفية تطبيقها ثملمجموعة من األمثلة التى تؤكد تلك الفرضية والتى تدعمها من اجل الوصول للهدف األساسى والرئيسى من البحث ومن

ثم ينتهى الفصل بعرض لملخص كامل لما جاء فى البحث.


الملخص باللغة العربية


م والتجاه المنتج للتصميم. يتم التعرف على نظام هذا التوجه وكيفية عمله والخطوات اإلتجاه التقليدى للتصميالرئيسية المتبعة من أجل التصميم بهذا اإلتجاه. إلقاء الضوء على بعض المفاهيم المختلفة مثل األنظمة المنتجة اللوغاريتمية

مبيوتر ى المختلفة المستخدمة فى كتابة الفكرة لكى يقوم الكواألنظمة البارامترية. هذا باإلضافة الى طرق التعبير اللوغاريتم بفهمها وتطبيقها , كما يتم عرض للنموذج المنتج وفئاته المختلفة وكيفية اإلستفادة منه.

التصميم اللوغاريتمى) حيث يبدأ هذا الفصل بمقدمة تشرح ماهية يأتى هذا الفصل بعنوان (الفصل الثانى:

دامه فى العمارة وأراء بعض العلماء فيه وكيفية توظيفه وامكاناته التى قد تفيد فى مجال العمارة. الكمبيوتر وكيفية استخومعرفة الفرق بينهما ثم )Computation & Computerizationيتم عرض الفرق بين مصطلحين متشابهين وهما (

وأراء الكثير من العلماء والمعماريين فى يتم النتقال لعرض الجدل الواسع من استخدام الكمبيوتر فى العمارة من عدمههذا األمر ومنهم من هو مؤيد ومنهم من هو معارض أو محددا للمجاالت التى قد يستخدم فيها الكمبيوتر فقظ وليس كاستخدام مطلق. يتم شرح لتوجه التصميم المعمارى الذى يعتمد على الكمبيوتر والطرق المختلفة لذلك وخواص تلك

بين التصميم التقليدى والتصميم باستخدام الكمبيوتر. باإلضافةالى عرض لفكرة اللوغاريتمات وكيفية الطرق والفرقكتابتها والتعبير عنها والتصميم اللوغاريتمى ومتطلباته وطرقه المختلفة. هذا باإلضافة للمشكالت اللوغاريتمية وتصنيفها

ت. هذا باإلضافة الى عرض مفصل للبرمجة وطرقها وكيفية حلها بإسلوب علمى وعرض لمختلف طرق حل المشكالالمختلفة وكيفية تحويل الفكرة الى اإلعتماد على بعض اللوغاريتمات واألدوات الرقمية وايضا عرض للغات البرمجة

المختلفة وانواعها حسب التصنيف الموضوع سواء كانت لغة البرمجة مرئية أو نصية.

تشكل الجزء الثانى: التصميم الحيوى وال

ياتى هذا الفصل بعنوان (التصميم الحيوى) حيث يبدأ هذا الفصل بمقدمة عن التصميم الفصل الثالث:المعمارى ومدى الحاجة للتفكير فى الطبيعة والبيئة المحيطة بنا أثناء عملية التصميم ومعرفة مدى تأثير هذا المبنى الجديد

من اجل توفير حياة أفضل للشخص كعامل أساسى وفعال فى عملية على بيئته المحيطة وكيفية اإلستفادة منها وذلكالتصميم مما يفتح المجال لظهور اتجاه ومدخل جديد من مداخل التصميم اال وهو التصميم الحيوى. يتم شرح لبعض

باإلضافة االمفاهيم الخاصة بالمدخل التصميمى الجديد مثل تعريف لعلم األحياء وتعريف للعمارة وكيفية التكامل بينهملكيفية التناظر بين العمارة وعلم األحياء والبحث عن التطور الطبيعى لفكرة اإلستدامة ,باإلضافة لتوضيح الفارق بين التصميم التقليدى والتصميم الحيوى ثم يتم عرض لمعنى التصميم الحيوى واختالفه عن التصميم المحاكى للطبيعة. عرض

كونة لهذا التوجه وماهية هذه العناصر وكيفية تعامل المصمم مع كل منهم باإلضافة الى لكيفية التكامل بين العناصر الم. يتم عرض للمخرجات ونتائج هذا التوجه فى التصميم من خالل عرض مفصل لبعض من األمثلة تحقيق التكامل بينهم

يم.التى توضح هذا التوجه وكيفية الوصول لهذه المبانى من خالل هذا اإلتجاه فى التصم

يأتى هذا الفصل بعنوان (التشكل) حيث يبدأ هذا الفصل بمقدمة عن مجال العمارة وتأثير الفصل الرابع:التكنولوجيا الجديدة فيه ومدى فاعليتها فى العمارة لتنحيها جانبا عن الفكر التقليدى, هذا باإلضافة الى كيفية استغاللها

ل وأنواعه وكيفيته والعوامل المساعدة على ذلك ومدى تأثير التشكل فى واإلستفادة منها. يتم عرض لتعريف معنى التشكالعمارة وعلم األحياء وهذا الذى دفع لظهور مفهوم جديد وهو التشكل الرقمى الذى يعتمد على الكمبيوتر فى عملية التطور

ير منهم باإلضافة الى تأث والتشكيل الخارجى , كما ايضا ظهر مفهوم اخر جديد وهو التشكل الحيوى وخصائص كل مفهوم ذلك على العمارة وكيفية اإلستفادة منه.

الجزء الثالث: التشكل الرقمى الحيوى فى العمارة

حيث يبدأ هذا الفصل بمقدمة عن نشأة (العمارة الرقمية الحيوية) يأتى هذا الفصل بعنوان الفصل الخامس:

لتطور ومن اين جاء ميالد العمارة وماذا أضافت التكنولوجيا العمارة وكيفية تطورها ورؤية بعض المعماريين لهذا االحديثة للعمارة وهل هذا بالفعل يعد اضافة ام ان ذلك ما هو إال استدعاء للماضى. يتم عرض لوجهات نظر مختلفة للتعامل

عمارة م عرض لفكرة المع النبات فى العمارة وايضا عرض إلهم المداخل المختلفة لإلتجاه الرقمى الحيوى فى العمارةز يتالرقمية النباتية وكيفية زرع فكرة هذا اإلتجاه المعمارى. باإلضافة لعرض فكرة التطور التى وضعها احد المعماريين ومحاولة تطبيقها ولكن رقميا باإلضافة لمحاولة تحديد المميزات التى توجد فى األجسام الحية والمراد تطبيقها فى المبنى

ل يأتى بعد ذلك المرحلة التطبيقية والتى تستعرض الفرضية البحثية الخاصة بالرسالة باإلضافة الى تحلي وكيفية تطبيقها ثملمجموعة من األمثلة التى تؤكد تلك الفرضية والتى تدعمها من اجل الوصول للهدف األساسى والرئيسى من البحث ومن

ثم ينتهى الفصل بعرض لملخص كامل لما جاء فى البحث.


ليس ترالكمبيونظرنا الى التشكل فى العمارة فانه يفهم على انه مجموعة من الطرق التى تقوم بتوظيف إذا مولدة إليجاد الشكل وتحوله. اةاظهار العرض ولكن كأد اةكأد

بالنظر الى علم األحياء والعمارة فانه يوجد بعض المتشابهات والقوى الكامنة بها فإن هذا يدفع الى عملية ج كلى بينهم فاذا فرضنا ان هذا اإلندماج قد يحدث بينهما فى مجال البرمجيات اعتمادا على ما بينهما من متشابهات اندما

Mayaكبرنامج ممثل للبرمجيات الحيوية وبرامج ( )X-Frogمثال عند الفرض بان اإلندماج الذى قد يحدث بين برنامج (– Rhino Ceros( ية وذلك يسهل فى عملية انتاج أشكال ومكونات تحاكى عملية النمو للبرمجيات المعمار ةمج ممثلاكبر

العضوى فى النباتات مثال من أجل تحقيق عملية النمو التكرار الذاتى والقابلية للتطور.

عندما يحدث هذا اإلندماج سيؤدى الى ظهور توجه جديد فى التصميم المعمارى وهو التصميم الرقمى ية البدء فى عملية التصميم المعمارى اعتمادا على استخدام الكمبيوتر محاكيا خاصية النمو الحيوى والذى يهدف الى كيف

لدى وحدة حيوية باسلوب رقمى وايضا النظام اإلنشائى الخاص به النتاج مجسمات قادرة على التطور وتستطيع تكرار ها من دراستها هندسيا وتفصيلها من أجل توظيف نفسها ونظامها اإلنشائى للوحدة الحيوية ولكن هذه المجسمات بعد ذلك ال بد

معماريا.

باإلعتماد على الكمبيوتر كنظام مولد لعملية التصميم المعمارى بعمل تحليل للنظام اإلنشائى للوحدة الحيوية تغير عن تلجعله هو نفسه النظام اإلنشائى للمبنى بالتناظر. هذا النظام اإلنشائى يعتمد على مجموعة من المتغيرات التى

طريق التحكم فى قيم هذه المتغيرات إلنتاج أجيال من نفس فئة المبنى وهذا ما يطلق عليه (التشكل الرقمى الحيوى فى العمارة) هذا ما يهدف البحث للوصول اليه.

األهداف

برنامج كتابة ال يهدف البحث الى إبراز أهمية استخدام الكمبيوتر كأداة مولدة فى عملية التصميم التى تعتمد على .النصى والمدخل اللوغاريتمى فى التصميم المعمارى

تحقيق اندماج كامل بين علم األحياء والعمارة من أجل إيجاد مدخل التصميم الحيوى. دراسة اإلختالفات بين التشكل الحيوى والتشكل الرقمى واإلندماج بينهما إليجاد مدخل رقمى حيوى للعمارة والذى

دخل اخر حيث يبدأ تصميم المبنى من خالل قاعدة حيوية اعتمادا على القوى الكامنة المشتركة يختلف عن أى مالمتواجدة بين علم األحياء والعمارة والذى بدوره يشجع على اإلندماج بينهما فى البرمجيات إليجاد أو إلنتاج وحدة

لتعامل مع المجسم الحيوى أكثر سهولة مصغرة تمثل البرمجيات الحيوية داخل برنامج معمارى والذى سيجعل من اوالمجسمات التى سيتم انتاجها من خالل هذه الخلية سيتم معالجتها معماريا بداخل نفس البرنامج بدون الحاجة للتنقل

) مع X-Frogبين البرامج الحيوية والبرامج المعمارية ,كمثال على هذا اإلندماج حيث قد يندمج برنامج حيوى مثل ( . )Maya – Rhino Cerosرية مثل(برامج معما

بعد تحليل القاعدة الحيوية فإن النظام اإلنشائى الخاص بها البد أن يدرس جيدا لتحويله لكى يصبح قادرا على أن يكون هو نفسه النظام اإلنشائى الخاص بالمبنى وايجاد أشكال مختلفة من نفس شكل المبنى.

المنهجيةئيسية حيث تبدأ بمقدمة عامة عن البحث باإلضافة لتحديد الغرض من أجزاء رالى ثالث لرسالة اتنقسم

.البحث واألهداف الرئيسية للبحث والفرضيات. هذا باإلضافة الى عرض الهيكل البحثى للرسالة دراسة التصميم المنتج والتصميم اللوغاريتمى الرقمى. -1 ى.ميم الحيوى والتصميم الرقمدراسة التصميم الحيوى ودراسة التشكل ومدى تأثيره فى عملية التص -2دراسة اإلندماج بين العمارة وعلم األحياء اعتمادا على الكمبيوتر إلنتاج نماذج معمارية عن طريق -3

البدء فى التصميم اعتمادا على وحدة حيوية ابتدائية وتطويرها ومحاكاتها ليكتمل توظيفها لتصبح مبنى مثل التطور الحيوى للوحدات الحيوية ولكن رقميا كما يتم تحليل لبعض األمثلة التى تؤكد الفكرة

بإستخدام الكمبيوتر والوصول لنماذج معمارية من خالل تلك المحاكاة.

الجزء األول : التصميم المنتج والتصميم اللوغاريتمى الرقمى

ى الحياة الكمبيوتر ودوره فحيث يبدأ بمقدمة عن أهمية استخدام يأتى هذا الفصل بعنوان (التصميم المنتج)الفصل األول: العملية ودوره البارز فى مجال العمارة سواء كأداة لإلظهار المعمارى للمعطيات الواضحة أو اقحامه كجزء من عملية التصميم المعمارى. يتم شرح مفصل لمعنى التصميم المنتج من خالل طرح عدة وجهات نظر مختلفة لتعريف هذا اإلتجاه

زاته. هذا باإلضافة لعمل مقارنة بينوايضا أهم خواصه وممي


ملخص البحثتعد عملية التصميم هى الطريق الذى يؤدى الى امكانية ابتكار رمز مميز أو استعارة عن الحياة وهو بالفعل يختص بالحياة والبيئة المحيطة هى جزء من الحياة لذلك فإن التصميمات المشروع فى إنشاؤها ال بد أن تصبح لها بعد

تكوين شكلها الخارجى يصبح مستوحى من وحدة حيوية. هذا باإلضافة الى أن األنظمة الميكانيكية التى يعتمد حيوى وعليها المبنى سوف تصبح مدارة بشكل حيوى بيولوجى. هذا باإلضافة الى أن الشكل الخارجى للمبنى يفضل أن يستفيد

مو والتطور وكيفية التكيف مع البيئة المحيطة.بقدر اإلمكان من أهم مميزات الطبيعة اال وهم القابلية للن

بالنظر الى كل ذلك نجد أنه أدى الى ظهور اتجاه متفرد فى التصميم وهو التصميم الحيوى وهذا اإلتجاه يبعد تماما عن أى توجه مستوحى من الحياة والكائنات الحية فى مجال التصميم والتكوين وهو غير تماما اتجاه محاكاة

لحية حيث انه غير غامض مثله وإنما يهدف الى اإلندماج الكامل للكائنات واألعضاء الحية كمكونات رئيسية الكائنات التعزيز وظيفة العمل المنتهى فهو يذهب بعيدا عن المحاكاة وانما يهدف الى التكامل وازالة المحددات والعواقب وتوليف

انماط مختلطة جديدة.

كامل واندماج تام بين (الطبيعة) كمصدر اساسى ومصدر لإللهام لكل يعد التصميم الحيوى هو نتيجة تالتصميمات حيث تعد من أهم عوامل هذا التصميم اإلعتماد الكامل على الطبيعة وذلك حيث أن الطبيعة قد واجهت الكثير

عة اللجوء للطبي من التحديات وقامت بالفعل بحلها لذلك بفضل اعتماد المصممين عند اإلعتماد على هذا التوجه على لإلستفادة من هذه الحلول وعدم الحاجة للتوصل لحلول جديدة.

ثانى العوامل هو(العلوم) المختلفة والتى لها تأثير كبير من حيث التكنولوجيا الجديدة المستخدمة فى المبانى

فى جال من أجل عمل تعديالتوالثورة فى مجال المواد المستخدمة فى المبانى والتوسع فى علوم الجينات التى فتحت الم ماهية المواد وسلوكها وذلك من أجل التوصل للخواص المختلفة المرغوبة فى هذه الموادز

ثالث العوامل المؤثرة فى اإلتجاه الحيوى هو (اإلبداع) والذى له دور كبير فى عملية التصميم والذى يجعل

اعتمادا على أهم مميزات الطبيعة من حيث النمو والتكيف مع عملية التصميم اكثر مرونة فى التصميم الخارجى للمبنى البيئة المحيطة مما يجعل المبانى متميزة بهذه الصفات المتفردة فى الطبيعة فقط.

قد اصبح استخدام الكمبيوتر بأشكال عدة فى عملية التصميم المعمارى من اجل الحصول على عملية تصميم

حلم كبير يراود الكثير من الباحثين والمعماريين. فانه بعد استخدام الكمبيوتر كوسيلة معمارى كاملة باستخدام الكمبيوترللتعبير والتطبيق فقط, فان الهدف حاليا هو جعل الكمبيوتر كأداة للتصميم من أجل ايجاد نظام مولد يساعد فى التصميم

ة. للحدود والمتغيرات التى تحدد العملية التصميميالمعمارى حيث انهم مطالبون باإلدارة والتعبير عن الصعوبة المتزايدة حيث انه ال بد من وجود عالقة تعاونية بين العقل البشرى لإلنسان وأنظمة الكمبيوتر وهذا التعاون من الممكن تحقيقه فقط

درك يمن خالل اللجوء إلستخدام استراتيجيات لوغاريتمية والتى تؤكد على عالقة تكاملية وجدلية بين الشخص حتى والتغلب وتجاوز حدودهم الجسدية والعقلية.

تستطيع أجهزة الكمبيوتر تسهيل عملية التصميم وتطوير التصميمات من خالل جعل أجزاء من عملية التصميم تدار بواسطة الكمبيوتر وذلك من خالل التطوير والتكيف التدريجى وهذه التوجهات فى التصميم يمكن توصيفها

بـ (التشكل).

اسة التشكل فى علوم األحياء والعمارة حيث وجد انهم يحملون بعض الصفات المشتركة فيما بينهم حيث بدران كالهما يتعامل مع مدخالت تدار داخل كم وكالهما يعتمد على استخدام نماذج حسابية كما انه بالفعل يوجد بعض

تنظيمات المؤسسية ولكنه بالرغم من تلك اإلختالفات اإلختالفات فى األهداف ومنطقية النشأة وقواعد المعرفة والطرق والوالصعوبات فان التعاون القوى والمباشر بين علم األحياء والعمارة يعد ضرورة ال غنى عنها ليس فقط على المدى القريب

يرة من هذا ثفى الحاضر ولكنه يمكنه ان يوجه عملية التصميم ناحية النتائج الحيوية . هذا باإلضافة الى أن النتائج الم التعاون سوف يصبح فى مزيد من المساهمات من أجل مصدراإللهام اإلبداعى.

يطلق على اإلعتماد على أجهزة الكمبيوتر فى عملية التصميم المعمارى الحيوى اسم التشكل الحيوى حيث

ثل األحمال الثابتة انها تهتم بدراسة مكونات تطورات األعضاء الحية وخاصة التى تحت تأثير الظروف السياقية م والديناميكية أو القابلة للتعرض لضوء الشمس. هذا باإلضافة الى تفييم ومحاكاة العروض الفيزيائية المعقدة.

بسم هللا الرحمن الرحيم

موافقون شرافاإل لجنة

.............................. محمد عبد العال إبراهيم أ.د / المعمارية الهندسة بقسم العمارة أستاذ األسكندرية جامعة - الهندسة كلية

............................. السياري محمد عادل د. سامر المعمارية الهندسة بقسم مدرس

األسكندرية جامعة - الهندسة كلية

جامعة االسكندرية

كلية الهندسة قسم الهندسة المعمارية

التشكل فى العمارة الرقمية الحيوية العمارة الرقمية المعتمدة على الحياة النباتيةدراسة وتطبيق على

مقدمة من

محمد جمعه أحمد محمود للحصول على درجة

الماجستير في العلوم الهندسية

فى

الهندسة المعمارية

موافقون ةالرسال على والحكم المناقشة لجنة ...................... عبدالعال ابراهيم محمد / د.أ

المعمارية الهندسة بقسم العمارة أستاذ األسكندرية جامعة - الهندسة كلية

...................... يحيي مصطفى محمد / د.أ عمارةال بقسم العمارة أستاذ األسكندرية جامعة -فنون الجميلة ال كلية

...................... مصطفى مرسى العربى / د.أ المعمارية الهندسة بقسم العمارة أستاذ األسكندرية جامعة - الهندسة كلية

والبحوث العليا للدراسات الكلية وكيل

...................... مجدى عبد العظيم احمد سليمان .د.أ

االسكندرية جامعة الهندسة كلية

جامعة االسكندرية كلية الهندسة

قسم الهندسة المعمارية

التشكل فى العمارة الرقمية الحيوية العمارة الرقمية المعتمدة على الحياة النباتيةدراسة وتطبيق على

رسالة علمية الدراسات العليامقدمة إلى

جامعة األسكندرية -كلية الهندسة ب

للحصول على درجةاستيفاًء جزئياً

الماجستير في العلوم الهندسية

فى

الهندسة المعمارية

مقدمة من

محمد جمعه أحمد محمود

2015 بريل إ

bio-digital morphogenesis in architecture · mahmoud mohamed gomaa ahmed for the degree of master...

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