INTELLIGENT BUILDING SKINS:
PARAMETRIC-BASED ALGORITHM FOR KINETIC FACADES DESIGN AND DAYLIGHTING PERFORMANCE INTEGRATION
by
Mohamed Mansour El Sheikh
A Thesis Presented to the
FACULTY OF THE USC SCHOOL OF ARCHITECTURE
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF BUILDING SCIENCE
May 2011
Copyright 2011 Mohamed Mansour El Sheikh ii
ACKNOWLEDGMENTS
I would like to express my deep and sincere gratitude to Karen Kensek. Her wide knowledge and her logical way of thinking have been of great value to me from the very early stage. Her understanding, encouraging and personal guidance has provided a good basis for this thesis. She has always provided me with the materials required for the success of my studies, as well as introducing me to new ideas and technology. Karen, you have been a great and generous mentor, whom I hope to get another chance to work with in the future.
I gratefully acknowledge Dr. David Gerber for his advice, supervision, and crucial contributions, which have made him a backbone of this thesis. His involvement and originality have triggered and nourished my intellectual maturity, which I will benefit from for a long time to come. With his enthusiasm and inspiration, and his ability to explain things clearly and simply, he contributed to the success of this thesis. David, I am grateful in every possible way and hope to keep up our collaboration in the future.
My special acknowledgements go to the person who inspired me to explore this field, Nathan Miller. He introduced me to parametric design in one of his classes, in which I had the chance to discover my passion about it. Nathan’s great work in parametric design has influenced my approach to problem solving, especially in my thesis work. I have also benefited from his continuous advice, guidance, and critical comments. I am indebted to him more than he knows.
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I warmly thank Professor Marc Schiler, a role model and gracious person, for his valuable advice and friendly help. His interesting explorations and extensive discussions around my work have been very helpful for this study. I am proud to record that I had the opportunity to work with such an exceptionally experienced person. Though he is not an official thesis advisor, he served on my thesis with true passion, sincerity, and kindness. Marc, words fail to express my appreciation to you.
I owe a special acknowledgment to Greg Otto, who was a gracious mentor at the early stages of this thesis. I am thankful that in the midst of all his activities, he provided me with the time and guidance to properly structure my study. His critical feedback in the beginning was crucial to the success of this study. Greg, you have been and will always be an exceptional mentor to me.
I would like to thank Professor Doug Noble for his support and guidance. He supervised my previous research work and has always been a good person for advice. He has always supported me in pursuing my research on building skins, and has provided me with all of the resources required for my success. Doug, thanks for providing me with the good foundation necessary for the success of this study; it has been pleasure working with you.
My parents, brother, and sisters deserve special mention for their inseparable support and prayers. My father, Mansour El Sheikh, is the person who set the foundation for my learning character, showing me the joy of intellectual pursuit ever since I was a child. My mother is the one who sincerely raised me with her caring and gentle love, and has always been a strong iv
supporter of my life path. Rana, Ahmed, and Salma, thanks for being supportive, loving, and caring siblings.
Finally, I would like to express my gratitude to everyone who supported me in bringing this thesis to light.
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TABLE OF CONTENTS
ACKNOWLEDGMENTS ............................................................................................................ ii
LIST OF TABLES ................................................................................................................... viii
LIST OF FIGURES .................................................................................................................... ix
ABSTRACT ........................................................................................................................... xvi
CHAPTER 1 INTRODUCTION ....................................................................................................1
1.1. BACKGROUND ........................................................................................................................ 2
1.2. RESEARCH STATEMENT............................................................................................................ 12
1.3. GOALS AND OBJECTIVE ............................................................................................................ 14
1.3.1 ILLUMINANCE ................................................................................................................ 15
1.3.2 LUMINOUS DISTRIBUTION ................................................................................................ 15
1.3.3 LIGHT PENETRATION ....................................................................................................... 16
1.4. STRUCTURE AND METHOD ....................................................................................................... 16
1.4.1 INVESTIGATION .............................................................................................................. 17
1.4.2 PROCESSING LOGIC......................................................................................................... 18
1.4.3 DOCUMENTATION .......................................................................................................... 20
1.4.4 SIMULATION METHOD .................................................................................................... 21
1.5. CONCLUSION ........................................................................................................................ 24
CHAPTER 2 INTELLIGENT SKINS ............................................................................................. 26
2.1. OVERVIEW ........................................................................................................................... 27
2.2. INTELLIGENCE IN ARCHITECTURE ................................................................................................ 27
2.3. SKIN AS ENVIRONMENTAL FILTER ............................................................................................... 34
2.4. INTELLIGENT KINETICS AND DAYLIGHTING PERFORMANCE ................................................................ 39
2.5. TYPOLOGY OF KINETICS IN ARCHITECTURE .................................................................................... 42
2.6. HUMAN INTERACTION AND CONTROLS ....................................................................................... 47
2.7. MODELING INTELLIGENT KINETICS ............................................................................................. 48
CHAPTER 3 DYNAMIC DAYLIGHTING ..................................................................................... 52
3.1. INTRODUCTION ..................................................................................................................... 53
3.2. DAYLIGHT REWARDS .............................................................................................................. 55
3.2.1 HUMAN HEALTH AND PRODUCTIVITY ................................................................................... 55
3.2.2 INDIVIDUAL OUTCOMES ................................................................................................... 57
3.2.3 ENERGY USAGE ............................................................................................................. 59
3.3. DAYLIGHT FUNDAMENTALS ..................................................................................................... 61
3.3.1 SOURCE OF LIGHT ........................................................................................................... 61
3.3.2 PROPERTIES OF DAYLIGHT ................................................................................................ 63
3.3.3 FORM AND ORIENTATION ................................................................................................. 65
3.3.4 INTERNAL FACTORS IMPACT .............................................................................................. 67 vi
3.4. PERFORMANCE INDICATORS ..................................................................................................... 68
3.4.1 PREVIOUS WORK ........................................................................................................... 68
3.4.2 ILLUMINANCE ................................................................................................................ 70
3.4.3 LUMINOUS DISTRIBUTION ................................................................................................ 71
3.4.4 DEPTH OF LIGHT PENETRATION ......................................................................................... 73
3.4.5 EVALUATION CRITERIA ..................................................................................................... 74
3.5. DAYLIGHT-DEFLECTION TECHNIQUE ........................................................................................... 76
3.5.1 EVOLUTION OF LIGHT DEFLECTION ..................................................................................... 76
3.5.2 CONCEPT OF DAYLIGHT DEFLECTION ................................................................................... 77
3.5.3 DAYLIGHT HARVESTING USING LIGHT-DEFLECTORS ................................................................ 77
CHAPTER 4 INTELLIGENT SKIN DESIGN TOOL ......................................................................... 82
4.1. INTRODUCTION ..................................................................................................................... 83
4.2. CONCEPTUAL IDEA ................................................................................................................. 85
4.3. DESIGN TOOL DOCUMENTATION ............................................................................................... 89
4.3.1 SKIN SYSTEM ................................................................................................................ 89
4.3.2 DIVA COMPONENT ........................................................................................................ 91
4.3.3 ILLUMINANCE VALUES ..................................................................................................... 91
4.3.4 EVALUATION AND PERFORMANCE CRITERIA.......................................................................... 92
CHAPTER 5 DAYLIGHTING SIMULATION METHOD ............................................................... 104
5.1. OVERVIEW ......................................................................................................................... 105
5.2. SIMULATION CONDITIONS ..................................................................................................... 106
5.2.1 LOCATION, DATE & TIME ............................................................................................... 106
5.2.2 SPACE DIMENSIONS & MATERIALS ................................................................................... 107
5.2.3 RADIANCE SETTINGS ..................................................................................................... 109
5.3. SIMULATION METHOD .......................................................................................................... 111
5.4. UNDERSTANDING SIMULATION RESULTS ................................................................................... 119
5.5. VISUALIZATION OF SIMULATED SCHEMES .................................................................................. 122
CHAPTER 6 SIMULATION ANALYSIS..................................................................................... 124
6.1. DATA ANALYSIS METHOD ...................................................................................................... 126
6.1.1 DIAGRAMS AND CHARTS ................................................................................................ 126
6.1.2 KINETIC SCENARIO COMPILATION METHOD ......................................................................... 128
6.2. SELECT CASE ANALYSIS UNDER CLEAR SKY ................................................................................... 129
6.2.1 LIGHTSHELF AND HORIZONTAL LOUVERS............................................................................. 130
6.2.2 SHADING CONFIGURATION 35: AND 55: ........................................................................... 134
6.2.3 COMBINED CONFIGURATION 24: AND 156: ...................................................................... 135
6.2.4 COMBINED CONFIGURATION 26: AND 163: ...................................................................... 138
6.3. OVERCAST SKY CONDITION DISCUSSION ................................................................................... 140
6.4. KINETIC SCENARIO FOR ACTUATION PATTERN ............................................................................ 144
6.5. ANALYSIS CONCLUSION ......................................................................................................... 146
CHAPTER 7 CONCLUSION AND FUTURE WORK .................................................................... 149
7.1. CONCLUSION ...................................................................................................................... 150
7.1.1 SCOPE AND LIMITATIONS ........................................................................................ 155 vii
7.2. FUTURE WORK ................................................................................................................ 158
7.2.1 OCCUPANTS’ BEHAVIOR .......................................................................................... 158
7.2.2 GLARE REMEDIATION .............................................................................................. 160
7.2.3 HEAT GAIN AND THERMAL COMFORT ...................................................................... 160
7.2.4 SKIN GEOMETRY ...................................................................................................... 160
7.2.5 SURROUNDING URBAN CONTEXT ............................................................................ 161
7.3. SUMMARY ......................................................................................................................... 162
BIBLIOGRAPHY ................................................................................................................... 165
APPENDIX A: ILLUMINANCE NODE POINT RESULTS ............................................................. 172
APPENDIX B: RESULTS FOR CHART PLOTTING ...................................................................... 250
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LIST OF TABLES
TABLE 6-1: PERFORMANCE PERCENTAGE TABLE .................................................................................................. 147
TABLE 10-1: GLAZING ONLY CHART VALUES ....................................................................................................... 250
TABLE 10-2: LIGHTSHELF CHART VALUES........................................................................................................... 250
TABLE 10-3: HORIZONTAL LOUVERS CHART VALUES............................................................................................. 250
TABLE 10-4: SHADING 0° AND 45° CHART VALUES.............................................................................................. 251
TABLE 10-5: SHADING 10° AND 45° CHART VALUES ............................................................................................ 251
TABLE 10-6: SHADING 35° AND 55° CHART VALUES ............................................................................................ 251
TABLE 10-1: HARVESTING 145° AND 160° CHART VALUES ................................................................................... 251
TABLE 10-7: HARVESTING 153° AND 153° CHART VALUES ................................................................................... 252
TABLE 10-8: COMBINED 24° AND 156° CHART VALUES ....................................................................................... 252
TABLE 10-9: COMBINED 26° AND 163° CHART VALUES ....................................................................................... 252
TABLE 10-10: COMBINED 55° AND 168° CHART VALUES ..................................................................................... 252
TABLE 10-11: COMBINED 10° AND 170° CHART VALUES ..................................................................................... 253
TABLE 10-12: TOP-LOWER SPLIT 162° AND 28° CHART VALUES............................................................................. 253
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LIST OF FIGURES
FIGURE 1-1: CURTAIN WALLS ............................................................................................................................ 2
FIGURE 1-2: ELECTRICITY USE IN USA.................................................................................................................. 4
FIGURE 1-3: DAYLIT ZONE ................................................................................................................................ 6
FIGURE 1-4: FLARE FAÇAD ............................................................................................................................... 8
FIGURE 1-5: INDEPENDENT TILT ANGLES ............................................................................................................. 14
FIGURE 1-6: SYSTEM LOGIC ............................................................................................................................. 19
FIGURE 1-7: INDEPENDENT ACTUATION .............................................................................................................. 23
FIGURE 2-1: INTELLIGENT BUILDING FEATURES AND HUMAN INTELLIGENCE ................................................................ 28
FIGURE 2-2: INTELLIGENT PROCESS ................................................................................................................... 32
FIGURE 2-3: QUALITIES OF BUILDING INTELLIGENCE ............................................................................................... 32
FIGURE 2-4: EGYPTIAN MASHRABIYYA ............................................................................................................... 35
FIGURE 2-5: BRISE SOLEIL ............................................................................................................................... 37
FIGURE 2-6: KINETIC TYPOLOGY ....................................................................................................................... 43
FIGURE 2-6: CONTINUED ............................................................................................................................... 44
FIGURE 2-6: CONTINUED ............................................................................................................................... 45
FIGURE 2-6: CONTINUED ............................................................................................................................... 46
FIGURE 3 -1: ELECTROMAGNETIC SPECTRUM ....................................................................................................... 54
FIGURE 3-2: QUALITIES OF LIGHTING ................................................................................................................. 58
FIGURE 3-3: INDIVIDUAL OUTCOME .................................................................................................................. 59
FIGURE 3-4: ENERGY USAGE IN OFFICES ............................................................................................................. 61
FIGURE 3-5: ATMOSPHERE LAYERS .................................................................................................................... 62
FIGURE 3-6: DAYLIGHTING CHARACTERISTICS ...................................................................................................... 64
FIGURE 3-7: BUILDING FORM AND ORIENTATION .................................................................................................. 66 x
FIGURE 3-8: SUN PATH DIAGRAM ..................................................................................................................... 67
FIGURE 3-9: IES LIGHTING HANDBOOK ILLUMINATION .......................................................................................... 71
FIGURE 3-10: ILLUMINANCE DISTRIBUTION ......................................................................................................... 72
FIGURE 3-11: ILLUMINANCE-DEPTH RELATIONSHIP ............................................................................................... 73
FIGURE 3-12: INTERPRETATION OF INDICATORS ................................................................................................... 75
FIGURE 3-13: SIMPLE LIGHT DEFLECTION ........................................................................................................... 76
FIGURE 3-14: COMBINED CONFIGURATION ......................................................................................................... 79
FIGURE 3-15: ANGLES CALCULATION ................................................................................................................. 80
FIGURE 4-1: SYSTEM LOGIC ............................................................................................................................. 86
FIGURE 4-2: SPACE DIMENSION ........................................................................................................................ 87
FIGURE 4-3: LOUVERS DEFINITION..................................................................................................................... 88
FIGURE 4-4: INDEPENDENT SPLIT SYSTEM ............................................................................................................ 88
FIGURE 4-5: INDEPENDENT LOUVER ACTUATION ................................................................................................... 90
FIGURE 4-6: ILLUMINANCE SCALE ..................................................................................................................... 90
FIGURE 4-7: DIVA COMPONENT SECTION .......................................................................................................... 93
FIGURE 4-8: VALUE ADJUSTMENT ..................................................................................................................... 94
FIGURE 4-9: ILLUMINANCE VALUES ADJUSTMENT .................................................................................................. 97
FIGURE 4-10: CALCULATION POINTS EXTRACTION ................................................................................................. 98
FIGURE 4-11: ILLUMINANCE EVALUATION RESULT ................................................................................................. 99
FIGURE 4-12: LUMINOUS DISTRIBUTION EVALUATION CRITERIA .............................................................................. 100
FIGURE 4-13: GENETIC ALGORITHM FITNESS VALUE ............................................................................................. 101
FIGURE 5-1: SPACE DIMENSIONS .................................................................................................................... 107
FIGURE 5-2: MODELED SPACE ....................................................................................................................... 108
FIGURE 5-3: MATERIALS SELECTION................................................................................................................. 109 xi
FIGURE 5-4: SIMULATION PARAMETERS ............................................................................................................ 110
FIGURE 5-5: RADIANCE PARAMETERS ............................................................................................................... 111
FIGURE 5-6: REDIRECTED ANGLE FOR SINGLE CONFIGURATION ............................................................................... 112
FIGURE 5-7: REDIRECTED ANGLE FOR COMBINED CONFIGURATION .......................................................................... 113
FIGURE 5-8: REVISED ANGLES DIAGRAM ........................................................................................................... 114
FIGURE 5-9: LOUVER CONFIGURATION ............................................................................................................. 114
FIGURE 5-10: SEMI-CLOSED CONDITION ........................................................................................................... 115
FIGURE 5-11: OPTIMAL TILT ANGLES ............................................................................................................... 116
FIGURE 5-12: SIMULATION CASES................................................................................................................... 118
FIGURE 5-13: VISUAL PRESENTATION OF TILT ANGLES .......................................................................................... 119
FIGURE 5-14: ILLUMINANCE NODES RESULTS SAMPLE .......................................................................................... 120
FIGURE 5-15: FRONT VIEW OF SIMULATED SCHEMES ........................................................................................... 122
FIGURE 5-16: PERSPECTIVE VIEW OF SIMULATED SCHEMES ................................................................................... 123
FIGURE 6-1: INDEPENDENT TILT-ANGLE SYSTEM ................................................................................................. 125
FIGURE 6-2: CHART VALUES SELECTION SAMPLE ................................................................................................. 127
FIGURE 6-3: CHART SAMPLE .......................................................................................................................... 128
FIGURE 6-4: LIGHTSHELF ILLUMINANCE RESULTS ................................................................................................. 131
FIGURE 6-5: ZOOMED LIGHTSHELF ILLUMINANCE RESULTS..................................................................................... 131
FIGURE 6-6: ZOOMED HORIZONTAL LOUVERS ILLUMINANCE RESULTS ....................................................................... 133
FIGURE 6-7: HORIZONTAL LOUVERS ILLUMINANCE RESULTS ................................................................................... 133
FIGURE 6-8: SHADING CONFIGURATION ILLUMINANCE RESULTS .............................................................................. 135
FIGURE 6-9: COMBINED CONFIGURATION ILLUMINANCE RESULTS ........................................................................... 136
FIGURE 6-10: ZOOMED COMBINED CONFIGURATION ILLUMINANCE RESULTS ............................................................. 137
FIGURE 6-11: COMBINED CONFIGURATION ILLUMINANCE RESULTS ......................................................................... 139 xii
FIGURE 6-12: ZOOMED COMBINED CONFIGURATION ILLUMINANCE RESULTS ............................................................. 140
FIGURE 6-13: HARVESTING CONFIGURATION ILLUMINANCE RESULTS ....................................................................... 141
FIGURE 6-14: COMBINED CONFIGURATION ILLUMINANCE RESULTS ......................................................................... 142
FIGURE 6-15: COMBINED-SPLIT CONFIGURATION ILLUMINANCE RESULTS .................................................................. 144
FIGURE 6-16: COMPILED SCENARIO FOR CLEAR SKY ............................................................................................. 145
FIGURE 6-17: COMPILED SCENARIO FOR OVERCAST SKY ........................................................................................ 146
FIGURE 7-1: STATIC VERSUS KINETIC ................................................................................................................ 155
FIGURE 7-2: ARCHITECTURE FOR HUMAN BEHAVIOR DETECTION SYSTEM .................................................................. 159
FIGURE 7-3: ALGORITHM LOGIC FOR FUTURE WORK ............................................................................................ 162
FIGURE 9-1: GLAZING ONLY RESULTS ............................................................................................................... 172
FIGURE 9-2: GLAZING ONLY RESULTS ............................................................................................................... 173
FIGURE 9-3: GLAZING ONLY RESULTS ............................................................................................................... 174
FIGURE 9-4: GLAZING ONLY RESULTS ............................................................................................................... 175
FIGURE 9-5: GLAZING ONLY RESULTS ............................................................................................................... 176
FIGURE 9-6: GLAZING ONLY RESULTS ............................................................................................................... 177
FIGURE 9-7: LIGHTSHELF RESULTS ................................................................................................................... 178
FIGURE 9-8: LIGHTSHELF RESULTS ................................................................................................................... 179
FIGURE 9-9: LIGHTSHELF RESULTS ................................................................................................................... 180
FIGURE 9-10: LIGHTSHELF RESULTS ................................................................................................................. 181
FIGURE 9-11: LIGHTSHELF RESULTS ................................................................................................................. 182
FIGURE 9-12: LIGHTSHELF RESULTS ................................................................................................................. 183
FIGURE 9-13: HORIZONTAL LOUVERS RESULTS ................................................................................................... 184
FIGURE 9-14: HORIZONTAL LOUVERS RESULTS ................................................................................................... 185
FIGURE 9-15: HORIZONTAL LOUVERS RESULTS ................................................................................................... 186 xiii
FIGURE 9-16: HORIZONTAL LOUVERS RESULTS ................................................................................................... 187
FIGURE 9-17: HORIZONTAL LOUVERS RESULTS ................................................................................................... 188
FIGURE 9-18: HORIZONTAL LOUVERS RESULTS ................................................................................................... 189
FIGURE 9-19: SHADING 0° AND 45° RESULTS .................................................................................................... 190
FIGURE 9-20: SHADING 0° AND 45° RESULTS .................................................................................................... 191
FIGURE 9-21: SHADING 0° AND 45° RESULTS .................................................................................................... 192
FIGURE 9-22: SHADING 0° AND 45° RESULTS .................................................................................................... 193
FIGURE 9-23: SHADING 0° AND 45° RESULTS .................................................................................................... 194
FIGURE 9-24: SHADING 0° AND 45° RESULTS .................................................................................................... 195
FIGURE 9-25: SHADING 10° AND 45° RESULTS .................................................................................................. 196
FIGURE 9-26: SHADING 10° AND 45° RESULTS .................................................................................................. 197
FIGURE 9-27: SHADING 10° AND 45° RESULTS .................................................................................................. 198
FIGURE 9-28: SHADING 10° AND 45° RESULTS .................................................................................................. 199
FIGURE 9-29: SHADING 10° AND 45° RESULTS .................................................................................................. 200
FIGURE 9-30: SHADING 10° AND 45° RESULTS .................................................................................................. 201
FIGURE 9-31: SHADING 35° AND 55° RESULTS .................................................................................................. 202
FIGURE 9-32: SHADING 35° AND 55° RESULTS .................................................................................................. 203
FIGURE 9-33: SHADING 35° AND 55° RESULTS .................................................................................................. 204
FIGURE 9-34: SHADING 35° AND 55° RESULTS .................................................................................................. 205
FIGURE 9-35: SHADING 35° AND 55° RESULTS .................................................................................................. 206
FIGURE 9-36: SHADING 35° AND 55° RESULTS .................................................................................................. 207
FIGURE 9-37: HARVESTING 145° AND 160° RESULTS .......................................................................................... 208
FIGURE 9-38: HARVESTING 145° AND 160° RESULTS .......................................................................................... 209
FIGURE 9-39: HARVESTING 145° AND 160° RESULTS .......................................................................................... 210 xiv
FIGURE 9-40: HARVESTING 145° AND 160° RESULTS .......................................................................................... 211
FIGURE 9-41: HARVESTING 145° AND 160° RESULTS .......................................................................................... 212
FIGURE 9-42: HARVESTING 145° AND 160° RESULTS .......................................................................................... 213
FIGURE 9-43: HARVESTING 153° AND 153° RESULTS .......................................................................................... 214
FIGURE 9-44: HARVESTING 153° AND 153° RESULTS .......................................................................................... 215
FIGURE 9-45: HARVESTING 153° AND 153° RESULTS .......................................................................................... 216
FIGURE 9-46: HARVESTING 153° AND 153° RESULTS .......................................................................................... 217
FIGURE 9-47: HARVESTING 153° AND 153° RESULTS .......................................................................................... 218
FIGURE 9-48: HARVESTING 153° AND 153° RESULTS .......................................................................................... 219
FIGURE 9-48: COMBINED 10° AND 170° RESULTS .............................................................................................. 220
FIGURE 9-49: COMBINED 10° AND 170° RESULTS .............................................................................................. 221
FIGURE 9-50: COMBINED 10° AND 170° RESULTS .............................................................................................. 222
FIGURE 9-51: COMBINED 10° AND 170° RESULTS .............................................................................................. 223
FIGURE 9-52: COMBINED 10° AND 170° RESULTS .............................................................................................. 224
FIGURE 9-53: COMBINED 10° AND 170° RESULTS .............................................................................................. 225
FIGURE 9-54: COMBINED 24° AND 156° RESULTS .............................................................................................. 226
FIGURE 9-55: COMBINED 24° AND 156° RESULTS .............................................................................................. 227
FIGURE 9-56: COMBINED 24° AND 156° RESULTS .............................................................................................. 228
FIGURE 9-57: COMBINED 24° AND 156° RESULTS .............................................................................................. 229
FIGURE 9-58: COMBINED 24° AND 156° RESULTS .............................................................................................. 230
FIGURE 9-59: COMBINED 24° AND 156° RESULTS .............................................................................................. 231
FIGURE 9-60: COMBINED 26° AND 163° RESULTS .............................................................................................. 232
FIGURE 9-61: COMBINED 26° AND 163° RESULTS .............................................................................................. 233
FIGURE 9-62: COMBINED 26° AND 163° RESULTS .............................................................................................. 234 xv
FIGURE 9-63: COMBINED 26° AND 163° RESULTS .............................................................................................. 235
FIGURE 9-64: COMBINED 26° AND 163° RESULTS .............................................................................................. 236
FIGURE 9-65: COMBINED 26° AND 163° RESULTS .............................................................................................. 237
FIGURE 9-66: COMBINED 55° AND 168° RESULTS .............................................................................................. 238
FIGURE 9-67: COMBINED 55° AND 168° RESULTS .............................................................................................. 239
FIGURE 9-68: COMBINED 55° AND 168° RESULTS .............................................................................................. 240
FIGURE 9-69: COMBINED 55° AND 168° RESULTS .............................................................................................. 241
FIGURE 9-70: COMBINED 55° AND 168° RESULTS .............................................................................................. 242
FIGURE 9-71: COMBINED 55° AND 168° RESULTS .............................................................................................. 243
FIGURE 9-72: TOP-LOWER SPLIT 162° AND 28° RESULTS ..................................................................................... 244
FIGURE 9-73: TOP-LOWER SPLIT 162° AND 28° RESULTS ..................................................................................... 245
FIGURE 9-74: TOP-LOWER SPLIT 162° AND 28° RESULTS ..................................................................................... 246
FIGURE 9-75: TOP-LOWER SPLIT 162° AND 28° RESULTS ..................................................................................... 247
FIGURE 9-76: TOP-LOWER SPLIT 162° AND 28° RESULTS ..................................................................................... 248
FIGURE 9-77: TOP-LOWER SPLIT 162° AND 28° RESULTS ..................................................................................... 249
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ABSTRACT
A high integration of design and research between architects, computational designers, and consultants is important to achieve innovation and efficiency. Communicating to the designer the importance of integrating performance-based approaches in the early design stage and their impact on the design, may shift the logic of executing an architectural project. The integration of daylighting into the design phase, through design tools and computation, results in the improved performance of daylight harvesting and therefore tackles issues of human comfort and energy efficiency. One example of performance-based integration is the design, simulation, and validation of intelligent features in building skin design and its impact on daylighting performance.
This thesis presents the design of an algorithm and parametric process developed in Grasshopper, a plugin for Rhino 3D, using DIVA for daylighting simulation. The main objective of the process and algorithm is to evaluate the performance of an intelligent façade, composed of a series of kinetic louvers that actuate in response to dynamic daylighting, and the incorporation of occupants’ preferences. Within the framework of this study, Grasshopper as a parametric computational tool allows the integration of Rhino, the design space, and DIVA, the dynamic daylighting tool, into a single process. The parametric tool extracts the designed geometry from the modeling space and inputs it into the DIVA component to be tested for illumination performance, luminous distribution, and daylight penetration depth inside an office space.
xvii
The thesis presents the initial experiment, in which the external skin actuates to optimize daylight-deflection, maintaining a desirable luminous indoor environment. In the experiment, the louvers rotate using the concept of independent tilt-angle, where every other louver has the same tilt angle; they could be in a harvesting, shading, or a combined configuration. When skin configuration changes, due to louver actuation, the algorithm detects the alteration and instantly reflects it onto a calculation grid inside the space. This allows the designer to run numerous iterations during the design stage and select the best possible one based on pre-defined criteria.
A genetic algorithm has been incorporated into the definition to enable a search for the best skin configuration at specific dates and times or under different sky conditions. The genetic algorithm works on finding an optimal – although not necessarily the best – solution under certain parameters and conditions. These parameters could range from users’ desired illumination levels, to externally-reflected daylighting components. Changes in any of these parameters trigger the system to run and find an optimal configuration for the skin to maintain the desired luminous environment.
In this study, one actuation parameter and three performance indicators for daylighting are defined. However, the proposed design tool is extensible; it is open to accepting additional parameters and performance indicators, which makes it more complex for better performance assessment. As a future development, the geometry of the skin panels will be considered as a varying parameter. 1
1. CHAPTER 1 INTRODUCTION
This research presents an investigation into using intelligent light-deflection techniques to optimize daylighting in office buildings. In this chapter, the background of the proposed topic, the research argument, and the objectives of the study are presented, along with insight into the methodology and intended deliverable2
1.1. BACKGROUND
Figure 1-1: Curtain Walls – The left image shows one of the world’s first curtain walls in England, Oriel Chambers. The right image shows a building by the same architect, which also has a curtain wall system, built two years later. At this time, the amount of glazing used was large compared to adjacent buildings in the area. The architect’s goal was to allow more daylight penetration into the space, as a means of energy-saving.1
In 1864, Peter Ellis designed Oriel Chambers in Liverpool2, England, one of the world’s earliest buildings with metal-framed glass curtain walls. Peter was considered a substantial user of glass facades. His design intent was not aesthetic, but had more of an emphasis on energy efficiency.
1 “Curtain wall - Wikipedia, the free encyclopedia.”
2 “Liverpool Architecture.” 3
The penetration of daylighting deeply into the space, reducing lighting costs, was the main objective for using curtain wall systems. As time passed, architects started incorporating more
glass into their facades, resulting in high levels of illumination inside the spaces. The use of larger amounts of glazing became more common, which made architects worried about their façade performance, and they started looking at the façade as an important filtering layer to the indoor environment.
In the United States, lighting accounts for almost 20-25%3 of total electrical energy use, and in the commercial sector accounts for 37%4 (Figure 1-2). Electric lighting also has an indirect effect on cooling loads in spaces; as a rule of thumb, each unit of electric light requires an additional one-half unit of electricity for space conditioning.5 Improvements in the lighting design profession increased the efficiency of lighting, by utilizing less electrical lighting and exploiting the available natural light. The impact of using natural light is significant not only in terms of energy usage, but also on employees’ productivity and health6.
Use of daylight is important not only in offices, but also in most architectural projects, including retail spaces7. In a comparative study by Southern California Edison of a large multinational
3 Ander, Daylighting Performance and Design, 2.
4 Ibid.
5 Ibid.
6 Dasgupta, The Impact of Windows on Mood and Performance of Judgmental Tasks.
7 Ander, Daylighting Performance and Design, 31. 4
retail organization, an approximate 26%8 increase in sales has been noticed in a store with skylights, relative to similar stores with no skylights.
Figure 1-2: Electricity Use in USA – breakdown of electricity consumption in the commercial building sector.9
The use of glass in office buildings has become important in the profession for transparency, visual, and daylighting purposes. Although useful for allowing light into buildings, untreated windows allow more daylight into a space than required, resulting in visual problems, such as over-abundance of light in some areas, not enough in others, and glare. Typically, the daylight depth in a room with untreated openings is about one-and-a-half times the distance from the window head to the floor (Figure 1-3). A typical window head is at 2.20m, which results in a 3.30m room depth of daylight area. Using light deflection techniques, such as light shelves, can
8 Ibid.
9 Ibid., 2. 5
extend the ratio up to twice that height, resulting in a daylit zone of 4.40m depth.10 This ratio shows the limitation of daylight penetration, which entails the use of electric lighting in many indoor spaces, leading to greater electrical energy consumption, and greater heat from light fixtures, in addition to that from sunlight. This is still a major balancing act in window design: daylight harvesting can help save energy through reduced use of electricity to run lights, but the heat gain might be undesired. As mentioned previously, light shelves are a good solution for deep light penetration up to twice the window header height11. The principle behind this idea is light-deflection, in which light is bounced off the upper surface of a shelf and deflected deeply into the back of the space. This technology opened new venues for the advancement of daylighting performance inside spaces, especially in office buildings. Amongst the technologies that allow better daylighting efficiency, redirecting light either into or out of a space is commonly referred to as light-deflection technology12.
10 O’Connor, Tips for daylighting with windows: the integrated approach, 3.
11 Ibid.
12 “Thiele AG - Transparente Innovation.” 6
Figure 1-3: Daylit Zone – the figure on the left shows the depth of daylight in the case of an untreated window opening, while the right figure shows the depth extended up to 2.0x using light shelves.
The introduction of light redirection technology had a significant impact on the performance of facades in optimizing daylighting13. Light deflection devices have been proven to efficiently increase the performance of daylighting in interior spaces, by redirecting light deep into the spaces, minimizing the undesirable effects of direct sunlight and the use of electric lighting. Such systems include light shelves, light tubes, venetian blinds, and anidolic systems. While these techniques have the same objective - increasing the amount of daylight in interior spaces - they are not suitable for every building. For example, using light tubes in a high-rise office building is not an efficient approach, given the typical height of a high-rise tower.
Daylight problems are mostly treated as individual cases, in which system customization is sometimes required. Such customization does not have to involve the major alteration of an existing technology, but can be a minor addition that makes the system fit within the design
13 Koster, Dynamic Daylighting Architecture. 7
context. The system can be a passive daylight system that aims for better lighting inside spaces, or a static or active system that possesses some dynamic capabilities. While passive systems enhance performance, they lack the flexibility of adapting to changing outdoor conditions. For example, fixed light shelves are optimized for specific ranges of dates and times, and are less effective for the rest of the year or under different sky conditions. The ineffectiveness of light shelves is due to the changing angle of the sun. Given the limitations of passive systems, designers started adopting active control systems, which led to the introduction of kinetics techniques in façade design.
Over the past few decades, architects have adopted kinetic systems in many glass façade systems, for their interactive abilities - and not particularly for environmental purposes14. Having movable devices on a building façade was a turning point in the profession. However, a façade can be referred to as “interactive” without possessing kinetic capabilities. Media facades are one type of interactive architecture, considered socially interactive due to their use of lights. They are even sometimes considered to be sustainable, when they use solar energy as a renewable energy source. Other types of interactive designs include wall prototypes designed by some architects for social interaction purposes, in which a wall is able to respond to an occupant’s motion. But these are also irrelevant to our current environmental needs, since they only address artistic and aesthetic issues.
14 “FLARE-facade.” 8
Figure 1-4: Flare Façade – The modular façade is composed of metal flake elements that are controlled by a series of pneumatic cylinders. These elements reflect sunlight in a way that casts a shadow on some of the faces of each element, giving them darker colors. The façade does not optimize the energy performance of the indoor spaces, but socially interacts with people outside the building and operates as an interactive piece of art.15
Architecture is currently experiencing a demand for smart, responsive-based designs, where the occupants’ comfort level is achieved through means of perception, processing, and response. Buildings are becoming more like high performance working robots/machines. Designers are investigating the potential of making façade elements move in response to other stimuli, whether human or natural. If we are to develop the field of architecture and performance-based design, the profession needs to restructure traditional kinetic approaches to make use of
15 Ibid. 9
today’s technology, beyond conventional mechanisms and single-function design. Venetian blind systems that are programmed to retract and close at certain times of the days are an example of conventional kinetic techniques.
It is worth noting that a number of studies have demonstrated that the ability of an employee to control to a degree the daylight and electric light directly around his or her work area has led to even better production and morale. This is because, while overall good lighting is important, individuals often have their own particular preferences for brightness and the angle from which light hits their work area.16
The statement above proclaims the need for individual control of daylight and electric light around an employee’s working area. Given today’s technological advancement, individual control can be provided in the form of an automated-smart system: a system which stores the preferences of the occupants and acts accordingly to adjust the quality of the luminous environment inside the space, without the need for manual human control.
Integrating intelligent features into the architecture of a building is a discourse taking place in the architecture profession. Façades that possess intelligent capabilities are always referred to as “Intelligent Skins”. In Chapter 2, the research presents a detailed explanation of intelligent skins. Intelligent skins touch upon not only energy performance, but also the aesthetics of the design. This combination is the focus of many interactive architecture designers, such as Michael A. Fox and Chuck Hoberman, who try to use intelligence to transform façade panels whenever needed in response to natural forces. The design of façades, an important element of architecture, is influenced by changes in design trends, in terms of geometry and systems.
16 Ander, Daylighting Performance and Design, 28. 10
Many designers, some of whom are famous, are incorporating greater geometric complexity into their designs. This approach to design has become more widely used for landmark and iconic architecture. While complexity is also found in systems and structure, this aspect addresses complexity in terms of form and geometry only. Designing a building with complex geometry does not obviate the need to perform better in terms of energy-efficiency. An optimal approach in this case is to combine arts and science to support whatever design path the designer is undertaking, by providing advanced technological solutions. Though complex geometry is not in the scope of this thesis, it could be approached using the same technique as a regular façade: one way of integrating advanced technology is through the use of dynamic techniques and capabilities.
Dynamic kinetics is a façade typology that integrates movable panels into one large system, the envelope; it is an integral part of the whole building, acting independently. Within the scope of this study, dynamic capabilities are applied to a secondary skin, where the building has two external facades: one has the glazing, and the other is offset from the glazing by 1.00m and consists of a series of horizontal louvers. The offset distance allows for accessibility and maintenance activities to take place. While in this study the secondary skin is a series of kinetic horizontal louvers, it can be found in different forms and configurations based on the project’s objectives, whether performance-based or aesthetic.
11
In this case, the horizontal louvers function as light-deflection devices capable of adapting to environmental changes. The use of light deflectors as a secondary skin on a building requires proper rationalization of the system to match the desired geometry of the architecture. This sometimes requires system customization using commonly-used technologies, developing a new approach using established techniques. If we are to make a significant contribution to the field, we have to commit to a new paradigm based on innovative development of the old.
Signal your intention. Commit to a new paradigm, rather than to an incremental improvement of the old…. In this case, the intention is not to be slightly more efficient, to improve on the old model, but to change the framework itself.17
This statement by McDonogh and Braungart is inspiring for designers to look forward and support today’s technology in the design profession. It reflects the need for an innovative framework that adapts to current performance needs, rather than altering old techniques and making them fit within a new context. Good practice should experience a fluidity of design and scientific creativity flowing between architects and consultants, in order to achieve innovative buildings. Rethinking the design program may be better than refining an old approach to fit the target problem - the designer should make use of existing techniques and approaches to develop a new, perhaps customized, technique for solving design and performance problems. It is crucial for the development of our profession that designers learn from the past, explore the current, and innovate for our changing environment and demands.
17 McDonough and Braungart, Cradle to Cradle, 182. 12
1.2. RESEARCH STATEMENT
Energy efficiency in buildings is influenced by the behavior of architectural spaces, part of which can be attributed to daylighting. Daylighting performance is envelope-dominated. For example, designing fully-glazed façades minimizes the efficiency of the envelope, despite allowing huge amounts of daylight into a space. This does not necessarily result in good performance, since illumination levels are not optimized to fall within the acceptable range. The problem is notably experienced in south facing façades, which get the most solar exposure over the course of the day.
Daylighting is a crucial asset for office design, but it is variable. Indoor spaces suffering inadequate daylighting levels during daytime experience illumination levels (quantity) out of the recommended range, and uneven distribution of daylighting (quality). They also suffer the need for electric lighting to compensate for the limitation of daylighting depth into the space. The design profession is currently undergoing technological advancement which will allow for better daylight performance, targeting greater energy savings and reduced electricity consumption. This will happen by bringing daylight deeper into the space, maintaining desired illumination levels (quantity), and achieving even luminous distribution (quality).
The integration of light deflection techniques into an intelligent dynamic panel system allows the enhancement of daylight harvesting, quantity and quality, inside south-facing spaces enclosed by fully-glazed façades – Hypothesis
13
This hypothesis combines two different aspects of architecture that correlate: “intelligent skins” and “daylight-deflection technology.” Within the context of this thesis, 1) intelligent skin is the means through which 2) daylight-deflection is enhanced.
The statement focuses on the intelligent dynamic panel system and its impact on the quality and quantity of daylighting in office spaces. Investigating this topic requires defining particular specifications, among which are daylighting benchmarks and the qualities that distinguish an intelligent envelope performance. In Chapter 3, an explanation of the qualities and specifications of daylighting in office spaces is presented. These qualities vary, and include such factors as sensors and controls, patterns of actuation, panel materials, panel geometry, targeted number of inputs and outputs to and from the system, illumination levels (quantity), and luminous distribution (quality). This study specifically investigates independent tilt angles and panel geometry, and their impact on optimizing the quantity and quality of daylighting inside office spaces. Independent tilt angles are an approach proposed in which every other louver has the same tilt angle, either in shading or harvesting position.
14
Figure 1-5: Independent tilt angles – the shading and harvesting configurations of different panels actuate independently in a secondary skin system.
1.3. GOALS AND OBJECTIVE
An optimal visual environment in office spaces, achieved through the use of daylight, is crucial for employees’ comfort, productivity, and morale18. Visual comfort is addressed through many factors, among which are light level (illuminance), luminous distribution, glare, light penetration depth, and direct sunlight19. The research goal of this thesis is to design an intelligent dynamic light-deflection system that provides daylight levels within a recommended range, even distribution of daylight inside the space, and penetration of daylight deep into the space, beyond today’s normal achievable depth (Figure 1-3). For a better understanding of the goals, the studied parameters are further explained below.
18 Dasgupta, The Impact of Windows on Mood and Performance of Judgmental Tasks.
19 Schiler, Simplified Design of Building Lighting. 15
1.3.1 ILLUMINANCE
Different organizations, like the Illuminating Engineering Society (IES) and the National Research Council of Canada (NCR), recommend different light levels for office spaces. The recommended illumination level for an office space according to the Illuminating Engineering Society of North America (IESNA), is 200 – 1500 lux, based on task.20 The NRC Institute for Research in Construction recommends a level of 400 – 500 lux for general office work.21 In terms of daylight factor, the recommended percentage is 2-5%. Maintaining a range of 200-1500 lux is the objective of this study, taking into account that values less than 200 lux, and higher than the recommended range, may be acceptable in some areas of the space, under certain conditions, where no activity is assumed to take place.
1.3.2 LUMINOUS DISTRIBUTION
For a better visual environment, the IESNA recommends that, within the occupant’s field of view, the ratio between the maximum and minimum illuminance should not exceed 1:10.22 However, the NRC Institute for Research in Construction recommendation exceeds that of IES, and goes up to 1:2023, providing an acceptable argument for this high contrast, like highlighting certain objects on the working plane. Sometimes due to high contrast, the occupant perceives
20IES North America, IESNA Lighting Handbook.
21National Research Council Canada, “NRC Canada.”
22 IES North America, IESNA Lighting Handbook.
23National Research Council Canada, “NRC Canada.” 16
parts of the space as dark which in reality have sufficient light levels. Maintaining a ratio of 1:10 prevents the false perception of light level inside spaces.
1.3.3 LIGHT PENETRATION
Untreated window openings allow light penetration one-and-a-half times the distance from the floor to the window head. Incorporating light shelves extends the ratio up to twice the distance (Figure 1-3). For example, a 2.20m window head height allows the penetration of daylight into the space up to 3.30m, if using an untreated opening, and 4.40m if using a light shelf. Within the context of this study, the goal is to exceed the 2x ratio – aiming for, at least, two-and-a-half times the vertical distance.
1.4. STRUCTURE AND METHOD
This thesis develops a parametric tool for integrating daylighting performance into the process of kinetic façade design. The tool is intended to be used by anyone - but especially designers - involved in the design process and early-stage decisions. This idea, where innovative, contemporary, exciting developments in façade design are tested for daylight optimization, is a primary concern; it allows designers to find the potential of complex design forms to enhance the indoor luminous environment.
The study focuses on investigating the effectiveness of light deflection by an intelligent secondary skin layer in south-facing indoor spaces. In this study, parametric tools are used to search façade configurations, by pre-defining some parameters denoting intelligence and environmental changes (refer to Chapter 2 for intelligence parameters). The investigation of this 17
topic prior to executing computer simulations is crucial. To address the problem in an efficient manner, the research has been divided into three main parts: investigation (literature study), simulation and documentation, and analysis. Each of the three parts is explained in the section below.
1.4.1 INVESTIGATION
This section provides a complete literature review of the investigated topic and its attributes. Given the investigation of two related topics, 1) intelligent kinetic skins and 2) daylighting performance, the investigation phase is split into two chapters. The literature review of both topics addresses the definition of intelligence within the framework of the study, the use of intelligent skins as light-deflectors, and the performance of daylight-deflection in enhancing the quality and quantity of light in office spaces.
If we are to express the correlation between intelligent skins and daylight enhancement, some points need to be covered in the literature study of the topic. These points directly relate to the intelligence of a building skin and its ability to respond to environmental changes, specifically sunlight. Providing a solid background to the following points builds a concrete foundation for explaining daylight enhancement through the use of intelligent systems:
 What is intelligence?;
 The concept of intelligent responsive systems;
 Intelligence and environmental controls;
 Sensors, data exchange and feedback loops of intelligent systems. 18
While more points are covered further in Chapter 1, for the interest of the study, the first portion of Chapter 2 covers the intersection of intelligent skins and daylight enhancement; it explains possible techniques for using smart-kinetic systems to adjust daylight quality in indoor spaces. Examples of similar systems and previous work are used to illustrate the positive potential of using deflection techniques in the context of the current technological advancements. The main points covered in Chapter 2 are:
 Benefits of daylighting;
 Daylight fundamentals;
 Performance indicators;
 Deflection techniques.
1.4.2 PROCESSING LOGIC
Within the framework, data processing depends not only on the simulation tool and its calculation capabilities, but also on the pre-defined parameters, based on the desired daylighting performance. The algorithmic components incorporated into the set of parameters force data to flow in certain directions for evaluation purposes. Processing stops when an optimal skin configuration is found by the genetic algorithm component (Figure 1-6). 19
Figure 1-6: System logic – the inputs to the system and the processing of data.
Grasshopper is responsible for setting the input parameters according to the desired luminous environment conditions, and passing these to the daylighting simulation tool, DIVA/Radiance, which then processes the data and sends the results back to Grasshopper for evaluation. Grasshopper compares the results against the pre-defined performance criteria. If the results are acceptable, Grasshopper provides the generated solution as the best possible under the defined simulation conditions. If the results do not match the criteria, Grasshopper sets another scenario for the skin and triggers the simulation tool to re-run a new scenario and generate a new outcome - and so on, until an acceptable result is obtained (Figure 1-6).
20
The proposed data workflow depends on a solution-based factor, where processing is about finding the optimal solution for a design problem. The system will run “all” possible solutions and then pick the one resulting in the best daylighting performance inside the space. Panel tilt angles are endless; thus, increments of 3.60 degrees will be set to restrict the possible set of solutions to 100.
Different sun conditions are expected to affect the performance of daylighting in the space, and simulating all times of the day is difficult due to time limitations. Consequently, data will be recorded for the following times only: June 21st (summer solstice), December 21st (winter solstice), and March 21st (equinox), each at 9:00am and 12:00pm, for clear sky and overcast sky. At each of the mentioned times, the sun has different solar angle and/or a different direction.
1.4.3 DOCUMENTATION
The integration of four tools was necessary for the objective of this study: Rhino as a modeling tool, Grasshopper as a parametric interface, DIVA 1.1 for daylight simulation, and the Galapagos component as a genetic algorithm problem-solver. A simple example is developed to assess the performance of the system in searching for an optimal solution for skin configurations. Grasshopper is used to identify the input parameters and the evaluation criteria for daylighting assessment, the DIVA component is used to simulate the process of daylighting, and Galapagos, the genetic algorithm component, uses a single-numerical value as a fitness number in search of optimal configuration.
21
The proposed tool is intended to be used by designers at the early stages of design, to integrate daylighting performance into the process. Such integration could be into the design of interior spaces, building envelopes, and/or orientations. In Chapter 4, the proposed design algorithm used to determine the optimal configuration for a building skin for better daylighting performance is documented. The algorithm is applied to a secondary skin configuration composed of horizontal louvers split into two independent layers; every alternate louver has the same tilt angle. The definition utilizes Radiance as the calculation engine for daylighting, and has been divided into screenshots, which are shown in Chapter 4.
1.4.4 SIMULATION METHOD
As a parametric design tool, Grasshopper allows the creation of a kinetic system that can respond to multiple inputs and outputs through the use of a genetic algorithm. In this tool, intelligent features are expressed as parameters, mathematical functions and benchmarks which make the intelligence of the system limited, but flexible enough for the system to implement certain desired tasks for better daylighting performance. Given that DIVA is a Rhino/Grasshopper plugin, it can easily be integrated into the intelligent part of the algorithmic definition.
Technical difficulties were experienced using DIVA 1.1, the daylighting simulation tool, to extract illuminance values and import them into Grasshopper. The difficulties experienced were due to scripting issues in the component itself. This problem prevented node values from being passed to the evaluation criteria for assessment.
22
Simulation is vital for this study, to illustrate the objective of the tool. Daylight simulation is a commonly-used technique for predicting the quality of luminous environments, as well as accounting for daylight variability during early design stages. This part provides a set of figures and results generated through executing numerous simulation runs for different skin configurations. Intelligence is defined in the parametric software in the form of preset parameters/constraints, such as the occupants’ desired illuminance range. As previously mentioned, Rhino, Grasshopper and the DIVA-plugin are the tools used for simulation in this study. These three tools were designed to work together, and are capable of efficiently exchanging data without the need for more interfaces, making the simulation clean, quick, and reliable.
Modeling building intelligence in computer programs is new technology. Accordingly – within the content of this thesis – intelligence is defined in terms of parameters that can be controlled and referred to as “intelligent enough” to execute required tasks, like setting a parameter for the desired illuminance range. These parameters work in a loop of multiple inputs and outputs which can only be handled by parametric software.
In all simulation runs – as shown in Chapter 5 – a generic office space of 6.00m x 7.50m x 3.00m is used. These dimensions remain fixed throughout the entire study. Though the tilt angle changes, the space dimensions remain the same. The façade is assumed to be fully glazed, using a curtain wall system. However, the elements of the curtain wall system are not taken into account during simulation, in order to minimize calculation time. Initially, the simulation is run 23
for clear and overcast skies for three base test cases: glazing only, light shelf, and horizontal louver system. This part shows the enhancement of daylight performance in relation to changing façade/skin system. It also illustrates the ability of daylight deflection to affect the indoor luminous environment quality.
Afterwards, an intelligent-dynamic system composed of a series of louvers arranged horizontally, each actuating independently (Figure 1-7), is modeled using Rhino/Grasshopper. This is considered to be the main case study of the thesis, on which design alterations will be tested. The panels actuate independently, with the aid of some parametric algorithms. The performance of the skin is shown inside the interior space in terms of quality and quantity of daylighting - which requires establishing some measuring points in the space.
Figure 1-7: Independent actuation of secondary skin panels for better indoor luminous environment quality.
The modeled office space is divided into 36 calculation nodes spread over a grid set at 0.70m, covering the entire surface area of the interior space. Assuming workers do not occupy the entire floor area of an office space, the success of the system is based on achieving the desired performance indicators – previously mentioned – for at least 75% of the office floor area. 24
Theoretically, the calculation grid is composed of points that read the lighting levels in different positions inside the space. It is expected that readings will vary from one point to another. These points act as the sensors in the simulation. Readings from each point are individually extracted and passed on to set performance criteria for assessment.
A successful run should be able to achieve each of the three indicators for as close as possible to 75% of the entire surface area. Two types of indicators are experienced in this study: individual node indicators, and group indicators. An individual indicator is the illuminance of each point. This does not require evaluation of all points together to see if they fit within the range or not; each node is evaluated independently. Group indicators represent the luminous distribution and the depth of penetration. To evaluate both items, the system is required to look at the results as a collection of nodes, and assess their performance.
1.5. CONCLUSION
Daylighting is a crucial asset in office spaces; it increases the productivity of workers, enhances their morale, and maintains their health24. Despite its importance, sometimes designers do not adequately account for daylight during the design phase, which subsequently requires the use of more electric lighting. On the other hand, some architects, like Aalvar Aalto, Louis Kahn, and Le Corbusier, addressed daylight through architecture, emphasizing its importance25. This thesis
24 Boubekri, Daylighting, Architecture and Health.
25 Schiler, Simplified Design of Building Lighting, xi. 25
explores one example, where innovative-contemporary developments in façade design are considered for better daylighting performance in south-facing office spaces. The whole study is dependent on daylight-deflection techniques to bring daylight levels to desired ranges inside a generic office space. The deflection method is supported by some intelligent features to enhance the operation of the façade system.
The methodology implemented in this study enables designers to account for the performance of daylighting during the early design stage. It also allows them to explore numerous façade designs and their impact on the quality of the indoor luminous environment. Moreover, the technique integrates lighting analysis into the design/modeling tool, which eliminates the need for more interfaces or model export/import procedures. The proposed algorithmic definition is intended to provide flexibility by allowing the possibility of setting different performance indicators – if necessary – based on different design problems.
In the following chapters, an elaboration of the investigated topic is presented, detailing the argument, as well as the intersection of intelligence and daylight-deflection.
26
2. CHAPTER 2 INTELLIGENT SKINS
Applying intelligence to buildings in the form of intelligent façades, sensors, materials, or even building systems, is a discourse taking place in the profession. In this chapter, background research into intelligence in architecture, intelligent applications to buildings, and the human interaction with building systems, is presented.27
2.1. OVERVIEW
The word “intelligent” was first used at the beginning of the 1980s to describe buildings, together with the American word “smart”26. Since then, building façades incorporating intelligent features have come to be known as “intelligent building skin,” where the skin forms the greater part of the intelligent system in the building. Describing a façade as an intelligent element requires the presence of dynamic living capabilities, which enable interaction with diurnal and seasonal changes, and human beings in the surrounding environmental context, in order to achieve a reduction in the energy consumption inside indoor spaces. Intelligence is not an equation of fixed variables; it is a process that is inspired by human intelligence and cognitive capabilities. That being said, the definition of intelligence can be manipulated in different ways according to the designers’ intentions and approaches. However, all definitions acknowledge the influence of living organisms in terms of behavior and reasoning.
2.2. INTELLIGENCE IN ARCHITECTURE
Applying intelligence to buildings in the form of intelligent façades, sensors, materials, and even building systems, is a discourse taking place in the profession. People are the establishing point for intelligence in buildings. They are not passive organisms, but adapt to their surroundings psychologically, physically and behaviorally, and often change their environments to be more suitable for them. This is a complex interaction, informed by their senses and mediated by the brain. The brain allows people to reason, perceive, and react to their environment, whether
26 Wigginton and Harris, Intelligent Skins. 28
tangible or non-tangible. Humans have always been the inspirational model for considering the application of intelligence in buildings (Figure 2-1).
Figure 2-1: Intelligent Building Features and Human Intelligence – the aspects of human intelligence that profoundly impacted the implementation of intelligent features in buildings27.
The concept of intelligence in architecture should be distinguished from integration or automation in buildings. Intelligence is often referred to by people when objects or elements function using automated features and control systems28. They sometimes use the term “intelligent” to describe automated domestic functions at home through a computerized system, like turning on/off the lights, or opening and closing doors. Since these actions are manually triggered by the occupant, they should not be considered intelligent, due to the absence of a system reasoning process (Figure 2-2). In this research, intelligence is based on a
27 Clements-Croome, Intelligent Buildings, 44.
28 Fox and Kemp, Interactive Architecture. 29
different archetype, which relates to human characteristics and the energy-performance of indoor spaces in buildings, exploring the interaction between the building skin and occupants to provide a better luminous indoor environment. Clements-Croome provides a relevant definition of the term ‘Intelligence’:
Intelligence is not an attribute, but a complex hierarchy of information processing skills, underlying an adaptive equilibrium between individuals and their environment.29
Moreover, the Intelligent Building Institute (IBI) presented one of the first definitions of intelligence in buildings:
An intelligent building is one which provides a productive and cost effective environment through the optimization of its four basic elements – systems, structure, services, management and the inter-relationship between them. Intelligent buildings help building owners, property managers, and occupants realize their goals in the areas of cost, comfort, convenience, safety, long-term flexibility, and marketability. There is no intelligence threshold past which a building "passes" or "fails". Optimal building intelligence is the matching of solutions to occupant needs. The only characteristic that all intelligent buildings have in common is a structured design to accommodate change in a convenient, cost-effective manner.30
Given the scope of this thesis, the above statement presents a valid argument. Assessing the performance of intelligent systems in buildings does not have an absolute benchmark; it is a relative evaluation process that depends on the occupants’ needs and preferences, and the function of the space. Accordingly, the presence of an occupants-model during simulation is necessary for the success of the study. However, simulating such a model in the study would add another layer of investigation, and this has not been included, due to time limitations. Therefore, a compromise has to be made for the simple modeling of intelligent features. The
29 Clements-Croome, Intelligent Buildings, 5.
30 “iBuilding Website.” 30
occupants-model is represented in the form of a set of parameters that resemble the normal working employee preferences. These parameters are simplified factors of the desired luminous environment in general office spaces. Refer to Chapter 3 for a detailed explanation of the desired quality of luminous environments.
People involved in the design and construction process can have different views on the performance of an space; the occupant, however, is the one who will truly judge the success of the luminous environment inside the space. Since it is hard to incorporate occupants in the simulation model, the designed algorithmic definition allows for multiple variable inputs to represent changing user needs. This is considered to be an appropriate simplified method for mimicking changing occupants’ preferences.
Despite their importance, some buildings tend to ignore occupants’ behaviors and preferences, and incorporate responsive features that work based only on environmental changes and climatic conditions. An intelligent building can be looked at as a human body, where occupants represent internal organs, and the envelope resembles the external organ, the skin. Human intelligence is geared to protecting the internal organs, and providing an optimal living environment for them to perform well. Likewise are the building occupants. They need to have a good working environment for better productivity. The occupants’ behaviors and preferences are driving factors for building operation - though they differ according to the climate and function of the space. An intelligent building should be able to achieve optimal performance by implementing the following processes: 31
 Create a relationship between occupants’ behavior and indoor space conditions.
 Automatically adapt and respond to environmental changes and user requirements.
 Expedite cost-effective alteration to occupants’ behavior changes, including changing tasks.
The term “intelligent” has been applied recently to objects that resemble human beings’ behavior. Sometimes called ‘smart’, they tend to process (perception) data like human beings and react (action) based on a process of analysis (thinking). Most of these intelligent features have the same intent, but are different in scale and function. In cars, for example, intelligent driving systems enable cars to automatically detect when cars ahead stop unexpectedly and respond by applying brakes. This feature provides security and comfort to the driver - who is the occupant in this case. The smart driving system evaluates the situation and reacts in a way similar to the way the driver would have reacted. It mimics the expected driver’s behavior for better performance and comfort.
Intelligent buildings should operate in a similar way. They are expected to possess some cognitive features that allow them to perceive data, analyze it, and respond with an appropriate reaction (Figure 2-2). This process can be applied to different aspects of the building operation, among which is the environmental performance of spaces, emphasizing this study’s objective. Embedding the behavior of users, and the changing environmental conditions, into an intelligent-cognitive system may drastically enhance the energy performance of spaces. 32
Figure 2-2: Intelligent Process – the data flow process that, generically, identifies a façade as an intelligent feature.
In his book “Intelligent Buildings”, Brian Atkin identifies three aspects that should be found in intelligent buildings:31
 Buildings should ‘know’ what is happening inside and immediately outside;
 Buildings should ‘decide’ the most efficient way of providing a convenient, comfortable, productive environment for the occupants;
 Buildings should ‘respond’ quickly based on occupants’ preferences.
Figure 2-3: Qualities of building intelligence – the main qualities of building intelligence, as defined by Mervi Himanen.32
31 Atkin, Intelligent Buildings.
32 Clements-Croome, Intelligent Buildings, 45.
Perception (Sensors)
Analysis and Reasoning (BMS)
Response (Dynamics) 33
Mervi Himanen divided the qualities of building intelligence into five main categories (Figure 2-3): connectivity, self-recognition, kinaesthetics, logic, and spatiality. Clements-Croome defined each category as follows:33
 Connectivity relates to how the occupant connects to the system. This could be through speech recognition, automatic control, motion detection, etc.
 Self-recognition provides self-consciousness capabilities for the building to detect its current status and interaction level.
 Spatiality describes the spatial expression of the architecture.
 Kinaesthetics relates to the kinetic capabilities of the system, as well as adaptive technology.
 Building Logic expresses the embedded sensors layer that monitors occupants’ behavior and reports back to the building management system.
These five factors are taken into consideration within this study with a different approach than that of real-life, due to the limitations of simulation tools, time constraints, and the difficulty of modeling occupants’ behavior inside the space. “Connectivity” and “Building Logic” are expressed in the form of a pre-defined set of parameters which reflect the occupants’ requirements for better productivity and an enhanced luminous environment. These parameters can be changed at any time prior to running the simulation, which means that the system can be tested for different user preferences, if any. “Self-recognition” and “Spatiality” are expressed in the form of space-sensors/calculation points. Whenever the calculation grids
33 Ibid. 34
go out of the performance criteria range, the system should be able to detect this and work to bring at least 75% of the points into the desired range. Although the method used in this study for simulating one factor of human intelligence inside the space - the varying occupants’ desired range of illumination - is not close to reality, it is the best model that can be achieved within the time limitation.
As previously mentioned, intelligent-responsive skins should account for environmental changes and occupants’ comfort for better performance. But does this mean that no building skins without intelligent features perform well in terms of energy-efficiency? The answer is “no”. Environmental approaches have been implemented in the profession before the advanced intelligent technologies discussed here were invented. Architects have long integrated passive approaches into their designs to enhance the performance of the spaces. We, as architects, should acknowledge the importance of previously-designed buildings in providing a concrete foundation for implementing today’s technologies in the intelligent-responsive building field. The following section provides two examples of passive environmental controls in architecture which influenced the invention of today’s techniques.
2.3. SKIN AS ENVIRONMENTAL FILTER
Given that a façade is the exterior shell of a building, it should act as an environmental filter fine-tuned towards energy-reduction, daylighting, ventilation, and excellent quality of indoor spaces. Throughout history, façade treatments for better performance have been applied to protect indoor spaces from adverse climatic conditions. Many different examples illustrate the façade as an important filter layer, among which are: Mashrabiyya, brise-soleil, the trombe 35
wall, high-mass walls, and super-insulated envelopes. Despite the functional differences between the techniques, they all aim for better indoor environments, as well as protecting occupants from unfavorable environmental changes. Mashrabiyya and brise-soleil are especially good examples, which attempt to deal with both thermal and daylighting considerations.
Figure 2-4: Egyptian Mashrabiyya – the Mashrabiyya is a great example of an environmental façade treatment for optimizing daylighting, minimizing glare, and driving cool air into the space. The image on the left34 shows the indoor effect of this element, while the image on the right35 shows the exterior look of this ornamental Egyptian icon.
The Mashrabiyya is a great example of a passive environmental façade application that controls daylighting and natural ventilation inside a space. Hassan Fathy, the Egyptian leader in
34 “Sennari House In Cairo: Home to Napoleon’s Scholars.”
35 “Mashrabiyya - Wikipedia, the free encyclopedia.” 36
environmental and vernacular architecture, describes the Mashrabiyya as a mean of control of severe glare conditions in interior spaces (Figure 2-4). In old times, Egyptians were leaders in inventing environmental performance-based prototypes. They adopted the Mashrabiyya in most Egyptian Islamic houses for environmental purposes and comfort of human occupants; in addition, it also reflected local cultural values36. While it was a successful approach, widely adopted in Egyptian houses, people are now moving towards implementing more advanced technologies in buildings. The Mashrabiyya works inefficiently when windows are open – as seen in the left image of Figure 2-4 – which is necessary for having an outdoor view. The question arises: if it performs so well, why don’t we continue using it? Simply put, the answer is: we cannot use this ornamentation piece on all façades. It is a product of the Egyptian culture that was suitable for buildings at that time - the middle ages up to the mid-twentieth century. As seen in Figure 2-4, the design of this element was customized for specific cultures; it is not a generic-modern element that can be fitted into any design - quite apart from its transparency limitation, as previously mentioned.
The Western world has had different approaches for environmental filters. Brise soleil, a pattern of permanent concrete shading elements, is a technique that was popularized by Le Corbusier in buildings with large surface areas of glazing37. This performance-based pattern allows the penetration of low-angle sun in winter, for passive heating, and the blockage of high-angle sun during the summer (Figure 2-5). The Gustavo Capanema Palace, designed by Le
36 Kenzari and Elsheshtawy, “The Ambiguous Veil.”
37 Melendo, Lainez, and Verdejo, “Nineteen Thirties Architecture for Tropical Countries.” 37
Corbusier in 1935, is a famous example that shows the efficient use of brise soleil in Rio de Janeiro. In this example, the brise soleil works well with high-angle sun, however the system is limited in its ability to deal with low-angle sun that may penetrate the space, resulting in an uncomfortable luminous environment. Today’s demands for complexity in form and design led to the emergence of another aesthetical limitation of using traditional brise soleil, however this system is found in some old buildings by famous architects like Richard Meier, who used brise soleil in a canopy at the Getty Center in Los Angeles, California.
Figure 2-5: Brise Soleil – a modular pattern of fixed concrete shading elements to protect occupants during summer months from heat gain and to allow passive heating during winter months.38
Architects have long been able to achieve successful environmental control techniques for “better” performing spaces. They used all available resources – from cultural inspirations to
38 “Brise soleil - Wikipedia, the free encyclopedia.” 38
local materials – to achieve better performance. Though these techniques worked well at the time, they do not fit within the needs and preferences of today’s occupants, and the design complexity. In other words, though the performance of these systems hasn’t changed, other variables have changed which demand better energy performance inside spaces. My hypothesis is that the fast pace of ongoing technological advancement in building systems has made the occupants demand more energy-efficient environments - especially in office spaces - for better productivity and lower running costs. To fulfill the users’ needs, designers have explored advanced techniques on building façades, which represent a significant part of any architectural project, besides acting as the medium between the indoor and outdoor environments39. However, designers have also developed new systems inspired by historical innovations.
The main case study of this thesis investigates the performance of a brise soleil-like system that possesses dynamic-responsive capabilities. The system uses the same solar shading technique of the brise soleil, and adds to it light-deflection techniques for enhanced luminous environment in office spaces. While the proposed system is inspired by historical innovations, it exploits today’s advanced technology by integrating intelligent features into the skin system, which allow independent tilt angle control for each panel.
Building façades are the main manipulators of environmental parameters. If designed efficiently, they should be capable of maintaining an adequate comfort level, by adjusting the impact of natural forces on interior spaces. The envelope’s functions include daylighting optimization and
39 Wigginton and Harris, Intelligent Skins. 39
glare protection, acoustical barrier, natural ventilation, humidity adjustment, wind protection, visual contact, security and safety, and energy performance. For a building to overcome unexpected and changing adverse climatic conditions, it has to integrate advanced cognitive technology that allows the skin to think, and respond appropriately. For example, a space can detect changes in human behavior - typing or reading, for example - and optimize daylighting levels accordingly.
2.4. INTELLIGENT KINETICS AND DAYLIGHTING PERFORMANCE
The skin is one of the dynamic regulatory organs that allow the body to survive through a wide range of unfavorable conditions. The intelligent behavior of the skin enables adaptation to the surrounding environment by means of physical processes, such as perception, reasoning and action, which allow the human body to overcome adverse environmental conditions. Analogously, the building envelope acts as the medium through which the interior spaces of a building interact with the surrounding environment. Buildings are subjected to a wide range of unfavorable and varying environmental conditions, which requires the envelope to possess intelligent‐dynamic capabilities, and automatically respond to environmental changes and user demands.
Smart-kinetic façades are one type of intelligent skin. This is a technological advancement that addresses today’s dynamic, constantly-changing activities in order to optimize indoor conditions to meet the user’s needs. Smart-kinetics is the flexible adaptability of building façades to respond to changing environmental conditions, taking into account human interaction and 40
behavior. They should be capable of handling the rapidly varying patterns of human interaction in a space.
Smart-kinetics, part of comprehensive intelligent building systems, can be designed as performance-based elements that relate to interaction and responsiveness. They can be part of a primary system, or perform independently as a secondary skin layer. Operable windows are one example of a primary system application, where the windows on the main envelope open and close according to need, while a series of external louvers is a secondary skin application, distinct from the main skin and operating independently. Michael A. Fox, an interactive architecture designer, refers to this type as “dynamic” kinetic typology, where the kinetic elements are part of a bigger system but can act independently.40 Besides the potential of providing better energy-performance, the use of a secondary skin system allows for more creative designs and skin geometries. That is why a secondary skin system is used in this study. Despite the advanced technology in most buildings, only a few efficiently exploit the presence of an intelligent platform in the building management system, because cognitive-smart applications in buildings haven’t developed enough yet for real-life applications. Though some buildings are referred to as “intelligent architecture,” they can only execute specific tasks, and are unable to act the same way human beings do.
Responsive skin systems first emerged in the form of kinetic technology that works according to a pre-defined set of orders, with no room for processing or reasoning in response to unforeseen
40 Fox and Kemp, Interactive Architecture. 41
variables. Natural forces are the variables in this case. One example is a dynamic louver system that follows the motion of the sun to prevent direct light inside the space. Such a system is not considered intelligent, as the sun’s path is already known and can be programmed into the system, making the louvers move in the same pattern every day. A designer can provide the equations for calculating the sun’s position, and the panels will actuate accordingly to face the calculated position. This can be referred to as a single-input system, where only one pre-set input is dealt with. Other types of input that can directly affect the occupants in terms of comfort level and productivity include: enhancement of daylight, maximization of daylight, protection from the sun, insulation, natural ventilation, heat collection, heat rejection, sound attenuation, generation of electricity, and exploitation of pressure differentials.41
Making a building respond to and account for human needs in its daily operation is one problem where user input is critical. This is obvious when it comes to lighting in office spaces. People usually assume that daylighting will be available when they go to work during daytime. In fact, employees rarely question the quality of the luminous environment inside the space. With today’s changing needs, designers have provided occupants with manual control of lighting for better satisfaction, reflecting changing tasks and activities inside the same space. The question is: what happens if we design an intelligent daylight harvesting system that automatically recognizes occupants’ demands and reacts accordingly? Will it enhance daylighting performance and satisfy users? My answer would be: yes, it will. This does not mean that good performance is achieved only through intelligent kinetics, however; it is one of many approaches.
41 Wigginton and Harris, Intelligent Skins, 36. 42
Within the scope of this research, the critical questions of “where” and “when” daylight is needed are more important than “how much”. Adding the time and place as variables to the equation requires the implementation of an automated-cognitive system that can automatically detect human behavior, and react to it in an appropriate manner42. This is what is referred to as an “intelligent” system, after adding the “how much” to the equation.
2.5. TYPOLOGY OF KINETICS IN ARCHITECTURE
Kinetic architecture can be expressed in different forms in buildings, one of which is integrating dynamic features into the façade/skin. Kinetic façade elements are found in various configurations. Below are some configurations of kinetic façades that have been adopted in current buildings. All images in this section have been extracted from a Master of Building Science thesis by former USC student Ryan Hansanuwat.43
42 Wang, Intelligent Buildings and Building Automation.
43 Hansanuwat, “Kinetic facades as environmental control systems.” 43
Figure 2-6: Kinetic Typology – The figure shows various typologies of kinetic envelope applications on building
facades.
44
Figure 2-6: Continued
45
Figure 2-6: Continued
46
Figure 2-6: Continued
47
2.6. HUMAN INTERACTION AND CONTROLS
Architectural space can take advantage of an audience locally, regionally, and globally by reconceptualizing the role that the physical environment plays in shaping the viewer’s experience.44
The quote above is from Interactive Architecture, a book by Fox and Kemp which presents the general idea of human interaction in a simple way. Though it sounds simple, the quote carries an important aspect that highlights the significance of human interaction in the field of intelligent skins: it is the users’ learning experience. Intelligent architecture should be able to not only expedite lifestyle and behavior, but also to influencing them.45
Intelligence in architecture is a two-way process, in which the building learns from the occupants’ behavior, and vice versa. The architectural environment can learn from our experiences on a short-term or long-term basis, and can also teach us how to live more efficiently. For example, when direct sunlight hits the working plane, an intelligent system of series of louvers can adjust to overcome the problem of glare or over-illumination. The occupants will learn that, at this time of the day, the sun direction is undesirable for better working conditions. This feedback from the system is significant in teaching occupants how to respond to such situations. Though there could be more complex examples, this one explains
44 Fox and Kemp, Interactive Architecture, 138.
45 Ibid., 142. 48
the simple idea behind a back-and-forth interaction. Another quote from the same chapter in Fox and Kemp's book says that:
To a certain extent, our behaviors are nothing but learned intuitions growing out of our experiences in the world.46
As buildings react to changing human behavior, users are challenged with new levels of involvement, understanding and choice. Since this interaction brings new learning experiences to their lifestyle, it is crucial for architects to account for these changing patterns in future designs, and make them geared towards enhancing the working environment in ways other than facilitating the human experience inside the space.
Intelligent architecture responses could be based on either knowledge-based information, sensor-based information, or both. There are many possible mechanisms of human interaction, including sensors, which are highly important elements in intelligent environments. Sensors are devices capable of gathering data from the real world, like motion, light, temperature, humidity, sound, and so on.
2.7. MODELING INTELLIGENT KINETICS
Conceptually, the design of kinetic skins is similar to some of the advanced techniques where the designer adjusts parameters to generate a range of outcomes, except that in the case of
46 Ibid. 49
intelligent kinetics there is no final form; rather, the design outcome is a kinetic process, from which multiple forms will occur over the life-cycle of a building.47 Kinetic skins are generally described as elements integrated into one large system, with adaptable capabilities to create more efficient spaces. The need for better-performing architecture has led to the emergence of kinetics technology, extending beyond conventional techniques. The current trend in the profession is towards incorporating sustainability and technology as integral elements of this larger system, such as intelligence and kinetic applications. In practice, kinetic façades are found in different compositions, where each has its own characteristics, objectives, and impact on the building functionality and aesthetics. They are not necessarily for purely sustainable purposes, but also have aesthetic or socio-cultural value. That being said, modeling intelligence in computer tools is crucial for achieving all the objectives mentioned above.
Modeling intelligence is a special, complicated case of simulation. Commercial computer tools for modeling intelligent architecture are not yet available for designers. Most of the work, time and effort is still in research labs, and firms specializing in this advanced technology. The challenging part of simulating intelligence is in how we can insert human-like agents into a model and make them behave like human beings, and how the computer tool can detect these agents and recognize their behavior as occupants. In the case of real-life simulations, where sensors occupy the space, it is still hard – but not impossible – for the sensors to understand and detect human behavior and emotions, and react accordingly. Many research labs are currently
47 Moloney, “Building Skins as Kinetic Process: Some Precedent from the Fine Arts.” 50
working on cognitive realization of human behavior, and how sensors can detect facial emotions and human interaction.
Carnegie Mellon Robotics Institute is one of the leading labs in intelligence and human interaction. The Intelligent Agent Technology Lab is developing a research project about “Agent-based Composition of Behavioral Models (ABC)” in which cognitive models are being developed to represent human performance in computer simulations. These models provide a comprehensive representation of the knowledge, behavior, problem-solving skills, and procedures used by occupants in task situations; they take into consideration the intellectual capabilities and limitations of humans. Since there is no “standard” cognitive reference for all situations, problems still persist in developing the human behavior models. The project team analyzed labor-intensive tasks to create a detailed mapping of what humans do to accomplish those tasks. Though this method is time-consuming, effort-intensive, and does not well represent real human behavior, they were able to program human agents with a set of production rules and executable procedures.48
This is where the argument lies: how can we rationalize human behavior in the form of rules, procedures and parameters in simulation tools? How simple should it be? Should the model be capable of handling multitasking or single-tasking? In my opinion, a successful comprehensive simulation would be one that exploits more than one human model, each representing a single-task activity. In this study, the behavior of occupants is dependent on the quality of the
48 “Robotics Institute: Agent-based Composition of Behavioral Models.” 51
luminous environment. Intelligence has been integrated into the simulation from a single-task perspective for adjusting the quality and quantity of daylighting inside the space; only the desired illumination for occupants has been taken into account in the algorithm. A set of parameters is changed, based on human discomfort assumptions that allow for testing the intelligent skin system against different scenarios of occupant preferences. This is not the only method of simulating human behavior during the early design stage, but it is the simplest.
52
3. CHAPTER 3 DYNAMIC DAYLIGHTING
Bringing daylight into the core of the building is an architectural design challenge that aims for a better visual environment and greater energy efficiency. This can be achieved through the use of advanced dynamic daylight strategies.
This Chapter addresses the specifications for daylighting requirements, providing essential fundamental knowledge for the purpose of this research. It presents background research on daylight and its rewards, daylight qualities, light-deflection strategies, daylight evaluation, and the target benchmark of the design. It is expected that the reader will, at this point, have the necessary information on which the simulation in the following chapter is based.53
3.1. INTRODUCTION
In 197349, the energy crisis triggered designers’ interest in the use of renewable sources of energy, such as solar power, in an effort to reduce non-renewable energy usage. Today, the increasing notion of scarce resources has demanded better daylight strategies to minimize dependency on electric light. Despite the growing notion of energy conservation, daylight is not often used as a major scheme to exploit renewable sources and reduce energy consumption. Many offices rely on electric light during daytime, when it is unnecessary and can be replaced by the integration of daylight strategies. The point is that the notion of energy conservation has not influenced architectural practices enough to adopt advanced daylight approaches in the design. They are required by code to provide certain levels of illumination for different space usage, regardless of the source of light, which gives more room for relying on electric light to compensate for the lack of interior illumination from natural light. New demands by the building industry, and occupants, requires taking daylighting into account during the design phase, to allow more light deep into the core of the building and maximize the percentage of daylit areas.
Daylighting in architecture is a design strategy that exploits natural sunlight in indoor spaces, reducing dependency on electric light, and maintaining human health and a productive work environment during daytime. Daylight refers only to the visible part of the energy spectrum released by the sun (Figure 3-1). It is a source of light that provides full-spectrum light with flawless color rendering.
49 Boubekri, Daylighting, Architecture and Health, 39. 54
Figure 3 -1: Electromagnetic Spectrum – the range of the visible part of the spectrum.50
Daylight, as a free design resource available to architects, enhances the quality of indoor spaces. It invigorates interior spaces, creating a relationship between the occupant and the space. This relationship could be dramatic or intimate, depending on the function of the space. For office spaces, intimacy is required for a better work environment. The art of using daylighting in architecture is not only about allowing light into the space, but providing it without adverse effects. Despite these effects, life cannot continue without daylight, which is required for human health and, now more than ever, for energy-saving approaches.
Successful daylighting is not about increasing opening sizes or adding skylights. It encompasses thoughtful integration of design approaches addressing glare, heat gain, variation in light-
50 Ander, Daylighting Performance and Design, 27. 55
availability, and direct light penetration. However, in the context of this thesis, only variation in light level, luminous distribution, and penetration depth are tested with different daytime scenarios.
The benefits of a well-designed daylighting concept in office spaces range from better productivity, due to enhanced daylighting quality inside the space, to reduced consumption of artificial lighting. A well-designed space should be able to optimally utilize solar energy through controlling and harvesting daylight. Taking into account the limitations of passive daylight strategies, successful daylight design in office buildings requires going beyond conventional techniques of integrating large openings or light shelves in the architecture. It requires a system that is capable of accounting for unforeseen changes in natural lighting. These changes can range from external elements like reflections from surrounding context, to internal factors like interior surface reflections or changing occupants’ activities that require different illumination schemes.
3.2. DAYLIGHT REWARDS
3.2.1 HUMAN HEALTH AND PRODUCTIVITY
Despite the excessive use of artificial light in architecture, people still appreciate the natural gift of daylight, acknowledging its advantages. Natural lighting has always been an important design feature in the building design field. Besides providing a connection to the outdoor environment, it is as vital an element for maintaining human physical health as it is to plant life. Natural light 56
can bring happiness to a space and make people escalate the value of their presence. It also results in an environment with dynamic light conditions, unlike one lit artificially.
Daylight strategies are crucial for sustaining human health, work productivity and a pleasing work environment. There is a disconnection in office architecture and daylighting design which has an extensive impact on inhabitants, affecting body health, productivity, and visual comfort. Such problems arise due to the lack of daylight inside a space, and the extreme reliance on electric light. Most people perceive daylit environments as pleasant spaces for work. In 2003, a student at the Rensselaer Polytechnic Institute carried out a survey of measured negative mood under different daylight conditions. Dasgupta was able to show that, while people working for 20 minutes in an office with a large window during daytime showed a small but significant reduction in negative mood, workers in the same office space during nighttime had no change in their negative mood.51
In his book, Koster briefly explained the influence of daylighting on human physiology and psychology. The following quote explains how important natural light is to human health:
Light synchronizes the human biological clock with day, night and seasonal rhythms. A lack of natural daylight can lead to disorders of the automatic nervous system, loss of energy, fatigue, a tendency towards self-isolation and metabolic disorders. Conversely, intensive light therapy has been shown to support the healing process.52
51 Dasgupta, The Impact of Windows on Mood and Performance of Judgmental Tasks.
52 Koster, Dynamic Daylighting Architecture, 57. 57
3.2.2 INDIVIDUAL OUTCOMES
In 1996, Veitch and Newsham proposed that lighting quality can be defined as the degree to which the luminous environment supports the following requirements of the people who use the space (Figure 3-2):
 Visual performance;
 Post-visual performance (task performance and behavioral effects other than vision);
 Social interaction and communication;
 Mood state (happiness, alertness, satisfaction, preference);
 Health and safety;
 Aesthetic judgments (assessments of the appearance of the space or the lighting).
58
Figure 3-2: Qualities of lighting – Veitch’s proposal determines the quality of lighting in any given installation through determining the balance of the (sometimes conflicting) dimensions shown in the diagram.53
They also added that the qualities mentioned above do not allow direct measurement of daylighting, but express an emergent state that is created between the occupant in the environment and the light. According to their report, good lighting quality exists when a lighting system creates good conditions for seeing, supports task performance or setting-appropriate behaviors, fosters desirable interaction and communication, contributes to appropriate mood, provides good conditions for health and avoids ill effects, and contributes to the aesthetic appreciation of the space.54
53 Veitch, “Psychological processes influencing lighting quality,” 19.
54 Veitch, J. A, Determinants of Lighting Quality I. 59
Figure 3-3: Individual Outcome – the influence of various factors, including lighting conditions, on the individual outcome.55
3.2.3 ENERGY USAGE
Lighting accounts for 30-50% of the energy use in commercial buildings.56 Significant energy-savings can be obtained if daylight strategies are incorporated into the architecture, primarily for use during daytime when sunlight is available and the use of artificial light is unnecessary.
Daylight design strategies can reduce the extensive use of electric light inside office spaces if well designed, as well as indirectly increasing savings due to changes in thermal loads. Controlling sunlight penetration into a space is a broad strategy that not only guarantees
55 Veitch, “Psychological processes influencing lighting quality,” 20.
56 Phillips, Daylighting, 38. 60
adequate light levels, but also reduces solar heat gain, which is preferred in hot climates. However, savings vary by building orientation, season, and façade design.
The Environment Department of Great Britain carried out a comparative study on various façade types (Figure 3-4). The study shows room for decreasing lighting loads through the design of better performing façades. Lighting needs for a cellular plan are the least significant, while an open office space required a greater lighting load for a better work environment. In cellular plans, more vertical surfaces could be used to bounce light and provide more illumination, which is not the case in open offices. Adding movable reflective surfaces on façades could be a good solution for open space offices.
While a passive system can result in considerable energy savings, active approaches can go beyond these conventional numbers, simply because they are capable of adapting to the major source of daylight - the sun - which is a dynamic natural force that changes location over the course of the day. 61
Figure 3-4: Energy Usage in Offices – the breakdown of energy usage costs, including lights, for typical and good practice offices.57
3.3. DAYLIGHT FUNDAMENTALS
3.3.1 SOURCE OF LIGHT
Daylight, an important requisite in office buildings for efficient task execution and a satisfying visual working environment, is usually a combination of direct sunlight, diffuse light from the
57 Koster, Dynamic Daylighting Architecture, 23. 62
sky, and light bounced off surfaces. One can distinguish daylight sources into two main types: primary sources, and secondary sources. Primary sources are sources that release light like the sun and sky, while secondary sources are sources that reflect light but do not produce it, like surfaces and objects.
Sunlight passes through various layers in the atmosphere before hitting the built environment. The intensity of solar radiation is dependent on various factors, among which are the sun’s position, clouds, gaseous and particulate pollution, and thickness of the air mass (Figure 3-5). Daylight delivers full-spectrum light for flawless color rendering, as well as providing the best visual conditions in a luminous environment for the human eye.
Figure 3-5: Atmosphere Layers – the layers through which light passes before arriving on the work plane.58
58 Baker and Steemers, Daylight Design of Buildings, 31. 63
Considered a secondary source of daylight, surfaces are the surrounding context, including the ground and neighboring façades, and interior surfaces in the space. The finish material of each surface affects the amount of light bounced off of it. The brighter the surface, the more light is bounced off. Therefore, daylight at a point in a space is composed of the following components:
 Direct sunlight (in the case of a clear sky and no blockage);
 Diffused light from the sky;
 Externally reflected components;
 Internally reflected component.
Considered the only source of natural light, the sun has high luminous efficacy. On a clear day, direct sunlight can illuminate a horizontal plane up to 10000 foot-candles. On an overcast day, sky luminance may reach up to 20,000 cd/m2, while the luminance of a clear sky reaches 50,000 cd/m2.59
3.3.2 PROPERTIES OF DAYLIGHT
Visual and thermal problems always accompany the penetration of daylight into a space, and are perceived by occupants as unfavorable luminous and thermal conditions. Insufficient lighting, illumination beyond recommended ranges, or direct sunlight falling on working planes are among the major problems caused by daylighting. More problems are addressed in terms of characteristics or variables (Figure 3-6), thereby controlling the quality of the luminous environment. Each parameter is looked at as a design problem that results in an adverse condition, requiring the adoption of design strategies to overcome it.
59 Koster, Dynamic Daylighting Architecture, 54. 64
Figure 3-6: Daylighting Characteristics – the characteristics of daylighting that have impact on occupants’ productivity and visual comfort in indoor spaces
Within the scope of the study, the two main factors that are tested are the exterior dynamic-intelligent skin that harvests and controls the penetration and direction of light, and the complex panel geometry. The conventional horizontal louver linked to an intelligent system is the first phase of the study, while the second phase tests various panel geometries linked to the same system of a real-life building.
Within the context of this research, the quality of daylight in a space is addressed through three main aspects: the illumination levels range, the light penetration depth, and the luminous distribution in the space. In office buildings, the use of daylighting has a considerable impact on the energy consumption of the building. However, flooding the space with daylight neither achieves the recommended illumination range nor provides a good visual environment. It may
INDOOR DAYLIGHTING CHARACTERISTICS
Brightness
Luminous Distribution
(Quality)
Colour
Glare and Veiling Reflections
Visual Contact with Outdoor Environment
Individual Control 65
result in over-illuminating the space, leading to many visual, thermal and energy problems. Daylight harvesting strategies may efficiently control the penetration of light into the space, controlling the quality of the luminous environment accordingly.
3.3.3 FORM AND ORIENTATION
Orienting a building in relation to the surrounding context and the known path of the sun is a crucial concern in the design process, allowing the designer to either let more light into the space, or to prevent it (Figure 3-7). There are different techniques for controlling light amounts in spaces, among which horizontal and vertical fins are the most famous. Though they have been very successful in solar shading and light deflection throughout the past decades, designers are rethinking this technique with an eye to using advanced integrated technology. While vertical fins are efficient blockers on east and west façades, where the sun angle is low, horizontal panels are the most effective for south-facing spaces, due to high-angle sun. These strategies are commonly known, because of the constant path of the sun, which moves in the same route every day, every month, and every year.
66
Figure 3-7: Building form and orientation – various building forms and orientations, and their impact on daylight penetration into the space.60
Building form determines the surface area exposed to the outdoor. The more compact the building plan, the less daylit space exists (Figure 3-7). The depth of the plan and section determines how deep the light will penetrate into the space. As shown in Figure 3-7, a north-south orientation has a deep width, which minimizes the penetration of sunlight into the space. Conversely, an east-west orientation has a shorter width, allowing sunlight to hit most of the indoor space. Generally, orienting the longer side of the building towards the sun is a favorable idea. Also, the use of courtyards produces greater light-deflection on the building exterior surfaces, and directs light into more space. This strategy also increases the perimeter of the building that is exposed to sunlight.
60 Ibid., 69. 67
Figure 3-8: Sun path diagram – the annual sun path for Los Angeles. The high-angle sun represents August, while the low-angle sun reflects the sun location in December, both on the same day, at the same time.
Given that the path of the sun is precisely known, designers are able to calculate the altitude and azimuth of the sun on any specific date and time in any location worldwide (Figure 3-8). They can predict the best building orientation, and generate diagrams displaying the sun’s location and annual shading range. Using numbers from the charts, equations, and tables, the amount of illumination inside a space can be manually calculated. The fluctuation of the amount of sunlight hitting a space is dependent on the orientation of space, location, and month, day and time of the year. During the summer, a larger surface area of a building is exposed to the sun - represented by the blue line on the horizontal plane in Figure 3-8, while the red line, representing the sun range during the winter, has a shorter period.
3.3.4 INTERNAL FACTORS IMPACT
In addition to the external factors mentioned above, lighting design is directly related to some internal parameters which are present inside a space itself. Manipulating these parameters changes the quality of the interior luminous environment. Required illumination differs 68
according to task; the more complex a task, the more light is likely to be required. Given that light in general office spaces is task-oriented, all parameters of task execution should be precisely defined. Some of these parameters are known and unlikely to change, like the working plan of a computer desk - which is always around 2’ 7” (90 cm). Illumination levels are also dependent on materials - specifically surface reflectance, dirt accumulation, and room dimensions. These factors should be defined prior to beginning the design process. Furniture distribution in relation to glazing location is crucial in daylighting. A favorable practice for designing is to change one variable at a time, and in this study furniture has been omitted from the simulation, for quick-easier runs, intending to bring as much surface area as possible into desired conditions, regardless of the occupancy status.
3.4. PERFORMANCE INDICATORS
3.4.1 PREVIOUS WORK
In section 3.2.1, the importance of daylighting to human health was highlighted as a necessary requisite for a better, more productive work environment, and greater energy savings. However, there are no exact measurements that can directly quantify this impact. Several studies on the topic of daylight quality and performance have been conducted in the past ten years. Several research labs dedicated sections to lighting research, including daylighting. Various studies showed different assessment criteria for the quality of daylight inside a spac