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Post-treatment analysis of the glare remediation of the Walt Disney Concert Hall

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Post-treatment analysis of the glare remediation of the Walt Disney Concert Hall

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Content POST-TREATMENT ANALYSIS OF THE GLARE REMEDIATION
OF THE WALT DISNEY CONCERT HALL

by

Jae Yong Suk

A Thesis Presented to the
FACULTY OF THE SCHOOL OF ARCHITECTURE
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF BUILDING SCIENCE

May 2007

Copyright 2007 Jae Yong Suk
ii
DEDICATION

To my wife Kyung-Mi, for all of her love and supports,
to my parents, and to my brother’s family.
iii
ACKNOWLEDGEMENTS
I would like to express my gratitude to all the people who helped me to successfully
complete this thesis. Without their help and efforts, I would never have been able to
finish this work. I would like to extend my deepest thanks to Professor Marc Schiler,
the chair of my thesis committee members, for his precious guidance and endless
encouragement during the entire process. Also thanks to my committee members,
Professor Edwin Woll, Professor Karen Kensek and lighting designer Teal Brogden,
who shared their professional knowledge and valuable time with me and gave great
advice to me.
Thanks to USC School of Architecture and to JELD-WEN for awarding me GRS
scholarship and Architectural Scholarship. With the great financial supports from
them, I could focus on my thesis and other research works in MBS program. My
gratitude goes to Professor Doug Noble and all of MBS teammates, Tareq, Sandy,
Othman, Chris, and Jason, who encouraged me in completing the thesis.
Again, I would like to thank my parents for their immense support and love all
through my life.
iv
TABLE OF CONTENTS

Dedication ………………………………………………………………………... ii

Acknowledgements ………………………………………………………………. iii

List of Tables ……………………………………………………………………... vii

List of Figures ……………………………………………………………………. viii

Abstract …………………………………………………………………………... xiv

Chapter 1: Introduction of the Walt Disney Concert Hall Glare Problems ……….. 1
1.1 The Walt Disney Concert Hall …………………………………………. 1
1.1.1 History of the Walt Disney Concert Hall ………………………... 2
1.1.2 Icon of Los Angeles ……………………………………………... 4
1.1.3 How has this building affected neighbors? ……………………… 4
1.1.4 Rumors …………………………………………………………... 8
1.2 Discomfort Glare ……………………………………………………….. 8
1.2.1 Introduction to Glare …………………………………………….. 9
1.2.2 Different Types of Glare ………………………………………... 10
1.2.3 Definition of Discomfort Glare ………………………………… 11
1.2.4 Common Methods of Evaluating Glare ………………………... 12
1.3 Heat Island Effect (Environmental Warming) ………………………… 12
1.3.1 Introduction of Microclimate …………………………………... 13
1.3.2 What is Overheating? …………………………………………... 14
1.3.3 Common Methods of Evaluating Temperature ………………… 15

Chapter 2: Background of Visual and Thermal Glare Analysis ………………….. 17
2.1 The Elements of Discomfort Glare …………………………………… 17
2.1.1 Luminance and Illuminance ……………………………………. 17
2.1.2 Brightness Levels ………………………………………………. 19
2.1.3 Contrast (Brightness Difference) ………………………………. 20
2.1.4 The Field of View ………………………………………………. 20
2.1.5 Visual Adaptation ………………………………………………. 22
2.1.6 Reflection and Distribution …………………………………….. 23
2.1.7 Reflectance of Materials ……………………………………….. 25
2.1.8 Vertical Surfaces ……………………………………………….. 26
2.2 Existing Discomfort Glare Analysis Methods ………………………... 27
2.2.1 The Daylight Glare Index Method ……………………………... 27
2.2.2 The Visual Comfort Probability Method ………………………. 28
2.2.3 The Unified Glare Rating Method ……………………………... 29
2.2.4 The Relative Visual Performance Method ……………………... 30
v
2.2.5 The Video Photometry Method ………………………………… 31
2.2.6 The Schiler Glare Method ……………………………………… 32
2.2.7 The Daylight Glare Probability Method ……………………….. 32
2.3 The Elements of Thermal Glare Effect …………………...…………... 34
2.3.1 Heat Transfer …………………………………………………… 34
2.3.2 Heat Capacity …………………………………………………... 35
2.3.3 Emissivity ……………………………………………………… 37
2.3.4 Emittance ………………………………………………………. 37
2.3.5 Solar Reflectance ………………………………………………. 37
2.3.6 Transmittance …………………………………………………... 38
2.4 Existing Thermal Glare Analysis Methods …………………………… 39
2.4.1 Datalogger ……………………………………………………… 39
2.4.2 Infrared Thermometer ………………………………………….. 39
2.5 Remediation of the Walt Disney Concert Hall ………………………... 40
2.5.1 Previous Research on Disney Hall ……………………………... 40
2.5.2 Previous Research Results ……………………………………... 41
2.5.3 Resolutions ……………………………………………………... 42

Chapter 3: Visual Glare Research ………………………………………………... 45
3.1 Research Strategies for Visual Glare ………………………………….. 45
3.1.1 Lighting Analysis Software …………………………………….. 47
3.1.2 Variables to be considered in the new study …………………… 47
3.1.3 Fields of views from Four Intersections ……………………….. 49
3.1.4 Process of Photographing Disney Hall …………………………. 50
3.1.5 Pictures of Disney Hall ………………………………………… 52
3.2 Visual Glare Research Results ………………………………………... 57
3.2.1 Photoshop ………………………………………………………. 57
3.2.2 RASCAL and CULPLITE ……………………………………... 59
3.2.3 Schiler Glare Rating ……………………………………………. 62
3.2.4 Luminance Histograms ………………………………………… 64
3.2.5 The Schiler Glare Scores ……………………………………….. 69
3.3 Results Comparison between Previous and Current Research ………... 72
3.4 Problems ………………………………………………………………. 75

Chapter 4: Camera Test …………………………………………………………... 76
4.1 Camera Test Strategy ………………………………………………….. 76
4.1.1 Components of the Camera Test ……………………………….. 76
4.1.2 Photographing ………………………………………………….. 78
4.2 Camera Test Results …………………………………………………... 78
4.2.1 Pictures of Automatic Cameras ………………………………… 78
4.2.2 Pictures of Nikon D200 ………………………………………… 81
4.2.3 Luminance Histograms of Automatic Camera Pictures ………... 86
4.2.4 Luminance Histograms of Nikon D200 Pictures ………………. 88
4.2.5 Glare Score Comparisons ………………………………………. 92
vi
Chapter 5: Thermal Glare Research ……………………………………………… 94
5.1 Research Strategies for Thermal Glare ……………………………….. 94
5.1.1 The Components of Thermal Glare Research ………………….. 95
5.1.2 Location Selection ……………………………………………… 96
5.1.3 Normalization …………………………………………………... 97
5.1.4 Installation of Dataloggers ……………………………………... 99
5.1.5 Data Logging ………………………………………………….. 100
5.1.6 Infrared Thermometer Measurement ………………………….. 101
5.2 Thermal Glare Research Results …………………………………….. 103
5.2.1 Ground Temperature Data …………………………………….. 103
5.2.2 Mid-air Temperature Data …………………………………….. 118
5.3 Results Comparison between Previous and Current Research ………. 120
5.3.1 Comparison Charts of Ground Temperature ………………….. 120
5.3.2 Comparison Data of Mid-air Temperature ……………………. 123
5.4 Problems ……………………………………………………………... 124

Chapter 6: Conclusions …………………………………………………………. 126
6.1 Visual Glare Issue ……………………………………………………. 126
6.1.1 Disney Hall Glare Research Conclusion ……………………… 126
6.1.2 Camera Test Conclusion ………………………………………. 128
6.2 Thermal Glare Issue ………………………………………………….. 128
6.2.1 Ground Temperature Research Conclusion ………………….... 129
6.2.2 Mid-air Temperature Research Conclusion ………………….... 131

Chapter 7: Future Work …………………………………………………………. 133
7.1 Recording Temperature inside the Promenade condominiums ……… 133
7.2 Manual Camera Test for Visual Glare Analysis …………………….... 134
7.3 Measurement of Actual Luminance for Absolute Glare ……………... 135

Bibliography …………………………………………………………………….. 137

Appendices
Appendix A …………………………………………………………………. 140
Appendix B …………………………………………………………………. 142
Appendix C …………………………………………………………………. 154
Appendix D …………………………………………………………………. 159
vii
LIST OF TABLES

Table 2. 1: Reflectance of Materials …………………………………………. 25

Table 2. 2: UGR index ……………………………………………………….. 30

Table 2. 3: Specific heat capacity of building materials …………………….. 36

Table 3. 1: Glare scores of four intersections_2004 …………………………. 70

Table 3. 2: Glare scores of four intersections_2006 …………………………. 71

Table 4. 1: Glare score comparison table ……………………………………. 93

viii
LIST OF FIGURES

Figure 1. 1: Walt Disney Concert Hall ………………………………………... 2

Figure 1. 2: Map of Los Angeles Downtown …………………………………. 3

Figure 1. 3: Promenade condominiums ………………………………………. 5

Figure 1. 4: Glare on Promenade condominiums …………………………….. 6

Figure 1. 5: Glare from Founders Room ……………………………………… 7

Figure 1. 6: Urban Heat Island Profile ………………………………………. 13

Figure 2. 1: Basic properties of light ………………………………………… 18

Figure 2. 2: Brightness Levels ………………………………………………..19

Figure 2. 3: Brightness Differences ………………………………………….. 20

Figure 2. 4: Sketch of Binocular visual field ………………………………... 21

Figure 2. 5: Diagram of Foveal vision ………………………………………. 22

Figure 2. 6: Brightness Adaptation (Brightness to which eye is adapted.
Influenced by all areas in the field of view) ……………………. 23

Figure 2. 7: Specular, spread, and diffuse reflections ……………………….. 24

Figure 2. 8: Diagram of vertical surfaces ……………………………………. 26

Figure 2. 9: Correlation between the new DGP formula and the probability
of disturbed persons in the tests ………………………………... 33

Figure 2. 10: Heat transfer …………………………………………………... 35

Figure 2. 11: Diagram of transmittance ……………………………………... 38

Figure 2. 12: Polished stainless steel of REDCAT Marquee before
the remediation …………………………………………………. 41

Figure 2. 13: Temporary fabric cover on Founders Room …………………... 43

ix
Figure 2. 14: Orbital sanding on Founders Room …………………………… 44

Figure 3. 1: Sun path diagram ……………………………………………….. 46

Figure 3. 2: Photographs from four intersections ……………………………. 49

Figure 3. 3: Photographing from 1
st
Street and Grand Avenue …………….... 50

Figure 3. 4: Photographing from 2
nd
Street and Grand Avenue ……………... 51

Figure 3. 5: Photographing from 1
st
and Hope Streets ………………………. 51

Figure 3. 6: Photographing from 2
nd
and Hope Streets …………………….... 51

Figure 3. 7: 1
st
Street and Grand Avenue from 6:30 AM to 10:00 AM …….... 53

Figure 3. 8: 2
nd
Street and Grand Avenue from 6:30 AM to 10:00 AM ………54

Figure 3. 9: 1
st
and Hope Streets from 2:30 PM to 6:00 PM ……………….... 55

Figure 3. 10: 2
nd
and Hope Streets from 2:30 PM to 6:00 PM ……………..... 56

Figure 3. 11: Diagram of visual glare analysis process ……………………… 57

Figure 3. 12: Adobe Photoshop ……………………………………………… 59

Figure 3. 13: RASCAL software …………………………………………….. 60

Figure 3. 14: CULPLITE software …………………………………………... 62

Figure 3. 15: Luminance histogram of 1
st
Street and Grand Avenue
at 5:00 PM ……………………………………………………… 65

Figure 3. 16: Luminance histogram of 2
nd
Street and Grand Avenue
at 7:30 AM ……………………………………………………… 66

Figure 3. 17: Luminance histogram of 1
st
and Hope Streets at 6:00 PM ……. 67

Figure 3. 18: Luminance histogram of 2
nd
and Hope Streets at 6:00 PM ….... 68

Figure 3. 19: Glare score comparison chart between 2004 and 2006
from 1
st
Street and Grand Avenue …………………………….... 72

x
Figure 3. 20: Glare score comparison chart between 2004 and 2006
from 2
nd
Street and Grand Avenue ………………………………73

Figure 3. 21: Glare score comparison chart between 2004 and 2006
from 1
st
and Hope Streets ………………………………………. 74

Figure 3. 22: Glare score comparison chart between 2004 and 2006
from 2
nd
and Hope Streets …………………………………….... 74

Figure 4. 1: Automatic cameras ……………………………………………… 77

Figure 4. 2: Nikon D200 …………………………………………………….. 77

Figure 4. 3: Glare on DWP building with four automatic cameras ………….. 79

Figure 4. 4: REDCAT marquee with four automatic cameras ………………. 80

Figure 4. 5: Founders Room with four automatic cameras ………………….. 81

Figure 4. 6: DWP taken by Nikon D200 …………………………………….. 83

Figure 4. 7: REDCAT marquee taken by Nikon D200 ……………………… 84

Figure 4. 8: Founders Room taken by Nikon D200 …………………………. 85

Figure 4. 9: Luminance histograms of DWP ………………………………… 87

Figure 4. 10: Luminance histograms of REDCAT …………………………... 87

Figure 4. 11: Luminance histograms of Founders Room ……………………. 88

Figure 4. 12: Luminance histograms of DWP with Nikon D200 ……………. 89

Figure 4. 13: Luminance histograms of REDCAT with Nikon D200 ……….. 90

Figure 4. 14: Luminance histograms of Founder’s Room with Nikon D200 .. 91

Figure 5. 1: iButtons and Raytek infrared thermometer …………………….. 95

Figure 5. 2: Thermal glare research scope …………………………………... 96

Figure 5. 3: Exact locations of nine data loggers ……………………………. 97

Figure 5. 4: Normalization results with 10 dataloggers ……………………... 98
xi
Figure 5. 5: Embedded datalogger on the road ……………………………… 99

Figure 5. 6: Two installed dataloggers on sidewalk ………………………....100

Figure 5. 7: Measuring focal point temperature at mid-air …………………. 102

Figure 5. 8: Temperature data from 10/18/2003 to 11/03/2003 …………….. 104

Figure 5. 9: Temperature data from 07/11/2004 to 07/17/2004 …………….. 105

Figure 5. 10: Temperature data from 08/30/2006 to 09/16/2006 …………… 106

Figure 5. 11: Temperature data from 09/17/2006 to 10/07/2006 …………… 107

Figure 5. 12: Three days temperature pattern from 09/23/2006
to 09/25/2006 ………………………………………………….. 108

Figure 5. 13: Temperature data from 10/08/2006 to 11/08/2006 …………… 109

Figure 5. 14: Three days temperature pattern from 10/21/2006
to 10/23/2006 ………………………………………………….. 110

Figure 5. 15: Temperature data from 11/04/2006 to 12/01/2006 …………… 111

Figure 5. 16: Three days temperature pattern from 11/18/2006
to 11/20/2006 ………………………………………………….. 112

Figure 5. 17: Temperature data from 12/02/2006 to 01/06/2007 …………… 113

Figure 5. 18: Three days temperature pattern from 12/18/2006
to 12/20/2006 ………………………………………………….. 114

Figure 5. 19: Temperature data from 01/07/2007 to 02/02/2007 …………… 115

Figure 5. 20: Three days temperature pattern from 01/23/2007
to 01/25/2007 ………………………………………………….. 116

Figure 5. 21: Temperature data from 02/03/2007 to 03/02/2007 …………… 117

Figure 5. 22: Three days temperature pattern from 02/16/2007
to 02/18/2007 ………………………………………………….. 118

Figure 5. 23: Infrared thermometer measurement results …………………... 119

xii
Figure 5. 24: Location #03- Peak temperature comparison
between 2003 and 2006 ……………………………………….. 121

Figure 5. 25: Location #04- Peak temperature comparison
between 2003 and 2006 ……………………………………….. 121

Figure 5. 26: Location #06- Peak temperature comparison
between 2003 and 2006 ……………………………………….. 122

Figure 5. 27: Location #07- Peak temperature comparison
between 2003 and 2006 ……………………………………….. 123

Figure A. 1: Datalogger locations on March, 2003 ………………………… 140

Figure A. 2: Datalogger locations on July, 2004 …………………………… 141

Figure B. 1: 1
st
Street and Grand Avenue from 6:30 AM to 10:00 AM …….. 142

Figure B. 2: 1
st
Street and Grand Avenue from 10:30 AM to 2:30 PM …….. 143

Figure B. 3: 1
st
Street and Grand Avenue from 3:00 PM to 5:00 PM ………. 144

Figure B. 4: 2
nd
Street and Grand Avenue from 6:30 AM to 10:00 AM …..... 145

Figure B. 5: 2
nd
Street and Grand Avenue from 10:30 AM to 2:00 PM ……. 146

Figure B. 6: 2
nd
Street and Grand Avenue from 2:30 PM to 6:00 PM ……… 147

Figure B. 7: 1
st
and Hope Streets from 6:30 AM to 10:00 AM …………….. 148

Figure B. 8: 1
st
and Hope Streets 10:30 AM to 2:00 PM ………………….... 149

Figure B. 9: 1
st
and Hope Streets from 2:30 PM to 6:00 PM ………………. 150

Figure B. 10: 2
nd
and Hope Streets from 6:30 AM to 10:00 AM …………... 151

Figure B. 11: 2
nd
and Hope Streets from 10:30 AM to 2:00 PM ………….... 152

Figure B. 12: 2
nd
and Hope Streets from 2:30 PM to 6:00 PM …………….. 153

Figure C. 1: Image analysis procedure manual, page 1 …………………….. 154

Figure C. 2: Image analysis procedure manual, page 2 …………………….. 155

xiii
Figure C. 3: Image analysis procedure manual, page 3 …………………….. 156

Figure C. 4: Image analysis procedure manual, page 4 …………………….. 157

Figure C. 5: Image analysis procedure manual, page 5 …………………….. 158

Figure D. 1: Ground temperature from 08/30/2006 to 09/16/2006 ………… 159

Figure D. 2: Ground temperature from 09/16/2006 to 10/08/2006 ………… 160

Figure D. 3: Ground temperature from 10/08/2006 to 11/04/2006 ………… 161

Figure D. 4: Ground temperature from 11/04/2006 to 12/02/2006 ………… 162

Figure D. 5: Ground temperature from 12/02/2006 to 01/07/2007 ………… 163

Figure D. 6: Ground temperature from 01/07/2007 to 02/03/2007 ………… 164

Figure D. 7: Ground temperature from 02/03/2007 to 03/03/2007 ………… 165

xiv
ABSTRACT

This thesis further develops research undertaken about the Walt Disney Concert
Hall. Originally admired for its beautiful, shiny, curved façade, the concert hall was
also noteworthy as a source of visual glare and heat. These concerns led to the
County of Los Angeles hiring of a consultant to quantify the problems and suggest
resolutions. The solution undertaken was to sand key problem areas of the stainless
steel façade. After this treatment, complaints stopped, but no one tested the actual
resulting levels of thermal and visual glare. This study re-examines these issues after
the surface treatment. An infrared thermometer and dataloggers were used to record
mid-air temperature and ground temperature in front of the adjoining REDCAT
theater. Using photographs of Disney Hall and luminance histograms, visual glare
scores were evaluated. The comparison between previous and current research
results tells whether or not the remediation was successful to reduce the glare
problems.
1
CHAPTER 1
INTRODUTION OF THE WALT DISNEY
CONCERT HALL GLARE PROBLEMS

The Disney Concert Hall in downtown Los Angeles, California, was designed by
world famous architect Frank Gehry. Since its grand opening in fall of 2003, it has
drawn both compliments and criticism for its unique shapes. This chapter is going to
explain some of the environmental issues surrounding this building.

1.1. The Walt Disney Concert Hall
The Walt Disney Concert Hall is the fourth building of the Los Angeles Music
Center complex. Bounded by Hope Street, Grand Avenue, 1
st
, and 2
nd
Streets, it has a
state-of-the-art 2,265 seat auditorium that serves as the home for the Los Angeles
Philharmonic Orchestra and the Los Angeles Master Chorale. Frank Gehry, an
architect known for his swooping shapes and eye-catching shiny materials in
building skin, designed the building. The Walt Disney Concert Hall opened on
October 23, 2003 with a concert by the Los Angeles Philharmonic.

Figure 1. 1: Walt Disney Concert Hall

1.1.1. History of the Walt Disney Concert Hall
The Disney Hall project was launched in 1987 when Lillian Disney, the widow of
Walt Disney, donated 50 million dollars to the Music Center of Los Angeles County
to build a world-class performance space for the Los Angeles Philharmonic. Frank
Gehry was selected to design this project in 1988. Los Angeles County donated a
block of land and promised to finance construction of a six-level subterranean
parking garage, which cost an estimated 90 to 110 million dollars. Construction of
the underground parking garage began in 1992 and was successfully completed in
1996.

2
However, cost overruns, alleged mismanagement, and design disagreements delayed
the project until after the Gehry-designed Bilbao Guggenheim Museum was
successfully completed in 1997. The success of Guggenheim Museum suggested
solutions to the engineering and design problems of the Disney. The budget
difficulties were resolved through additional contributions from the late Lillian
Disney and the Disney family, the County of Los Angeles, the State of California,
and the generous support of corporations, foundations and individuals. Construction
of Disney Hall began in November 1999 and was completed in October 2003. Upon
completion in 2003, the project had cost an estimated total $274 million, including
the parking garage. From design start in 1987, to construction start in 1999, to the
inauguration in 2003, the project took sixteen years to complete.

Figure 1. 2: Map of Los Angeles Downtown (MapQuest)
3
4
1.1.2. Icon of Los Angeles
“The Walt Disney Concert Hall will be a feast for your eyes, ears, and spirits.”, per
Gil Garcetti, LA’s district attorney, who photographed Disney Hall.
“It is a serene, ennobling building that will give people in this city of private places a
new sense of the pleasure of public space.”, per Paul Goldberger, architecture critic
at The New York Times.
“Harmonious and incomparably beautiful, the colors changing depending on where
the sun is,” another critic said.

Located on a historically and culturally prominent downtown site, the Walt Disney
Concert Hall has become the permanent home of the Los Angeles Philharmonic.
Since its opening in 2003, the Walt Disney Concert Hall has been greatly successful.
Concerts have been selling out, and many critics have swooned over architect Frank
Gehry’s design. In addition to its unique building shapes, Disney Hall is also well
known as one of the most acoustically sophisticated concert halls in the world,
providing both visual and aural intimacy for an unparalleled musical experience.
This building has attracted tourists from all over the world. In many respects it could
be considered a great accomplishment.

1.1.3. How has this building affected neighbors?
Although this building has drawn many compliments, not everyone is happy with its
environmental impact. Some portions of the Disney Hall’s exterior have produced
glare and hot spots for its neighbors, for drivers, and for pedestrians. The
homeowners’ association at the neighboring Promenade condominiums complained
that reflected sunlight from the Disney Hall caused uncomfortable glare and
increased temperatures inside some units (Janssen 2004, p.1).

Figure 1. 3: Promenade condominiums

“You couldn’t even see, and then the furniture would get really hot,” said Jacqueline
Lagrone, 42, who lives in the fourth floor of the Promenade condominiums. “You
would have to literally close the drapes, and you’d still feel warmth in the house. You
would have the air conditioning on all the time.” (Glaister 2004)
“It does get really, really warm in the summer,” said Susan Yokoyama who is a co-
owner of the Video Action store at the Promenade Plaza across the street from the
hall. “It’s like a heater. It’s like sitting in a sauna. It can also be quite blinding.”
(BoiFromTroy 2004)

5

Figure 1. 4: Glare on Promenade condominiums (Schiler 2004, p.2)

Throughout one summer, passing drivers reported being distracted by the reflected
rays from the Disney Hall, while pedestrians described having to cross the street to
avoid the intense heat. Figure 1.5 shows a strong glare spot on the middle of
Founders Room.

6

Figure 1. 5: Glare from Founders Room (Schiler 2004, p.1)

Even though the Disney Hall case is still really famous to lots of people, it is not a
unique case of glare problems in the world. South Korea had a similar case to Disney
Hall glare problems about 20 years ago. After completion of Lotte World, a huge
amusement park in Seoul, the residents of neighboring apartment buildings got
radiant heat and discomfort glare from its big glass dome. A study was carried out to
evaluate the level of glare and heat problems. The researchers surveyed how many
residents were feeling uncomfortable due to increased temperature and blinding
glare: the final report said that the problems were quite serious. Finally, most of the
residents got financial compensation from the owner of the building.
7
8
1.1.4. Rumors
There were some interesting stories about Disney Hall. Some people said that traffic
cones that were located in front of REDCAT were melted by the heat from polished
stainless steel surfaces and that a trash bin in front of REDCAT was lit on fire due to
the focused heat from the REDCAT marquee. Another humorous story circulated
about an activist who used an unusual method to protest about the heat generated by
the Disney Hall – he roasted a hot dog on one of the wall surfaces. None of these
stories has been proven, but it is really obvious that there was some sort of problem
to make people feel concerned and uncomfortable. During this study, one of the
security guards at Disney Hall told the author that he had also heard all of these
stories.

1.2. Discomfort Glare
Glare is a common problem, due to exterior surface materials and interior lighting
design to highlight two examples. Architects, interior designers, and lighting
designers have repeatedly had trouble dealing with this issue in architectural projects.
For that reason, many researchers have tried to find out how we can evaluate this
problem and how we can prevent problem for building projects. Most of the previous
research was focused on how much glare would reduce occupants’ productivity
inside office areas. Nowadays more people are aware of the external glare problems
and understand how dangerous the problem can be. It is very important to understand

9
what glare is and to find out how we can be more careful when designing and
constructing buildings.

1.2.1. Introduction to Glare
Glare, the result of excessive absolute light levels or excessive contrast between
bright and dark areas in the field of view, can interfere with visual perception.
Discomfort glare can be uncomfortable and even painful, but does not significantly
reduce ability to perform visual tasks. It is influenced by brightness conditions within
the entire field of vision. Disability glare reduces the ability to perceive visual
information needed for task performance. It is influenced by object brightness (Egan
1983, p.31). Even though many people don’t know exactly what glare is, most
people have experienced the glare effect in our daily lives. Typically, contrast glare is
from a strong light source such as car headlights during driving at night or a glowing
light fixture in a dark room. We can also see contrast glare from specular building
skins such as glass and steel skins even during daytime. When we look at the bright
sun on the clear sky, we can experience absolute level glare. Light shining into the
eyes of pedestrians and drivers can obscure night vision for up to an hour after
exposure. Exterior glare is particularly an issue in road safety, as bright or badly
shielded light sources around roads may partially blind drivers or pedestrians
unexpectedly and contribute to accidents.

10
1.2.2. Different Types of Glare
Glare happens when our eyes have adjusted to a certain general brightness, then
suddenly some annoying, distracting, and sometimes blinding light strikes our visual
field. There are two different classification based on the sources of glare or the levels
of glare. With the sources of glare, we can divide glare into three categories: absolute
glare, contrast glare and veiling reflection. The levels of glare have generally been
divided into three categories: disability glare, discomfort glare, and veiling reflection.
These two classifications of glare are actually quite similar but not identical. The
following explains three categories defined by the levels of glare.

1. Disability glare describes effects such as being blinded by headlights of
oncoming cars when driving at night, with significant reduction in sight
capabilities.
2. Discomfort glare occurs when our eyes are impacted by an excessively bright
light in relation to the general brightness level. Direct afternoon sunlight through
windows is one of the common examples of discomfort glare inside buildings. It
is necessary to provide overhangs, fins, or blinds to avoid the penetration of
direct light and to control brightness and contrast inside the space. Another
example occurs with artificial lighting for building interiors. A poorly designed
exposed light fixture in a building interior may cause discomfort glare to the
occupant of the space. Instead of providing need light for the occupants, it causes
strain and pain in their eyes. Thus, it reduces their productivity and health.
11
Discomfort glare can be present in any degree of brightness without a loss in
ability to see, but when it grows to a degree that might reduce the ability to see
and cause temporary blindness, it is called disability glare.
3. A veiling reflection is a reflected light that veils or masks some of the
information we see. This type of glare often happens when we read a magazine
and some part of the page is veiled or masked by the reflection of light that
comes to our eyes. This type of glare can be avoided easily by changing the
angle of incidence or the light fixture placement (Tedjakusuma 2003, p.3).

1.2.3. Definition of Discomfort Glare
The nature of discomfort glare first occurs when our eyes are adapted to an overall
low light level. This means physically that the iris aperture is wide open to capture
more light coming into the eye. If there is a point light source whose brightness is
substantially greater than the overall brightness within the human visual field of view,
that light point source will effectively burn a hole or cause sensor damage at the
retina where it is focused. Technically, there is visual discomfort before the source
burns the hole. Thus, the eye attempts to protect itself from this phenomenon by
signaling visual discomfort and reacting to the bright light. As a result, we will make
an adjustment by squinting and/or turning away, trying to correct the environment.
Being exposed to discomfort glare for some period of time can reduce our
performance or productivity. We will have a hard time concentrating and will easily

12
get tired in doing our task. In some extreme cases, discomfort glare might cause
physical and psychological damage (Tedjakusuma 2003, p.9).

1.2.4. Common Methods of Evaluating Glare
There have been many different research projects to figure out how to evaluate glare.
Most existing glare research is based on consideration of size, luminance, the
number of glare sources, and the background luminance. So far, many studies have
been conducted inside a room with subjective research methods. These surveys were
performed to find out how many people were uncomfortable with glare. Thus, the
results of these tests could vary depending on each person’s eye sensitivity.
Another method used brightness contrast ratios between small areas and their
surroundings. Less than a ratio of 3:1 was considered glare free; 3:1 to 10:1
contained glare; and above 10:1 discomfort glare occurs and starts to become
problematic. Others argue t’hat this ratio is clearly not true and too simplistic in
explaining the phenomenon of discomfort glare. For instance, if we have a printed
black type on a white paper, the brightness contrast ratio is over 50 to 1. However,
we do not experience discomfort glare (Tedjakusuma 2003, p.4).

1.3. Heat Island Effect (Environmental Warming)
The term "heat island" refers to urban air and surface temperatures that are higher
than nearby rural areas. The increase of ambient urban air temperatures results
primarily from the replacement of vegetation with buildings, roads, and other heat-
absorbing infrastructure. Many cities and suburbs have air temperatures that are 2 to
10°F warmer than the surrounding natural land cover. Figure 1.6 shows a city's heat
island profile. It demonstrates how urban temperatures are typically lower at the
urban-rural border than in dense downtown areas. The graph also shows how parks,
open land, and bodies of water can create cooler areas. Elevated temperatures can
impact communities by increasing peak energy demand, air conditioning costs, air
pollution levels, and heat-related illness and mortality (Cleveland 2006). There can
also be very specific microclimate warming effects; this has been shown to be the
case for the Disney Concert Hall.

Figure 1. 6: Urban Heat Island Profile (Cleveland, 2006)

1.3.1. Introduction of Microclimate
A microclimate is a local external atmospheric zone where the climate differs from
the surrounding area. Microclimates exist near bodies of water that may cool the
13
14
local atmosphere, or in heavily urban areas where brick, concrete, and asphalt absorb
the sun's energy, heat up, and reradiate that heat to the ambient air. The area in a
developed industrial park may vary greatly from a wooded park nearby, as natural
flora in parks absorbs light and heat in plant leaves, while a building roof or parking
lot conducts heat back to the air (Wikipedia).

1.3.2. What is Overheating?
Local overheating usually occurs in cities because of buildings and infrastructure.
The reason the city is warmer than the country comes down to a difference between
the energy gains and losses of each region. There are several factors that contribute
to the relative warmth of cities:

1. Heat generated by city buildings and cars eventually makes its way into the
atmosphere. This heat contribution can be as much as one-third of that
received from solar energy.
2. The thermal properties of buildings add heat to the air by conduction. Tar,
asphalt, brick, and concrete absorb radiant gain and increase in temperature.
Different from these building materials, plants absorb radiant gain and
convert CO
2
to O
2
and evapotranspire in order to dissipate excess heat
without increasing in temperature.
3. The canyon structure that tall buildings create enhances the warming. During
the day, solar energy is trapped by multiple downward reflections off the
15
buildings while the infrared heat losses are reduced by re-absorption.
4. The urban heat island may also increase cloudiness and precipitation in the
city, as a thermal circulation sets up between the city and surrounding region
(Cleveland 2006).

Cities all over the world have been warming up in the summer over the years. Los
Angeles is a striking example of how a city was transformed into an urban heat
island. In the 1930s, Los Angeles was an area covered with irrigated orchards. The
high temperature in the summer of 1934 was 97°F. Then, as pavement, commercial
buildings, and homes replaced trees, Los Angeles warmed steadily, reaching 105°F
and higher in the 1990s (Pon 1999). A specific building such as Disney Hall might
also be a contributing factor in increasing heat gain to its neighbors and the ground.
There is some concern that urban heat island effect is also a contributor to global
warming.

1.3.3. Common Methods of Evaluating Temperature
Temperatures can simply be measured via a diverse array of sensors. Big differences
exist between different temperature sensor or temperature measurement device types.
In one classification system, they are broken into two groups: contact and non-
contact.

16
Contact temperature sensors measure their own temperature. One infers the
temperature of the object to which the sensor is in contact by assuming or knowing
that the two are in thermal equilibrium, that is, there is no further heat flow between
them.

Most commercial and scientific non-contact temperature sensors measure the thermal
radiant power of the infrared or optical radiation that they receive from a known or
calculated area on its surface, or a known or calculated volume within it. One then
infers the temperature of an object from which the radiant power that is assumed to
be emitted (some may be reflected rather than emitted). Sometimes the inference
requires a correction for the spectral emissivity of the object being measured.
Knowing how and when to apply a spectral emissivity correction is part of the
inference, too, and can introduce significant errors if not done correctly
(Temperatures.com).

This chapter has introduced general information about the Walt Disney Concert Hall
and its visual and thermal glare problems. The following chapter explains more
details about the elements and process of visual and thermal glare problems then
shows the research and the remediation applied on the Disney Hall to solve these
problems two years ago.
17
CHAPTER 2
BACKGROUND OF VISUAL AND THERMAL
GLARE ANAYLSIS

For a better understanding of the thermal and visual problems of Disney Hall, it is
necessary to figure out important levels of glare and to understand existing glare
analysis methods.

2.1. The Elements of Discomfort Glare
As previously introduced in chapter 01, there are several classifications of visual
glare. Based on types of glare, it is categorized into absolute glare, relative glare, and
veiling reflection. Based on levels of glare, it can be categorized into blinding glare,
disability glare, and discomfort glare. Among many types of glare, this study mostly
focuses on discomfort glare. The following are the crucial elements to cause
discomfort glare problems.

2.1.1. Luminance and Illuminance
Understanding the difference between luminance and illuminance is very important
to analyze discomfort glare. Luminance is often confused with the concept of
illuminance. Luminance (sometimes referred to as brightness) is measured brightness
which is also composed of a directional quantity. Specifically, luminance is defined
as the intensity of visible brightness of a source or surface in the direction of the
observer, divided by the area of the source or the surface seen. The units of
luminance are candelas per square foot which were previously known as
footlamberts.

Illuminance is the density of luminous flux incident on a surface. Illuminance is
measured in lumens per square foot, commonly referred to as the footcandles. One
footcandle is a quantity of light on 1ft
2
of surface area 1ft away from a light source of
the intensity of 1 cd (that is: one standard candle- which has a technical definition).
We don’t see footcandles (illuminance); when a surface is illuminated, we see the
light leaving the surface, defined as luminance (Egan 2002, p.86).

Figure 2. 1: Basic properties of light (Egan 2002, p.83)
18
2.1.2. Brightness Levels
The eye can detect brightness over a range of greater than a trillion (10
12
) to 1.
However, brightness perception is normally within a range of only 1000 to 1.
Apparent brightness is relative and subjective. For example, under identical
illumination gray paper viewed on a black surface appears brighter than gray paper
viewed on a white surface. Nonetheless, its measured brightness, called luminance,
in candelas per square foot or fL would be the same. The figure below shows that
brightness over 2000 fL or 650 cd/ft
2
causes eyes to blink or squint (Egan 2002,
p.21).

Figure 2. 2: Brightness Levels (Egan 2002, p.21)
19
2.1.3. Contrast (Brightness Difference)
Visual perception is based on the concept of contrast and other factors such as eye
adaptation, expectations, and experience. Contrast is the brightness difference
between the object being viewed and the immediate surroundings. The magnitude of
contrast in a space influences the mood and affects productivity. Higher contrast
actually helps us gain better visual performance. However, visual glare problem also
may occur because too much contrast or too high luminance is involved. For
comfortable contrast in most situations, brightness difference should be within the
allowable range (Egan 2002, p.25).

Figure 2. 3: Brightness Differences (Egan 2002, p.25)

2.1.4. The Field of View
Different animals have different fields of view, depending on the placement of the
eyes. Humans have a 180-degree forward-facing field of view but the range of visual
abilities is not uniform across a field of view. The binocular visual field (vision by
both eyes) extends vertically 130° and horizontally more than 120° when both eyes
20
are focused on a fixed object. Vision by one eye alone is called monocular vision.
The sketch below shows the extent of binocular and monocular visual fields (Egan
1983, p.8).

Figure 2. 4: Sketch of Binocular visual field (Egan 2002, p.40)

The fovea is a spot located in the center of the macula region of the eye’s retina. The
fovea is responsible for sharp central vision, which is necessary in humans for
reading, watching television or movies, driving, and any activity where visual detail
is of primary importance. As shown below, foveal vision is the detail acuity of the
eyes. Foveal vision provides the best color response because of the concentration of
cones in the fovea, the thinnest area of the retina (Egan 1983, p.7).

21

Figure 2. 5: Diagram of Foveal vision (Egan 2002, p.40)

Similarly, color vision and the ability to perceive shape and motion vary across the
field of view; in humans the former is concentrated in the center of the visual field,
while the latter tends to be much stronger in the periphery. This is due to the much
higher concentration of color-sensitive cone cells in the fovea as compared to the
higher concentration of motion-sensitive rod cells in the periphery. Since cone cells
require considerably brighter light sources to be activated, the result of this
distribution is that peripheral vision is much stronger at night relative to binocular
vision (Wikipedia).

2.1.5. Visual Adaptation
Visual adaptation is the ability to accommodate different brightness levels. It is
influenced by all areas in the field of view. It can be explained with the figure below.
When our eyes are adapted to 100 fL, a surface with a measured brightness of 100 fL
should have a perceived brightness of 100 fL to an observer. However, if the
22
observer’s eyes are adapted to only 1 fL (e.g., under dark shadow conditions), this
surface could have a perceived brightness of 400 fL. Although measured brightness
(or luminance) would be the same in both of these situations, the surface could
appear four times as bright due to brightness adaptation (Egan 1983, p.25). For
example, when one small and really bright light fixture is suddenly turned on in a
very dark room, discomfort glare occurs to its occupants. Visual adaptation also
becomes problematic if the luminance changes too rapid.

Figure 2. 6: Brightness Adaptation (Brightness to which eye is adapted.
Influenced by all areas in the field of view) (Egan 2002, p.43)

2.1.6. Reflection and Distribution
When light encounters a material, the characteristics of the light will change
depending on the property of the material. Light may be transmitted, absorbed, or
reflected. If the surface is polished, such as polished marble or a mirror, the light will
23
reflect specularly; that is, the angle of the incoming incident light will be equal to the
angle of the outgoing reflected light. Spread reflections are caused by slight
irregularities in a surface, created by etching, hammering, or corrugating. The beam
spread is primarily at the mirror angle, but softened into a wider cone. Diffuse
reflections are caused by matte materials, such as plaster and matte paint, which
reflect light equally in all directions. These reflections are nondirectional and are
good for achieving a wide distribution of light (Egan 2002, p.57).

Figure 2. 7: Specular, spread, and diffuse reflections (Egan, 2002, p.57)

24
25
2.1.7. Reflectance of Materials
Reflectance ( ρ) is the percentage of incident light that is reflected from a surface,
with the remainder absorbed, transmitted, or both. Total amount of light reflected
from a surface includes all reflections: diffuse, spread, and specular. Both the
perceived brightness and measured brightness (luminance) are affected by the
reflectance of materials. There is a tendency to assume that specular surfaces are
more efficient in reflecting light than matte surfaces. While this sometimes may be
true, just as often it is not. For example, matte white paint reflects light much more
efficiently than polished stainless steel. Typical reflectance for finish materials are
given below (Egan 2002, p.58).

Material Reflectance (%)Material Reflectance (%)
Aluminum, brushed 55-58 Clear or tinted Glass 5-10
Aluminum, etched 70-85 Reflective Glass 20-30
Aluminum, polished 60-70 Asphalt 5-10
Stainless Steel 50-60 Concrete 40
Tin 67-72 Grass 5-30
Brick, red 10-20 Snow 60-75
Limestone 35-60 White Paint 70-90
White Plaster 90-92 Mahogany 6-12

Table 2.1: Reflectance of Materials (Egan 2002, p.58)

2.1.8. Vertical Surfaces
Light reflected from vertical surfaces may be a source of glare. The highly specular
building façades of an office building reflect a great deal of sunlight to neighbors and
the ground surface. Reflected light from vertical surfaces is most noticeable on the
shady side of buildings, where light is reflected from unshaded light-colored walls or
facades of adjacent buildings in the sun. Vertical surfaces receive their greatest solar
impact at low sun angle, such as in wintertime and at high latitudes (Egan 2002,
p.94).

Figure 2. 8: Diagram of vertical surfaces (Egan 2002, p.94)
26
27
2.2. Existing Discomfort Glare Analysis Methods
There are at least seven significant glare analysis methods.

1. The Daylight Glare Index Method
2. The Visual Comfort Probability Method
3. The Unified Glare Rating Method
4. The Relative Visual Performance Method
5. The Video Photometry Method
6. The Schiler Glare Method
7. The Daylight Glare Probability Method

It is important to decide which method would be best for analyzing exterior visual
glare problems. To be the same as previous research methods applied to Disney Hall
glare case, the visual issue needs to be approached through photographs and
computer simulation. Thus the Schiler Glare Method is the best choice for this study.
Of course, if there is any problem during the comparison of results, it is also
necessary to try other research methods.

2.2.1. The Daylight Glare Index Method
The Daylight Glare Index (DGI) Method was developed by R.G. Hopkinson (1963).
Based on extensive experimentation and subjective testing, he proposed that glare
was dependent on the background level within a space. The field of view and glare
28
source were defined in terms of steradians. This method seemed to address the
complex phenomena of glare in terms of contrast between high intensity glare source
and background luminance (Schiler 1995, p.1). Experiments were made by exposing
the observer to a glare source and asking him or her to rate the amount of the
disturbance on a subjective scale.

2.2.2. The Visual Comfort Probability Method
Visual Comfort Probability (VCP) is the discomfort glare evaluation rating, which
was originally developed by S.K. Guth (1966) and later completed by David L.
Dilaura (1976). It has been used for decades by IESNA (Illuminating Engineering
Society of North America) to evaluate discomfort glare. Basically, this method
estimates how many people out of 100 would be comfortable within the space
(Schiler 1995, p.1). The experimental work predicts discomfort glare ratings from
luminous conditions: source luminance, luminances in the field of view, the visual
size of the glare source, and the location of the glare source in the field of view. The
field luminance or the background luminance is calculated as the sum of the
luminance of each luminaire and its contribution to the background by interaction
with the reflective surfaces of the room. In a given geometry along a specified line of
sight, a luminaire with a VCP of 80 will produce acceptable glare sensations in 80%
of the population. Standard conditions were adopted for the calculation of VCP, and a
consensus developed that a luminaire with a VCP of 70 is acceptable (Veitch 2006).

2.2.3. The Unified Glare Rating Method
This method was developed by CIE (Commission Internationale de L’eclairage) for
establishing an international standard for visual glare analysis in 1995. This method
uses a combined formula from Glare Constant formula which was developed by
Hopkinson and Position Index which was developed by Guth. It uses a limited range
of glare source size thus it is effective only for normal size glare sources within a
field of view. The value for UGR is found from the formula.

⎥
⎦
⎤
⎢
⎣
⎡
=
∑
2
2
10
25 . 0
log 8
P
L
L
UGR
s
b
ω

Where
UGR = Unified Glare Rating
b
L = average background luminance [cd/m
2
]
s
L = luminaire luminance [cd/m
2
]
ω = solid angle of the luminaire [sr]
P = Guth position index

With Unified Glare Rating, the glare is determined based on UGR index. The
following table shows the UGR index.

29
30
Glare Criterion UGR
Just Imperceptible 10
Perceptible 16
Just Acceptable 19
Unacceptable 22
Just Uncomfortable 25
Uncomfortable 28
Just Intolerable 31

Table 2.2: UGR index (Hwang 2002, p.2)

2.2.4. The Relative Visual Performance Method
The Relative Visual Performance (RVP) was developed in order to overcome
deficiencies in previous models of visual performance, including the visibility level
model, for the purpose of improving illuminance level recommendations. The RVP is
the measure of human visual performance with regards to discomfort glare. This
study was made based on the speed and accuracy of performing a task. A number of
people were asked to perform a task in a given room lit by a particular light source.
While the background and the light source illuminance level were changed, the time
taken by the occupants to finish the task and the number of errors being performed
were recorded. This method is best used for measuring productivity as a result of the
changing illuminance on a surface, but is not useful for predicting or evaluating the
luminance quality of discomfort glare in a space (Tedjakusuma 2003, p.21). The
following equation shows how to transform visual performance time into units of
RVP.
⎟
⎟
⎠
⎞
⎜
⎜
⎝
⎛
∆ − ∆
∆ − ∆
=
Γ
Γ
,
'
, '
vis vis
vis vis
RT
T T
T T
RVP RVP
Where
RVP = Relative Visual Performance
vis
T ∆ = visual performance time
Γ
∆
, vis
T = the estimated value of
vis
T ∆ at readability contrast threshold

Thus, =0 when =
RT
RVP
vis
T ∆
Γ
∆
, vis
T and =0.998 when = (Rea
1991). Different lighting systems can be compared by measuring people’s response
with the same task and age of individual specified. With the higher RVP percentage,
it is possible to define better lighting environment for the given task.
RT
RVP
vis
T ∆
'
vis
T ∆

2.2.5. The Video Photometry Method
Mark S. Rea (1986) developed an image analysis system to measure the luminance
level using video photometry systems. The primary benefit of using video cameras is
being able to record different solar positions, shadows, etc. over time and to be able
to correlate action with each variable. Video data can be digitized and used for later
analysis in different algorithms to evaluate the luminous environment and then
correlated with the recorded occupant behavior. However, there are extensive
calibrations required to offset camera gains, settings, and spectral responsivity etc
(Schiler 1995, p.2).

31
2.2.6. The Schiler Glare Method
Most of the methods described earlier are tailored to specific situations or use
expensive and cumbersome equipment. However, Schiler developed a strategy that
attempts to predict possible glare within the entire range of human experience. His
method uses an inexpensive and non-calibrated video camera, a known luminance
light source placed within the field of view, and common software such as Microsoft
Excel and Adobe Photoshop to sort and analyze the results that create glare (Schiler
2000, p.2). This method is explained in more detail in chapter 03 which contains the
visual glare research strategy.

2.2.7. The Daylight Glare Probability Method
This method was developed by Jan Wienld and Jens Christoffersen. It is an empirical
approach and is based on the vertical eye illuminance as well as on the glare source
luminance, its solid angle and its position index. Compared to existing glare models,
the Daylight Glare Probability (DGP) shows a very strong correlation with the user’s
response regarding glare perception. For determining glare, the new DGP formula
combines the vertical eye illumination as glare measure with the central term of
existing glare indexes. It also uses the part of the CIE-glare index, which describes
the influence of the glare source. Thus, the following equation gives the best
correlation with the user responses according to this method.

16 . 0 1 log 10 18 . 9 10 87 . 5
2 87 . 1
,
2
, 2 5
+
⎟
⎟
⎠
⎞
⎜
⎜
⎝
⎛
⋅
⋅
+ ⋅ ⋅ + ⋅ ⋅ =
∑
− −
i
i v
i s i s
v
P E
L
E DGP
ω

32
Where
v
E = vertical illumination at eye level [lux]
s
L = luminance of the source [cd/m
2
]
s
ω = solid angle of the source [sr]
P = Guth position index [-]

The luminance distribution within a field of view is recorded using CCD camera -
based luminance mapping technology. For automatic glare evaluation of the
luminance pictures, a new program ‘Evalglare’ was developed. Evalglare uses a
luminance picture in the RADIANCE picture format that enables the user to apply it
also for simulated lighting scenes. This program automatically detects glare sources
within a 180 degree fish-eye scene (Wienold 2006).

Figure 2. 9: Correlation between the new DGP formula and
the probability of disturbed persons in the tests (Wienold 2006, p.6)
33
34
2.3. The Elements of Thermal Glare Effect
Many researches have proved that the heat island effect occurs in many big cities. It
is clear to say infrastructures and buildings of a city are increasing the air and surface
temperature of a city. The following are the most important elements of heat island
effect: heat transfer, heat capacity, emissivity, emittance, solar reflectance, and
transmittance.

2.3.1. Heat Transfer
There are three different heat transfer modes. Conduction is direct heat flow through
matter. The heat travels from the warm surface of a stove to a cooking pot.
Convection is the transport of heat within the air. The heat travels upward to the
ceiling, with the natural upward movement of air. Radiation is the transmission of
electromagnetic rays through space. These rays have no temperature, only energy.
Every material or object with a temperature above absolute zero emits these rays in
all directions until they are deflected or absorbed (Clinton 1996). For example, when
a cloud blocks the sun's rays, a person will feel instantly cooler because he is no
longer receiving the sun's direct infrared radiant heat rays. The passing cloud did not
cool the surrounding air; the loss of warmth is due to the cloud blocking the
transmission of heat rays from the sun and not to a change in air temperature.

Figure 2. 10: Heat transfer (Graphic by Kevin Hand, Star-Bulletin)
http://starbulletin.com/specials/waianae/story2.html

Along with these three main modes of heat transfer, there is also latent heat transfer,
a change of state from solid to liquid or liquid to gas. Latent heat is the heat energy
required to change a substance from one state to another. But this is not often in play
at the scale of buildings, except in evaporative cooling. Yet, that's how plants take
care of the absorbed radiant gain and inanimate materials do not, which is one of the
causes of the heat island effect.

2.3.2. Heat Capacity
Heat capacity is a measurable physical quantity that characterizes the ability of a
body to store heat as it changes in temperature. It is defined as the rate of change of
temperature as heat is added to a body at the given conditions and state of the body.
35
36
In the International System of Units, heat capacity is expressed in units of joules per
kelvin. It is termed an "extensive quantity" because it is sensitive to the size of the
object. For example, a bathtub of water has a greater heat capacity than a cup of
water. Dividing heat capacity by the body's mass yields a specific heat capacity,
which is an "intensive quantity," meaning it is no longer dependent on amount of
material, and is now more dependent on the type of material, as well as the physical
conditions of heating (Wikipedia).

Substance Phase cp (J g-1 K-1)
Asphalt solid 0.92
Brick solid 0.84
Concrete solid 0.88
Glass, crown solid 0.67
Glass, flint solid 0.503
Granite solid 0.790
Gypsum solid 1.09
Marble, mica solid 0.880
Sand solid 0.835
Soil solid 0.80
Wood solid 0.42

Table 2. 3: Specific heat capacity of building materials (Wikipedia)

37
2.3.3. Emissivity
Emissivity is a material characteristic relating to the absorption of radiant energy. A
lower emissivity represents a better characteristic of a material in regard to heat loss.
This emissivity depends on factors such as temperature, emission angle, and
wavelength.

2.3.4. Emittance
The emittance of a material refers to its ability to release absorbed heat. Scientists
use a number between 0 and 1, or 0% and 100%, to express emittance. A perfect
black body has an emittance equal to 1 (100%), while a perfect reflector has an
emittance equal to 0 (0%). With the exception of metals, most construction materials
have emittances above 0.85 (85%).

2.3.5. Solar Reflectance
When sunlight strikes a building surface, solar energy is either transmitted through
the surface, absorbed by the surface, or reflected away from the surface. Solar
reflectance is a measure of the ability of a surface material to reflect sunlight –
including the visible, infrared, and ultraviolet wavelengths – on a scale of 0 to 1. For
example, if a building is constructed with high solar reflectance materials, the
building can reduce heat gain from sunlight and save cooling energy during hot
summer months. However, at the same time, the reflected sunlight by high solar

reflectance materials can be aimed to the surrounding buildings or ground and
increase their temperature.

2.3.6. Transmittance
Transmittance is the fraction of radiant energy that, having entered a layer of
absorbing material, reaches its further boundary. For example, when sunlight reaches
glass, some amount of light is absorbed by glass, some is reflected back into the
atmosphere, and some is transmitted through the glass. The reradiated and convected
heat goes out as well as in. In cold climates, we actually worry about the reradiated
and convected heat to outside but in hot climates, it is the more important to care
about reradiated and convected heat which goes in. The figure below shows the
transmittance of glass.

Figure 2. 11: Diagram of transmittance (Egan 2002, p.66)
38
39
2.4. Existing Thermal Glare Analysis Methods
There are two different devices to evaluate thermal glare problems, datalogger and
infrared thermometer. Both of them are very popular to measure and analyze the
temperature of certain environments for research purposes.

2.4.1. Datalogger
Dataloggers are electronic instruments that record data over time or in relation to
location. Based on a digital processor, they are generally small, battery powered, and
portable (Wikipedia). Thus, they are very powerful tools to measure and record
temperature, relative humidity, wind speed, or solar radiation for long term research
like this study. However, temperatures of surfaces or objects are very tricky and
difficult to measure by dataloggers if the surface or the object is moving.

2.4.2. Infrared thermometer
Temperature measurement problems of a moving surface or distant objects of low
thermal mass can be solved in many cases through the use of an infrared
thermometer. Infrared thermometers measure surface temperature using infrared
radiation emitted from objects. They are sometimes called laser thermometers if a
laser is used to help aim the thermometer, or non-contact thermometers to describe
the device’s ability to measure temperature from a distance. By knowing the amount
of infrared energy emitted by the object and its emissivity, the object's temperature
can be determined (Wikipedia).
40
2.5. Remediation of the Walt Disney Concert Hall
Under pressure of possible lawsuits from residents of the nearby The Promenade
condominiums, Los Angeles County and Gehry were ready to take corrective action
for the comfort of the Disney Concert Hall’s neighbors. The Promenade condo
owners had been complaining since June 2003 that the concert hall was increasing
the interior temperatures of east-facing apartments by approximately 15 degrees. In
July 2003, Los Angeles County asked Marc Schiler, an architecture professor at the
University of Southern California, to figure out how to find and reduce the glare
(Goldin, 2004).

2.5.1. Previous Research on Disney Hall
Prof. Schiler used three methods of finding and quantifying the glare problems of the
Disney Hall. He recorded ground and mid-air temperatures in front of REDCAT
marquee using data loggers and an infrared thermometer from October 18
th
, 2003 to
November 3
rd
, 2003. A computer simulation using the software Lightscape was
conducted to figure out which parts of the Disney Hall were causing the glare
problems throughout the year. And he used photographic histograms of the Disney
Hall taken from the viewpoint of drivers on the four intersections to help quantify the
level and source of the glare.

2.5.2. Previous Research Results
Schiler’s study reveals that the situation was somewhat worse than what was
expected. The curvaceous swoops and swirls of Disney Hall focused sunlight into
hot beams and a powerful glare. As the report notes, “The light is very bright and
collimated.” At 1
st
and Hope Streets, immediately north of the Founders Room,
Schiler (2004) says, “There are moments when the sun is reflected directly into the
intersection. This can interfere with a clear view of traffic and pedestrians, especially
when heading south on Hope Street and turning left or heading east on First Street.”
Anyone who has stood just outside the ticket booth on Grand Avenue on a hot
summer day has felt the concentrating effect of all those concave steel reflecting
surfaces. The REDCAT marquee stainless surfaces had an even worse effect:
temperature on the sidewalk outside could reach 138°F (Schiler 2004).

Figure 2. 12: Polished stainless steel of REDCAT Marquee before the remediation (Schiler 2004)
41
42
2.5.3. Resolutions
The previous study observed that the polished stainless steel surfaces of the Founders
Room and CalArts Theater marquee clearly required remediation. Schiler identified
two different permanent solutions: to brush/sandblast or apply a film to selected
surfaces of the Founders Room and CalArts Theater Marquee.

The first solution included four different film options: (1) a colorless, translucent,
and slightly diffusing film; (2) a light blue, translucent, and diffusing film; (3) a
white and more strongly diffusing film; (4) a white and opaque film with a black
backing (Schiler 2004, p.50). However, after testing all of the suggested solutions
Schiler found that the sandblasted surface would reduce the reflectance significantly
and produce a visual effect similar to the brushed stainless steel panels on the rest of
the building. Thus the sandblasting technique was determined to be the preferred
option by Frank Gehry for a permanent solution. Meanwhile, the worst parts of the
building, those that contributed most to the glare and overheating problem at
Promenade condominiums, were covered by a gray mesh fabric to test the impact of
the proposed solution and to provide interim relief (Pogrebin 2004).

Figure 2. 13: Temporary fabric cover on Founders Room (Schiler 2005)

Finally, LA County decided to proceed with the permanent solution which was
suggested by Prof. Schiler. On March 14
th
, 2005, the crews began sandblasting some
parts of the Founders Room and REDCAT marquee to dull the exterior surfaces. The
figure below shows how the crews made orbital sanding and vibrator sanding works
on the surface of Founders Room. Approximately 4,000 square feet of the total
200,000 square feet of cladding required the treatment. “This work would cost
$180,000, and Los Angeles County paid for the cost” said Terry Bell, a Gehry
partner prior to the remediation, who was the project architect and manager for the
Disney Hall (Pogrebin 2004).
43

Figure 2. 14: Orbital sanding on Founders Room (Schiler 2005)

The following chapters describe the previous and current research strategies for
visual and thermal glare problems and show how much glare problems was reduced
by the remediation.
44
45
CHAPTER 3
VISUAL GLARE RESEARCH

The objective of this study is to find out whether the methods used by Schiler to
measure glare were helpful in determining the problem areas to treat and whether or
not the treatment worked as predicted. If it is shown that the remediation reduced the
glare problem, how much was the problem reduced? If there is no measured
reduction, why not? Was there no reduction or is the method flawed in its current
form? In order to best determine the answers to these questions, a repeat study of the
Disney Hall was undertaken after remediation using similar research strategies.

3.1. Research Strategies for Visual Glare
To minimize variables, the research study should closely follow the methods of the
previous research. The previous research for visual glare was conducted twice, first
on March 29
th
, 2004 and secondly on July 2
nd
, 2004. Digital pictures were taken
from four intersections around Disney Hall every 30 minutes. It would be better to
take pictures of Disney Hall exactly on the same day of March and July. However,
this research scope was from August 30
th
, 2006 to March 3
rd
, 2007 and it was not
possible to photograph Disney Hall at the end of March or the beginning of July.
Therefore, the photographing of Disney Hall for this study was conducted on
September 23
rd
, 2006 instead of March 29
th
, 2006. It was possible to get same glare
effects on Disney Hall from the same sun angle and sun path because March 29
th
is
approximately 8 days after the vernal equinox and September 23
rd
is 2 days after the
autumnal equinox; the sun positions are very close. The figure below shows the
maximum elevation of the sun in summer, the lowest elevation of the sun in winter,
and exactly same sun path in both of equinoxes.

Figure 3. 1: Sun path diagram (Köster 2004, p.2)

Many tools and software were used to analyze visual glare. These included a digital
camera, a Kodak LS 433, Lightscape, Adobe Photoshop, Microsoft Excel, RASCAL,
and CULPLITE.

46
47
3.1.1. Lighting Analysis Software
Lightscape was used to show the possible glare areas on a building. Prof. Schiler
used a 3D model from the architecture firm to simulate the building’s performance
for a whole year. Lightscape allows simulations, with specific material properties
such as reflective factor, to be done for hourly sun positions (Schiler 2004). For
computational purposes, significant modifications of the model were required,
reducing the number of surfaces from over 900,000 to approximately 90,000. The
simulation results suggested that four corners of Disney Hall, including the Founders
Room and the REDCAT marquee, could have discomfort glare problems. Even
though this software could suggest possible problematic areas of glare, it was not
possible to tell how serious the glare problems were. Therefore, Schiler used a
photographic method to evaluate the level of discomfort glare.

3.1.2. Variables to be considered in the new study
There are many crucial conditions to be considered when repeating glare
photographs of Disney Hall. First of all, the sun angle should be approximately the
same as the previous research, because a different sun angle creates a very different
glare pattern on a building. In the previous research, photographs were taken on
March and July in 2004. For the current research, it is reasonable to compare March
29
th
and September 23
rd
which have the same sun angles and sun path because they
are close to equinoxes. An equinox is one of the two days in the year when day and

48
night are of equal length. Thus it was planned to take pictures of Disney Hall on
September 21
st
, 2006 to match with the previous one.

There were many other possible factors that can affect the final glare scores. The
following are some important variables that should be considered for accurate results
from the visual glare analysis: field of view, weather conditions, surface cleanliness,
and camera functions.
1. To analyze visual glare with pictures, it is important to keep the same field of
view for all of the pictures. Using printed pictures of previous photographs, it
was possible to get exactly the same field of view as the previous ones.
2. To select the clearest day close to August 21
st
, the weather forecast was
checked to confirm a date for photography. Clouds could reduce or remove
glare problems on the building. The clearest weather would be expected to
show the worst glare case of the building.
3. The surface cleanness could also affect glare scores of Disney Hall. If a lot of
dust has collected on the stainless steel surface, it can automatically reduce
specularity of the surface materials. There have been glare problems reported
from the Guggenheim Museum in Bilbao which has shiny titanium panels.
Some people said that lots of dust simply reduced the glare problems, and
others said that the neighborhood is mostly industrial, so it was not
considered to be a big problem. When Disney Hall was photographed, the
maintenance team was cleaning the building surfaces. Thus, the cleanness of
surfaces might be different or same between before and after the remediation.
4. Using a camera that was used in previous research could remove any
possibility of getting different picture quality from a different camera. In
Schiler’s study, four different cameras were used at four intersections, but it
was impossible to find three of previously used cameras. The remaining
camera was used for the new study.

3.1.3. Fields of views from Four Intersections
There are four intersections around Disney Hall. The photographs are from 1
st
Street
and Grand Avenue, 2
nd
Street and Grand Avenue, 1
st
and Hope Streets and 2
nd
and
Hope Streets. These locations were previously chosen by Prof. Schiler based on
Lightscape software predictions for a whole year simulation.

Figure 3. 2: Photographs from four intersections
49
3.1.4. Process of Photographing Disney Hall
The photographic study needs to be performed one day, from sunrise to sunset. It
was required to check the exact time of sunrise and sunset for the day. On site, the
field of view and a digital camera were double checked before 06:15 AM then
Disney Hall was photographed from four intersections exactly from 06:30 AM. To
take picture from all of four intersections of Disney Hall every 30 minutes, it was
required to walk very fast along the building and cross the street quickly. The
pictures below show the process of photographing. Photographs were taken exactly
at the same locations and same angle with 30 minutes intervals.

Figure 3. 3: Photographing from 1
st
Street and Grand Avenue

50

Figure 3. 4: Photographing from 2
nd
Street and Grand Avenue

Figure 3. 5: Photographing from 1
st
and Hope Streets

Figure 3. 6: Photographing from 2
nd
and Hope Streets

51
52
3.1.5. Pictures of Disney Hall
The images below show glare pictures of Disney Hall from the current research.
Each field of view has a total of 24 pictures with 30 minutes intervals from 6:30 AM
to 6:00 PM except 1
st
Street and Grand Avenue which was taken until 5:00 PM. The
first figure shows photographs of 1
st
Street and Grand Avenue intersection. From the
pictures, it is possible to see that a bright spot is moving around the building façade
as time is passing. After 3:30 PM, the sun shone directly into the camera, making
glare measurements meaningless. Then the sun totally disappeared behind the Disney
Hall after 5:00 PM. Thus, no more pictures were taken after this point of time.

Figure 3. 7: 1
st
Street and Grand Avenue from 6:30 AM to 10:00 AM
53

Figure 3. 8: 2
nd
Street and Grand Avenue from 6:30 AM to 10:00 AM
54

Figure 3. 9: 1
st
and Hope Streets from 2:30 PM to 6:00 PM
55

Figure 3. 10: 2
nd
and Hope Streets from 2:30 PM to 6:00 PM
56
3.2. Visual Glare Research Results
Luminance histograms are central to the analysis of glare picture. First, the picture
files in the camera need to be transferred to a computer. The following steps, using
several software programs, explain the process for making luminance histograms.

Discomfort
Glare
Digital Camera
Computer Photoshop
RASCAL
CULPLITE
Glare Scores

Figure 3. 11: Diagram of visual glare analysis process

3.2.1. Photoshop
To convert each picture file format from jpg to raw, the process is simple but requires
a long time and effort to set up and change the picture format. The “action” function

57
58
of Photoshop helped reduce the effort. This command can change all of pictures in
short time. The process is summarized below.

In Photoshop:
1. Import pictures into Photoshop with Action function
2. Set Image Size to 320(w) x 240(h)
3. Convert the image to Greyscale mode
4. Open image info window. Make sure Mode is RGB
5. Move the cursor around the area of each spot luminance measurement in the
image, note RGB values (all three should be the same value)
6. Record representative RGB value 0-255 for both bright and dim
measurement locations.
7. Save as .RAW image format (Header=0)
8. Exit Photoshop

Figure 3. 12: Adobe Photoshop

3.2.2. RASCAL and CULPLITE
The RASCAL process is straightforward and simple. It is only necessary to select
each picture and process them in the software.

In RASCAL:
1. Locate and Select the .RAW source file created in the Photoshop
2. Set Resolution to 320 x 240
3. Check Rotate Image box
4. Set Sample spread = 1
59
5. Set ASCII delimiter to Comma
6. Note or edit output filename and location- leave file suffix as “.asc”
7. Click Convert button
8. After processing, Exit RASCAL

Figure 3. 13: RASCAL software

However, CULPLITE is a little more complicated and somewhat confusing to use.
There are steps to input some values such as beginning and ending points of
background bell curve and spike. These values are dependent on user’s decisions.
60
61
Even though the visual glare issue is quite a subjective issue, I believe that the
software needs to develop more objective methods to score glare problems.

In CULPLITE:
1. Open CULPLITE.xls
2. Select worksheet tab asc
3. Open the .asc file created in RASCAL. You will need to select filetype as “all
files” in the Open File dialog window for the filename to display.
4. The Excel Import Wizard will begin to process the file:
i. Select Delimited, then press the Next button
ii. Select Comma (,) as delimiter, then press Finish button
5. In the newly created spreadsheet a1image.asc, select all or click corner
button between row 1 and column A
6. Copy selection to clipboard
7. Switch to file CULPLITE.xls (worksheet tab asc)
8. Click on cell A1, then press Enter key. This move should paste values from
clipboard into worksheet tab asc cells A1:IF320.

Figure 3. 14: CULPLITE software

3.2.3. Schiler Glare Rating
After processing every step, CULPLITE can be used to determine the Schiler Glare
Score that defines whether each picture has discomfort glare problems or not. The
following explains how to define user editable values in the software.

In CULPLITE:
1. Go to worksheet tab input.
62
63
i. Enter the 2 (high and low) pixel intensity values recorded from
Photoshop into indicated cells in columns F & G
2. Go to worksheet tab statistics
i. View the image histogram
ii. Below the histogram are some statistical values
iii. Under Individual Pixel Value enter any pixel value 0-255 to see its
corresponding luminance value estimate
iv. Under Background and Spike define image background and spike
by looking at image and entering high- and low-end pixel values for
both bell and spike regions.
v. Median values for the background bell and spike are calculated, as
are percent of view for background and spike regions.
vi. Look at top of histogram to see graphic representation of your
Background and Spike definitions.
vii. Look further below to see the ratio of median values (Spike to
Background Ratio)
Black “+” symbols on the histogram mark the boundaries you
defined for Background and Spike regions.
Red “ ” symbols on the histogram indicate the median pixel
value for each defined region.
viii. Look further below to see Schiler Glare indication:
IF median ratio < 2:1 THEN Schiler Glare = NO
64
IF 2:1 =< median ratio < 3:1 THEN Schiler Glare = MAYBE
IF median ratio >= 3:1 THEN Schiler Glare = YES

3.2.4. Luminance Histograms
Luminance histogram is basically an RGB composite histogram that takes into
consideration the human eye's greater sensitivity to green, then red and lastly blue.
This type of histogram is also sometimes called a brightness histogram because it
displays a compensated brightness range. The luminance histogram gives the best
graphical representation of the visual brightness and contrast of an image.

The following four luminance histograms were selected to show the worst case of
each intersection. All of the four histograms show different spike and background
bell curve. 1
st
Street and Grand Avenue have a really tall spike on the right side of the
histogram but the background bell curve is very low and flat. This represents a huge
contrast between glare source and background light level and the score is 3.45, which
means serious discomfort glare.

Figure 3. 15: Luminance histogram of 1
st
Street and Grand Avenue at 5:00 PM

This histogram is from 2
nd
Street and Grand Avenue. The spike is not high comparing
to the background bell curve, but there are a large amount of pixels that are really
dark. And these dark portions made this picture’s glare score really high which is
3.64.

65

Figure 3. 16: Luminance histogram of 2
nd
Street and Grand Avenue at 7:30 AM
66

Figure 3. 17: Luminance histogram of 1st and Hope Streets at 6:00 PM

This histogram is from 2
nd
and Hope Streets. A huge amount of pixels that have low
pixel value are shown on the left side of histogram. It is assumed that the trees next
to Disney Hall made a shadow with low sun angle at the late afternoon and the shade
made lots of dark pixels. Also an interesting feature from this histogram is the huge
amount of pixels that have a value from 180 to 210. These bright pixels are mainly
67
from limestone surfaces and REDCAT marquee stainless steel surfaces, and they
make lower glare scores. However, the glare score is 3.04, which means discomfort
glare.

Figure 3. 18: Luminance histogram of 2nd and Hope Streets at 6:00 PM

68
69
3.2.5. The Schiler Glare Scores
The following charts show the entire day’s glare scores of 2004 and 2006. The red
color represents discomfort glare problems that have scores over 3.0. Blue numbers
have scores between 2.0 and 3.0. They might be considered as discomfort. Black
numbers show that there is no glare problem. The first chart is from the previous
research in 2004 and the following chart is from current research in 2006.

The scores from 2004 were analyzed again for this study using CULPLITE. Thus,
the scores might be different from the previous research analysis. However, it is
important to keep a constant analysis approach in the CULPLITE software.

Previous research was focused on finding the worst cases of glare problems, thus the
east side of building was photographed only until 3:30 PM and west side of building
was photographed from 10:30 AM to 6:00 PM. However, for current research all
four intersections were photographed and analyzed from 6:30 AM to 6:00 PM.

Table 3. 1: Glare scores of four intersections_2004

As expected before the study, the east parts of the building had higher glare scores in
the early morning. 1
st
Street and Grand Avenue and 2
nd
Street and Grand Avenue are
located on east-south of the building. The west parts of building had higher glare
scores in the late afternoon. The Founder’s Room which is located on 1
st
and Hope
Street did not show any serious glare problems during the whole day but had high
scores at the early morning, noon and late afternoon. REDCAT which is located on

70
2
nd
and Hope Streets also showed similar glare scores with Founders Room but had
discomfort glare problem at 6:00 PM.

1
st
Street and Grand Avenue and 2
nd
Street and Grand Avenue showed much higher
glare scores than the other side of building. This result shows great similarity with
previous glare scores.

Table 3. 2: Glare scores of four intersections_2006

71
3.3. Results Comparison between Previous and Current Research
Based on the scores from 2004 and 2006 researches, the following comparison charts
were created. The red line shows the 2006 glare scores and blue line shows the 2004
glare scores. It was expected to show different results from 1
st
and Hope Streets and
2
nd
and Hope Streets because the surface remediation was performed only on
REDCAT marquee and Founders Room of Disney Hall. On the contrary, it was
expected to show similar results from pictures of 1
st
Street and Grand Avenue and 2
nd

Street and Grand Avenue intersection where no remediation was made.

Mar.29,2004
Aug.23,2006
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
6:30
7:00
7:30
8:00
8:30
9:00
9:30
10:00
10:30
11:00
11:30
12:00
12:30
13:00
13:30
14:00
14:30
Time
Glare Score

Figure 3. 19: Glare score comparison chart between 2004 and 2006
from 1
st
Street and Grand Avenue

Interestingly, 1
st
Street and Grand Avenue and 2
nd
Street and Grand Avenue glare
scores made almost same lines for each time of the day. This suggests that the
72
research methodology may be trustful even though we still have lots of other
variables.

Mar.29,2004
Aug.23,2006
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
7:00
7:30
8:00
8:30
9:00
9:30
10:00
10:30
11:00
11:30
12:00
12:30
13:00
13:30
14:00
14:30
15:00
15:30
Time
Glare Score

Figure 3. 20: Glare score comparison chart between 2004 and 2006
from 2
nd
Street and Grand Avenue

While the first two graphs seemed to show clearly repeatable results, the following
two graphs made the research results less clear. The Founders Room and REDCAT
marquee surfaces look quite different now after the remediation. However, the glare
scores from this research were almost the same or somewhat worse than the previous
glare scores before the remediation. This comparison graphs arouse suspicion about
the research methodology and led me to try additional tests.

73
Mar.29,2004
Aug.23,2006
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00
Time
Glare Score

Figure 3. 21: Glare score comparison chart between 2004 and 2006 from 1
st
and Hope Streets

Mar.29,2004
Aug.23,2006
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00
Time
Glare Score

Figure 3. 22: Glare score comparison chart between 2004 and 2006 from 2
nd
and Hope Streets

74
75
3.4. Problems
After making a comparison between 2004 and 2006 glare scores, every step of the
glare research process was investigated to understand why the result was different
from what was expected. This investigation uncovered interesting results concerning
the CULPLITE program and the camera used. Because both of these tools are crucial
to analysis of visual glare for this research, it is necessary to make more detailed
additional tests on them. Two problems were discovered: CULPLITE can not
recognize absolute glare in pictures and automatic digital cameras often function to
ameliorate glare problems in pictures; this interferes with accurate use of the method.

The following chapter shows the additional study of the automatic camera usage and
suggests that it is a mistake to use an automatic camera in the visual glare research.
76
CHAPTER 4
CAMERA TEST

The main purpose of this test is to find out whether or not it was a good idea to use
an automatic camera. It is important to check whether every camera shows the same
glare score for the same glare picture position. Including the Kodak LS443 camera
which was used for visual glare research, three other automatic cameras were tested
for photographs. Also one Nikon digital SLR camera that is manually controlled was
tested.

4.1. Camera Test Strategy
This test was conducted with cameras from different companies. It was assumed that
each camera might be pre-programmed with different software. A total of five
different cameras were used for this test. Four were automatic digital cameras, and
one was a digital SLR camera that can be used to manually set shutter speed,
aperture, and other values.

4.1.1. Components of the Camera Test
The cameras were selected randomly. The following shows the name of each camera
and the date that each camera’s was first released date on the market: Canon
Powershot S400 (March 2003), Canon Powershot SD400 (March 2005), Kodak
LS443 (January 2002), Nikon Coolpix 4300 (October 2002), and the Nikon D200
(December 2005).

Figure 4. 1: Automatic cameras

Except for the Nikon D200 camera, all the other cameras were set up in basic
automatic mode.

Figure 4. 2: Nikon D200
77
78
4.1.2. Photographing
The camera test was performed on November 9
th
, 2006. Glare problems were
photographed between 3:30 pm and 4:30 pm. This period of day has the worst glare
problems for downtown Los Angeles.

Actually, it was not difficult to find glare problems in downtown Los Angeles. Late
afternoon glare is created from many high rise buildings that have highly specular
surfaces. Three glare spots were found near Disney Hall to remove any possible
variables. DWP building and Disney Hall were taken from 2
nd
and Hope Streets and
1
st
and Hope Streets. First, the pictures were taken by four automatic cameras with
no manual settings. Then, a manual camera took pictures of glare spots with different
settings.

4.2. Camera Test Results
All pictures used the same process for visual glare test analysis. With CULPLITE
and RASCAL, every single picture was analyzed and evaluated. The results
suggested that previous and current research methods were not quite correct.

4.2.1. Pictures of Automatic Cameras
The images below are from four automatic cameras. It is not easy to recognize
differences between the four images. However, it is clear to see that the Kodak
camera creates darker images than the other cameras for three glare cases.
There is a big difference between the four pictures. The glare spot looks almost the
same from all of four pictures but the glare spot of Kodak camera shows brighter and
even makes red edges around the spot. Also the sky and building façade look darker
in the Kodak camera picture.

Figure 4. 3: Glare on DWP building with four automatic cameras

All four pictures almost look similar but the Kodak camera picture is darker than
other pictures. It is possible to assume that its glare score would be higher than other
pictures.
79

Figure 4. 4: REDCAT marquee with four automatic cameras

Without processing the luminance histogram, it is clear to see that use of the Kodak
camera would not reduce the glare.

80

Figure 4. 5: Founders Room with four automatic cameras

4.2.2. Pictures of Nikon D200
The aperture and exposure time of the Nikon D200 can be controlled manually. The
shutter speed and ISO values were fixed, and only the aperture value was changed to
make a clear comparison. With this method, it is possible to remove other non-
software variables that can affect glare scores.

For each glare situation, around 10 or 12 pictures were taken with different aperture
values. The below figures have 8 pictures which are selected from 12 pictures. There
81
82
are series of pictures for each location. Before taking pictures, the shutter speed and
ISO values were fixed with 1/250 sec and ISO 100. There is only a difference of
aperture value between pictures. The range of aperture value is approximately from F
3.5 to F 10.0. All pictures of manual camera tests are shown below.

Figure 4. 6: DWP taken by Nikon D200
83

Figure 4. 7: REDCAT marquee taken by Nikon D200
84

Figure 4. 8: Founders Room taken by Nikon D200
85
86
4.2.3. Luminance Histograms of Automatic Camera Pictures
As previously described in chapter 03, the visual glare research produced luminance
histograms from images and analyzed them to get actual glare scores. Luminance
histograms show the number of pixels that have specific brightnesses thus quantities
visual brightness and contrast of an image. The following histograms were captured
from CULPLITE software. When analyzing the luminance histograms, some
unexpected results came up from this test.

Two Canon cameras and the Nikon camera show similar background bell curves, but
the spike height is strongly different from each image. The most interesting
histogram is from the Kodak camera picture, and it shows that all of the background
bell curve is shifted to the left side. This means that the entire image is very dark.
The camera has not corrected anything to make enhance the image by changing the
brightness.

Figure 4. 9: Luminance histograms of DWP

Figure 4. 10: Luminance histograms of REDCAT

87

Figure 4. 11: Luminance histograms of Founders Room

4.2.4. Luminance Histograms of Nikon D200 Pictures
The images below show eight luminance histograms with different aperture values.
Three cases show similar results. As increasing aperture value from F4.2 to F9.0, the
spike on the right side of histogram is getting lower, and the background bell curve is
shifted to left side. This can increase glare scores.

In the figure below, the spike disappeared with F7.1 aperture value. And F7.1, F8.0
and F9.0 cases have a large amount of pixels near the left edge of histogram which
means 0 luminance value.

88

Figure 4. 12: Luminance histograms of DWP with Nikon D200
89

Figure 4. 13: Luminance histograms of REDCAT with Nikon D200

90

Figure 4. 14: Luminance histograms of Founder’s Room with Nikon D200

91
92
4.2.5. Glare Score Comparisons
Many interesting results are shown from this test. First, all cameras made very
different images of the building façade that corresponded to varying glare scores.
With the Nikon Capture software, every picture was investigated to get exact settings
of cameras. For example, Canon S400 used 1/800 sec shutter speed and F4.0
aperture value for the DWP glare picture. In fact, each camera used a different set up
for all pictures. All the cameras seem to be programmed with different preferences.
This means if someone uses a different camera for another test, the glare results can
be totally different. This may be one reason that the visual glare scores did not show
any difference even after the remediation.

There was a suggestion to find out the first manufactured date for each camera to see
if there was any relation between camera functions and glare scores. However, glare
scores were made so randomly that it does not show any relation with year of
manufacturing.

Table 4. 1: Glare score comparison table

The manual camera test also made quite interesting results. As I expected before the
test, the glare scores are getting higher with big aperture value (small aperture). And
at a certain point of aperture size, the entire view of the image become dark, and no
spike was found on the histograms. With this method of manual camera test, one set
of variables has been eliminated. Therefore it would be possible to take more correct
glare pictures that do not ameliorate glare problems but just show actual glare
problems in pictures. However, variables of the software which processes the image
and the CCD sensitivity curves still exist in this method. It is also difficult to find out
specific values of aperture and shutter speed for a different glare case.

Each of these, if correctly analyzed, should show the same glare score. A task for the
future would be to find an improved glare analysis technique.
93
94
CHAPTER 5
THERMAL GLARE RESEARCH

The complaints about thermal glare problems started from residents of Promenade
condominiums which is located adjacent to Disney Hall. To prove that the problem
actually existed, it would be necessary to measure the temperature inside the units of
Promenade Residence. This could not be done. Instead it was decided to measure
only ground temperatures in front of REDCAT marquee and mid-air focal points.
There might be a relationship between Promenade Residence unit temperature and
ground temperature in front of REDCAT, but it would be indirect. The previous and
current research data can merely show a relationship between radiant gain and
ground temperature, such as was shown by the dip in ground temperature which
occurred when the REDCAT was shaded by the other building.

5.1. Research Strategies for Thermal Glare
Two research methods were used for the previous Disney Hall glare research in 2003
and 2004. Prof. Schiler installed data loggers on the sidewalk and road in front of the
REDCAT marquee and recorded the ground surface temperatures for two weeks in
2003 and one week in 2004. The REDCAT marquee, which is located at the south-
west corner of building, reflected strong sunlight for the whole day. This is the
reason only this location’s temperature was recorded for the previous research. To
measure mid-air focal point temperature in front of the REDCAT marquee, he held a
lightweight dark color painted foamcore panel facing toward the marquee surfaces in
the location of one of the focal points, measured the foamcore surface temperature
with an infrared thermometer and when the temperature stabilized, recorded the
temperature. This is a very simple method to find the magnitude of the heat gain
caused by radiant heat from the highly reflective and specular marquee surface. The
present research also follows the previous research strategies.

5.1.1. The Components of Thermal Glare Research
The following tools were selected to gather and analyze ground and mid-air focal
point temperature data in front of REDCAT marquee: iButton, T-Max, silicone glue,
Raytek infrared thermometer, and black matt lightweight foamcore. iButtons and T-
Max were used for analysis of ground temperature data. Raytek infrared
thermometer and black matt foamcore were used for measuring mid-air focal point
temperatures.

Figure 5. 1: iButtons and Raytek infrared thermometer

95
5.1.2. Location Selection
In the previous research, the thermal glare research was conducted on the ground in
front of the REDCAT marquee (hereafter referred to as “REDCAT”). REDCAT is
located at the south-west section of the building; thus this location had the most
serious thermal glare problems. Prof. Schiler installed six iButtons at critical points
on the sidewalk and the road in front of REDCAT in 2003. In 2004, he also installed
three iButtons at critical points also on the sidewalk and road. Finally, he recorded
the ground temperature data of October 2003 and July 2004. Therefore, the current
research covered all of these critical points on the ground in front of REDCAT.
Moreover, two additional dataloggers were installed on different spots near REDCAT
to make a comparison between dataloggers.

Figure 5. 2: Thermal glare research scope
96
The image below shows the exact locations of the dataloggers. Datagloggers 01 and
02 were installed on the sidewalk. Dataloggers 03, 04, 05, 06 and 07 were installed
on the road. Locations 08 and 09 were additional locations on the road for the current
research. Datalogger 08 was installed under a tree to avoid any direct sunlight or any
radiant heat from REDCAT marquee. Location 09 was a bit distant from Disney Hall
in full direct sunlight.

Figure 5. 3: Exact locations of nine data loggers

5.1.3. Normalization
In order to correlate and compare data from data loggers, data loggers first must be
normalized to compare and contrast the same information. For the research, it was
necessary to prepare more data loggers than the required number. First, all the
loggers need to be set to record temperature data with the same interval, and need to
be placed at the same location as for the previous research. During the recording
97
procedure, it was necessary to change the location from a cold space to a hot space to
determine that they were exactly recording the same temperature even with rapidly
changing temperature range. After the normalization process, it was possible to take
out the data loggers that were broken or had no battery power left. Ten dataloggers
were normalized from August 29, 2006 to August 30, 2006. After two days’
normalization test, two dataloggers were found to be defective – they suddenly
measured large, different temperature data. The chart below shows the normalization
test results. Except datalogger #A6F21 and #4EE21, all the other loggers were
working correctly. However, the results were slightly different with maximum 2°F
difference. In case there was a consistent difference, it could be possible to add the
correction factors to the different dataloggers but no consistent difference was
observed from the normalization test.

50
55
60
65
70
75
80
85
90
95
100
08/29/2006 08/29/2006 08/30/2006
Time
Tem perature (*F)
FED21
FA421
CB321
AE121
A6F21
28921
35C21
4EE21
2AB21
1CD21

Figure 5. 4: Normalization results with 10 dataloggers
98
5.1.4. Installation of Dataloggers
For installing dataloggers, it was necessary to make small holes on the ground of
sidewalk and road in front of REDCAT marquee. Actually, there are existing holes
on the ground which Prof. Schiler made for his previous research. In previous
research, he got permission to make small holes for installing data loggers on the
ground, installing one data logger into each hole using silicone glue. The current
research used the existing holes on the ground. The pictures below show one
embedded datalogger on the road and two embedded dataloggers on the sidewalk.

Figure 5. 5: Embedded datalogger on the road

99

Figure 5. 6: Two installed dataloggers on sidewalk

5.1.5. Data Logging
With a 30 minute interval, iButtons can record temperature data for a maximum of
42 days. Every three or four weeks, all dataloggers were exchanged with new loggers.
To transfer temperature data from the iButtons to a computer, T-Max software was
used. Even though concrete materials on the ground surface could affect temperature
data, this was the correct method to measure the surface temperature of ground at the
moment. Of course, the temperature results do not determine whether the
temperature range would be at dangerous levels for humans or not. However, we
could measure the ground temperature as an indication of how much heat was
reflected to the ground from the marquee.

100
101
5.1.6. Infrared Thermometer Measurement
This method was employed to find out the magnitude of another thermal glare issue.
Different from ground temperature research, this research could examine and
establish the problem of focused heat by the building. At mid-air in front of
REDCAT, there are some radiant focal points caused by the concave shape of the
marquee surface. This surface not only reflects strong sunlight to its surrounding but
also focuses sunlight at certain angles.

As previously explained in chapter 03, radiation is one of three mechanisms for heat
transfer, and this research is closely related to radiation. A lightweight black
foamcore board was used to show the radiation effect. All objects radiate infrared
rays from their surfaces until they are reflected or absorbed by another object. When
infrared rays radiated from REDCAT marquee strike the surface of the black
foamcore, the rays are absorbed, and heat is produced in the foamcore quickly.
Lightweight foamcore increases in temperature quickly until it gets to the heat
balance point (this is different from high mass materials usch as concrete or water).
Then lightweight black foamcore re-radiates the absorbed energy by emitting
infrared radiation at the same rate that it is absorbing solar radiation. When the
foamcore starts to re-radiate the infrared ray from its body, the surface temperature of
the foamcore can be measured with infrared thermometer.

The following is the research procedure. As explained above, the lightweight black
foamcore was prepared to measure its surface temperature with radiant heat gain
from the REDCAT marquee. First it was necessary to hold the lightweight black
foamcore facing the marquee surface and change locations to find the local
maximum heat focal point directly on the foamcore surface. When the foamcore
absorbed enough radiant heat from the marquee and started to re-radiate infrared rays,
its surface temperature was measured several times using the infrared thermometer.
Then the highest temperature was recorded at each location. This process took
several minutes at each location. The results showed the temperature of focal points
caused by radiant heat from the marquee and also showed whether the focused
radiant heat was at a problematic level or not. The picture below shows the process
of infrared thermometer measurement.

Figure 5. 7: Measuring focal point temperature at mid-air
102
103
5.2. Thermal Glare Research Results
Using MS Excel, all temperature data were organized and visualized with graphs.
Daily temperatures of downtown Los Angeles were collected to compare the ambient
temperature versus the ground temperatures in front of REDCAT. With this method,
it was possible to assume the relation between ambient temperature and dataloggers’
ground temperatures.

5.2.1. Ground Temperature Data
All data from the previous and current research were comparatively graphed in MS
Excel to visualize the data. It is possible to examine heat island effect by comparing
dataloggers that record ground temperatures near the building, away from the
building, and the ambient temperature (in this case, of downtown Los Angeles). A
daily peak temperature comparison chart and three days pattern of actual temperature
chart were created from each set of data. The graph below is from previous research
in 2003. The highest record during this period was 136.4°F from location 07.
Location 07 was located in the concrete ground on the road. Daily peak temperatures
of downtown Los Angeles were between 80°F and 100°F during October 2003; then
the temperatures were dropped below 65°F after the beginning of November 2003.
This indicates a contribution to the heat island effect.

Location #03
136.4
Location #07
30
50
70
90
110
130
150
170
10-18-
2003
10-20-
2003
10-22-
2003
10-24-
2003
10-26-
2003
10-28-
2003
10-30-
2003
11-1-200311-3-2003
Time
Temperature (*F)
Hi
Low
Location #01
Location #02
Location #03
Location #04
Location #05
Location #06
Location #07
Location #08
Location #09

Figure 5. 8: Temperature data from 10/18/2003 to 11/03/2003

Other temperature data from July, 2004 showed quite different results. Locations 01
and 02 had the highest temperature, 139.1°F. An interesting result from this period
was that the highest temperatures were from the dataloggers on the sidewalk. It could
be assumed that the summer sun angle was high thus the reflected heat from the
REDCAT marquee was focused on the sidewalk. The ambient temperatures were
quite flat for a week in mid-July. Daily peak temperatures were around 90°F, and the
lowest temperatures were around 63°F. So there is still a heat island contribution.

104
Location #01
139.1
Location #02
Location #07
30
50
70
90
110
130
150
170
7-11-2004 7-12-2004 7-13-2004 7-14-2004 7-15-2004 7-16-2004 7-17-2004
Time
Temperature (*F)
Hi
Low
Location #01
Location #02
Location #03
Location #04
Location #05
Location #06
Location #07
Location #08
Location #09

Figure 5. 9: Temperature data from 07/11/2004 to 07/17/2004

105
All the following graphs are from the current research results. The first graph shows
the temperatures from August 30, 2006 to September 16, 2006. The highest
temperature was 148.1°F from location 03, which was embedded on the road. This
temperature record was even much higher than previous research’s worst case which
was 139.1°F. Even though downtown Los Angeles’s ambient peak temperature was
almost 100°F at the date, this was really surprising result. It is also interesting to note
that location 01 had lowest temperatures among all the locations.

Location #01
Location #03
148.1
Location #08
30
50
70
90
110
130
150
170
8-30-2006 9-1-2006 9-3-2006 9-5-2006 9-7-2006 9-9-2006 9-11-20069-13-20069-15-2006
Time
Temperature (*F)
Hi
Low
Location #01
Location #02
Location #03
Location #04
Location #05
Location #06
Location #07
Location #08
Location #09

Figure 5. 10: Temperature data from 08/30/2006 to 09/16/2006

The graph below was from September 17, 2006 to October 7, 2006. Locations 05, 06,
and 07 showed the highest temperatures among all locations. Especially, location 05
measured 134.6°F, which was highest record for this period. It was also interesting to
106
see that when the weather was cloudy on September 23
rd
all dataloggers had low
temperature readings. Location 01 and 02 showed lowest temperatures during sunny
or even during cloudy days.

Location #01
Location #02
134.6
Location #03
Location #06
Location #07
30
50
70
90
110
130
150
170
9-16-2006 9-19-2006 9-22-2006 9-25-2006 9-28-2006 10-1-2006 10-4-2006 10-7-2006
Time
Temperature (*F)
Hi
Low
Location #01
Location #02
Location #03
Location #04
Location #05
Location #06
Location #07
Location #08
Location #09

Figure 5. 11: Temperature data from 09/17/2006 to 10/07/2006

Figure 5.12 shows a three days pattern from temperature data of September 2006. All
dataloggers showed quite similar temperature pattern during a day. All dataloggers
had their peak temperatures at 2 PM. and afterwards the temperatures were going
down slowly. Then, there was suddenly a small dip at 4 PM. Actually, the previous
temperature data before the remediation had a similar phenomenon, which was
caused by one of high-rise buildings in downtown. This building created a shadow
that covered the whole area in front of the REDCAT and cooled down the ground
107
temperature. Different from other dataloggers, datalogger 09 showed two small dips
during the day.

Location #03
128.3
Location #07
Location #09
30
50
70
90
110
130
150
170
09/23/2006 09/24/2006 09/25/2006
Time
Temperature (*F)
Location #01
Location #02
Location #03
Location #04
Location #05
Location #06
Location #07
Location #08
Location #09

Figure 5. 12: Three days temperature pattern from 09/23/2006 to 09/25/2006

The following graph was from October 8, 2006 to November 8, 2006. All locations’
temperatures were much lower than previous months. However, location 06 and 07
still showed quite high temperatures during the half end of October. From this graph,
location 08 recorded and showed ground temperature under the shade of trees near
REDCAT. Location 08’s temperatures were similar to or somewhat lower than
downtown Los Angeles’s ambient peak temperature. This means the location 08 did
not get any focused heat from REDCAT marquee surfaces. It is also very surprising

108
to see huge difference between other dataloggers’ data and datalogger 08’s
temperatures.

Location #01
Location #02
Location #06
Location #07
135.5
Location #08
30
50
70
90
110
130
150
170
10-8-
2006
10-11-
2006
10-14-
2006
10-17-
2006
10-20-
2006
10-23-
2006
10-26-
2006
10-29-
2006
11-1-
2006
Time
Temperature (*F)
Hi
Low
Location #01
Location #02
Location #03
Location #04
Location #05
Location #06
Location #07
Location #08
Location #09

Figure 5. 13: Temperature data from 10/08/2006 to 11/08/2006

Again, this shows the Disney’s contribution to the heat island effect. Another
interesting result was location 09’s temperature data that is a bit distant from the
REDCAT marquee and in direct sunlight. This datalogger recorded much lower
ground temperature than the datalogger 03, 04, 05, 06, and 07 that were in front of
REDCAT, but higher than datalogger 01 and 02 on the sidewalk. It is possible to
conclude that there is a relation between radiant heat from the marquee and ground
temperature and also a relation between ground materials and datalogger’s
temperature.
109
Figure 5.14 shows three days pattern from temperature data of October 2006.
Different from September’s temperature pattern, each of the dataloggers showed a
different temperature pattern. Except for location 07, other locations had reached
their peak temperatures at 1:30 PM. Interestingly, location 07 had its peak
temperature at 3:00 PM, and there was large dip at 2 PM. This dip was almost the
same as the previous temperature data before the remediation- probably due to the
shadow of the high-rise building. Location 08, which was under trees, showed low
temperatures for whole day.

Location #06
135.5 Location #07
Location #08
Location #09
30
50
70
90
110
130
150
170
10/21/2006 10/22/2006 10/23/2006
Time
Temperature (*F)
Location #01
Location #02
Location #03
Location #04
Location #05
Location #06
Location #07
Location #08
Location #09

Figure 5. 14: Three days temperature pattern from 10/21/2006 to 10/23/2006

Now we can examine the winter season’s temperature data. Generally, all
dataloggers’ and downtown Los Angeles’s ambient temperatures were much lower
110
than those recorded during the summer. However, location 07 still showed very high
temperatures until November 9
th
; then all datalogger’s temperatures became almost
equal after November 22, 2006. Location 08 was still quite similar to LA downtown
peak temperature.

Location #06
Location #07 130.1
30
50
70
90
110
130
150
170
11-4-
2006
11-7-
2006
11-10-
2006
11-13-
2006
11-16-
2006
11-19-
2006
11-22-
2006
11-25-
2006
11-28-
2006
12-1-
2006
Time
Temperature (*F)
Hi
Low
Location #01
Location #02
Location #03
Location #04
Location #05
Location #06
Location #07
Location #08
Location #09

Figure 5. 15: Temperature data from 11/04/2006 to 12/01/2006
111
Figure 5.16 shows that temperature from November had almost the same pattern as
temperatures from October, but it had much lower temperature range. Location 07
had its peak temperature at 2:30 PM, and other locations had their peak temperatures
at 12:30 pm. The peak temperature time was around 30 minutes earlier than previous
month.

Location #06
Location #07 115.7
Location #09
30
50
70
90
110
130
150
170
11/18/2006 11/19/2006 11/20/2006
Time
Temperature (*F)
Location #01
Location #02
Location #03
Location #04
Location #05
Location #06
Location #07
Location #08
Location #09

Figure 5. 16: Three days temperature pattern from 11/18/2006 to 11/20/2006

112
The figure below shows December’s temperature data in 2006. Location 07 did not
show the highest temperature at this time. All nine dataloggers had low temperatures
for December and made quite similar lines to LA downtown’s ambient temperature.

Location #06
Location #08
30
50
70
90
110
130
150
170
12-2-
2006
12-6-
2006
12-10-
2006
12-14-
2006
12-18-
2006
12-22-
2006
12-26-
2006
12-30-
2006
1-3-
2007
Time
Temperature (*F)
Hi
Low
Location #01
Location #02
Location #03
Location #04
Location #05
Location #06
Location #07
Location #08
Location #09

Figure 5. 17: Temperature data from 12/02/2006 to 01/06/2007

113
Location 08, which was installed under trees, showed interesting result for December.
Sunlight, due to the lower sun angle of morning in December, had reached to
location 08 from early morning and increased its temperature until 10:30 AM. This
peak temperature was even higher than other locations’ highest temperatures for
some days. The other locations had peak temperatures at 12:30 PM.

Location #07
Location #08
83.3
Location #09
30
50
70
90
110
130
150
170
12/18/2006 12/19/2006 12/20/2006
Time
Temperature (*F)
Location #01
Location #02
Location #03
Location #04
Location #05
Location #06
Location #07
Location #08
Location #09

Figure 5. 18: Three days temperature pattern from 12/18/2006 to 12/20/2006

114
The figure below shows the ground temperature in front of REDCAT during January
2007. Again, location 07 and 06 had the highest temperatures among all of nine
dataloggers. Location 07 had 25°F higher temperature than other locations on
January 28
th
, 2007. This is very interesting data, but currently no theory has been
developed to explain this.

Location #06
Location #07 116
30
50
70
90
110
130
150
170
1-7-2007 1-11-2007 1-15-2007 1-19-2007 1-23-2007 1-27-2007 1-31-2007
Time
Temperature (*F)
Hi
Low
Location #01
Location #02
Location #03
Location #04
Location #05
Location #06
Location #07
Location #08
Location #09

Figure 5. 19: Temperature data from 01/07/2007 to 02/02/2007

115
January 2007 had exactly same temperature patterns as November 2006. Location 07
had its peak temperature at 3:00 PM, and there was a large dip at 2:00 PM. Other
locations had peak temperatures at 1:00 PM and also had small dips at 2:00 PM.
Location 08 still showed the highest temperature at 10:00 AM in the morning.

116.1
Location #07
Location #09
30
50
70
90
110
130
150
170
01/23/2007 01/24/2007 01/25/2007
Time
Temperature (*F)
Location #01
Location #02
Location #03
Location #04
Location #05
Location #06
Location #07
Location #08
Location #09

Figure 5. 20: Three days temperature pattern from 01/23/2007 to 01/25/2007

116
The figure below shows the ground temperatures in front of REDCAT during
February 2007 which is the last temperature data in this study scope. Location 07 and
location 06 showed the first and second highest temperatures among all of nine
dataloggers. Except location 06, 07 and 08, all the other dataloggers showed quite
similar temperature data.

Location #06
Location #07
30
50
70
90
110
130
150
170
2-3-2007 2-7-2007 2-11-2007 2-15-2007 2-19-2007 2-23-2007 2-27-2007
Time
Temperature (*F)
Hi
Low
Location #01
Location #02
Location #03
Location #04
Location #05
Location #06
Location #07
Location #08
Location #09

Figure 5. 21: Temperature data from 02/03/2007 to 03/02/2007

117
February 2007 showed slightly higher temperature than January 2007 but the
temperature patterns of January and February are quite similar. Location 07 had its
peak temperature at 3:00 PM, and other locations had peak temperatures at 1:00 PM.
Between two peak points, there is a sudden dip at 2:00 PM like previous months.
Location 08 still had its highest temperature at 10:00 AM in the morning.

Location #06
Location #07 122
Location #08
Location #09
30
50
70
90
110
130
150
170
02/16/2007 02/17/2007 02/18/2007
Time
Temperature (*F)
Location #01
Location #02
Location #03
Location #04
Location #05
Location #06
Location #07
Location #08
Location #09

Figure 5. 22: Three days temperature pattern from 02/16/2007 to 02/18/2007

5.2.2. Mid-air Temperature Data
The following figure shows measurement results of focused heat temperature at mid-
air focal points around Disney Hall. The measurement was conducted on October 2,
2006. Based on the datalogger research results, it was assumed that the temperatures
118
around Disney Hall would be highest between 2:00 pm to 3:00 pm. Actually, it was
not difficult to find out which side of the building had the hottest temperature around
Disney Hall; as expected, the figure below shows the south façade of the building
had higher temperatures than other facades. The east, west, and north façades of
building did not create as serious heat problems as the REDCAT marquee. However,
1
st
and Hope Streets intersection also had a high temperature of 115°F. It is likely that
the Founder’s Hall contributed to these temperatures. Directly in front of the
REDCAT marquee, the temperature range was between 130°F and 140°F. The
temperature in front of limestone surfaces was 112°F; evidently the limestone
surfaces reflected and focused radiant heat much less than REDCAT marquee
surfaces.

Figure 5. 23: Infrared thermometer measurement results
119
120
5.3. Results Comparison between Previous and Current Research
The current research has overlapped data periods with previous research in 2003.
Two weeks data of October in 2003 and 2006 were compared by each location. Also
Los Angeles downtown peak temperatures were compared to see whether the 2006
ambient temperatures were higher than 2003 or not. With these comparison charts, it
was possible to see whether the remediation actually reduced thermal glare problems.

5.3.1. Comparison Charts of Ground Temperature
The blue line in the graph below, shows current research data from 2006, and the red
line shows previous research data from 2003. The blue dash line shows ambient peak
temperature of LA downtown in 2006, and the red dashed line is for 2003. The
ambient temperatures of 2003 and 2006 were similar during this period. Thus, we
can simply compare dataloggers’ temperature data of 2003 and 2006 without
concerning about different weather conditions that could increase or decrease ground
temperatures.

The figure below shows temperatures of location 03, which was located in the road
paving. Generally, the temperature in 2006 was almost the same or slightly higher
than the temperature in 2003. This means that the total amount of reflected sunlight
was almost the same or larger than before the remediation.

AmbientTemp_2006
Location#03_2006
AmbientTemp_2003
Location#03_2003
30
50
70
90
110
130
150
170
18-Oct 20-Oct 22-Oct 24-Oct 26-Oct 28-Oct 30-Oct 1-Nov
Time
Temperature (*F)
AmbientTemp
_2006
Location#03_
2006
AmbientTemp
_2003
Location#03_
2003

Figure 5. 24: Location #03- Peak temperature comparison between 2003 and 2006

Location 04 also showed same result as location 03. Temperatures in 2006 were a
little higher than in 2003.

AmbientTemp_2006
Location#04_2006
AmbientTemp_2003
Location#04_2003
30
50
70
90
110
130
150
170
18-Oct 20-Oct 22-Oct 24-Oct 26-Oct 28-Oct 30-Oct 1-Nov
Time
Temperature (*F)
AmbientTemp
_2006
Location#04_
2006
AmbientTemp
_2003
Location#04_
2003

Figure 5. 25: Location #04- Peak temperature comparison between 2003 and 2006
121
Location 06 had a slight higher temperature than location 03 and 04. For most of the
time, there is at least a 5°F or 10°F higher temperature in 2006 than 2003.

AmbientTemp_2006
Location#06_2006
AmbientTemp_2003
Location#06_2003
30
50
70
90
110
130
150
170
18-Oct 20-Oct 22-Oct 24-Oct 26-Oct 28-Oct 30-Oct 1-Nov
Time
Temperature (*F)
AmbientTemp
_2006
Location#06_
2006
AmbientTemp
_2003
Location#06_
2003

Figure 5. 26: Location #06- Peak temperature comparison between 2003 and 2006

Location 07 had much higher temperature data than other locations. For October,
location 07 was the most serious focal point before the remediation and still is
getting most of radiant heat even after the remediation. Both in 2003 and 2006, the
highest temperatures almost reached to 140°F on October 21st and 22nd. Even
though the worst cases of both researches were almost same, most of the time, the
2006 temperatures were still higher than 2003.

122
AmbientTemp_2006
Location#07_2006
AmbientTemp_2003
Location#07_2003
30
50
70
90
110
130
150
170
18-Oct 20-Oct 22-Oct 24-Oct 26-Oct 28-Oct 30-Oct 1-Nov
Time
Temperature (*F)
AmbientTemp
_2006
Location#07_
2006
AmbientTemp
_2003
Location#07_
2003

Figure 5. 27: Location #07- Peak temperature comparison between 2003 and 2006

5.3.2. Comparison Data of Mid-air Temperature
In his previous research, Prof. Schiler recorded 348°F as the worst recorded case
before the remediation. This measurement was not documented officially but the
result was verbally stated by Prof. Schiler on December 4
th
, 2006. The focal point
data were not part of the contracted research and were not included in the contract
report. However, the data were one of the most important reasons to make the
remediation of Disney Hall. Gehry’s office and the County were informed of the
problem by separate memo, not included in the report.

The current research result was quite impressive. This research’s highest temperature
was 139°F, which was much lower than half of the previous research result. Both of
the worst cases were measured directly in front of REDCAT marquee, which
123
124
reflected a lot of sunlight. This result showed that the remediation made the marquee
surfaces less able to focus radiant heat than before. In this respect, it is possible to
say that the remediation was successful in reducing thermal glare problems. Before
the remediation, the 348°F focal point temperature was much higher than the highest
ground temperature which was up to 139.1°F in front of REDCAT, and it was clearly
a problematic temperature. Now the highest focal point temperature was 139°F after
the remediation, a little lower than the current highest ground temperature which was
148.1°F in front of REDCAT. The current focal point temperature at mid-air was not
as serious as before, but it still might be considered a high temperature.

However, it is necessary to understand that 139°F of lightweight foamcore surface
temperature does not mean that human body will also reach this temperature level
from standing just a several minutes in front of REDCAT marquee. As described
before, a high thermal mass like the human body increases temperature much more
slowly than that experienced in a low mass object like foamcore.

5.4. Problems
As previously explained, the thermal glare research was conducted with dataloggers
and infrared thermometer. The following two difficulties were found during the
thermal glare analysis process: missing dataloggers and surface temperature of
lightweight foamcore with wind.

125
While performing the thermal glare research, three dataloggers were lost. Because
the dataloggers were located in public locations, anyone could take them. To keep the
dataloggers safe, the dataloggers were completely fixed inside holes on the ground
with silicone glue. However, the loggers still needed to be checked very often and
replaced with new dataloggers if any of them was stolen.

The infrared thermometer measurement method also had a small problem. When
measuring the surface of lightweight foamcore, the surface temperature was
suddenly cooled down by a strong wind. On a windy day, it was not easy to measure
focused heat temperature on the foamcore surface. Thus, the measurement was
required to be conducted three times on quiet days with no wind. The most reliable
results were shown on this paper.

Even though these three problems existed, this study is able to prove whether or not
the remediation was successful for thermal glare issue. The remediation greatly
reduced the amount of focused high temperature at mid-air. By contrast, the
remediation failed to reduce the ground temperature in front of REDCAT. More
detailed conclusions will be explained in the following chapter.

126
CHAPTER 6
CONCLUSIONS

Two different research categories were explored in this thesis: visual glare and
thermal glare. Visual and thermal glares each have two effects. Thus four researches
were conducted separately, and the results from each research were different.

6.1. Visual Glare Issue
Visual glare research conclusions can be explained in two categories. The first
conclusion concerns the Disney Hall surface remediation for visual glare; the second
conclusion is about the camera test results to examine some suspicious features of
the automatic camera usage for the visual glare analysis method.

6.1.1. Disney Hall Glare Research Conclusions
So far, most glare research has been focused on visual glare problems inside a
building. There have been many studies all over the world intended to produce better
interior environments. However, we still don’t have much experience in analyzing
exterior visual glare problems. Especially today, specular building envelopes and
outdoor lighting fixtures are causing discomfort glare problems. While I was doing
research at Disney Hall, many tourists were talking and discussing about its glare
issues. It was surprising to see so many people aware of this issue. Especially for its
127
high profile, the Disney Hall can be a great case-study in this field of study. To start,
it is important to compare the level of glare problems before and after the Disney
Hall surface remediation.

This study shows that there are still glare problems on 1
st
Street and Grand Avenue
and 2
nd
Street and Grand Avenue in the early morning. There is not a serious visual
glare problem on 1
st
and Hope Streets and 2
nd
and Hope Streets. We might conclude
that the glare remediation reduced glare problems because the remediation was
previously applied only on 1
st
and Hope Streets and 2
nd
and Hope Streets. However,
the comparison between actual previous and current glare scores of these
intersections would indicate that there was no improvement by the remediation. If we
simply count on only the Schiler glare scores of Disney Hall, we might conclude that
the remediation made the visual glare problem even worse at certain field of view
especially on 2
nd
and Hope Street. This result raised some suspicions about the
research methodology. Even though exterior glare research has many variables to be
considered, it does not make logical sense that the remediation made the glare
problem worse. Anecdotal evidence suggests that the Disney Hall’s visual glare
problems were successfully solved or somewhat reduced by the remediation.

Thus, additional testing for the automatic camera was indicated to find out the reason
the current glare scores are worse than those before the remediation. Even though
this study could not prove whether or not the remediation reduced the visual glare
128
problems, I believe that there was an improvement by the remediation. This indicates
that corrections to the method are necessary.

6.1.2. Camera Test Conclusion
Camera test results suggest that using an automatic camera is not a proper technique
for visual glare research. When comparisons were done, it was discovered that glare
scores from different automatic cameras were different. One theory is that this result
was caused by an automatic camera function that is inherent in the camera’s software
to ameliorate glare problems in the resulting pictures. Camera manufacturers have
their own camera software that has different settings; thus it is very difficult to find
out how each automatic camera remediates the picture’s glare problems. This
suggests that it is necessary to use another type of camera such as a digital SLR
camera or a film camera for visual glare research.

The camera test shows that visual glare analysis also has other variables to be
concerned about and also suggests that a manual camera is one of possible solutions
to get more reliable glare scores.

6.2. Thermal Glare Issue
There were two thermal glare issues regarding ground temperature and mid-air
temperature. Even though both were researched in front of the REDCAT marquee,
each temperature issue has a different research approach and result.
129
6.2.1. Ground Temperature Research Conclusion
The surface remediation of REDCAT marquee did not make any improvement in
ground temperature. The worst case of ground temperature was up to 148.1°F on
September, 2006. This record was even higher than previous worst temperature
record which was 139.1°F on July, 2004. Even though these two worst cases were
from different months of different year, this result suggests there are still problems of
thermal glare local heating.

The actual comparison charts of temperature data from October 2003 and 2006 show
how much temperature was decreased or increased by the remediation. The
comparison charts show no difference of ground temperatures before and after the
remediation with quite similar ambient air temperature of downtown Los Angeles on
October 2003 and 2006. Moreover, the ground temperature in 2006 was even
somewhat higher that ground temperature in 2003. This means that the surface
treatment on the REDCAT marquee did not result in a change of ground temperature.

This study suggested that ground temperature was actually increased by radiant heat
from the REDCAT marquee. Through the comparison between dataloggers directly
in front of REDCAT and dataloggers away from REDCAT, it was possible to find the
local heating effect from the highly reflective building surfaces. A large amount of
heat from the sun was accumulated on the ground surface. However, the ground
surface directly in front of REDCAT is not only getting heat from direct sun but also
130
receiving radiant heat from REDCAT marquee surfaces. During hot summer days,
the difference between ground temperatures in front of the REDCAT and ground
temperatures far from REDCAT was almost 15°F. For the cold winter days, the
difference was up to 30°F. This result was larger than what I expected before the
study. This has implications for heat island and global warming.

There are many variables that can increase exterior ground temperature. However, it
is possible to say that vibrating or orbital sanding was not an effective solution to
reduce heat reflection to the ground from the REDCAT marquee surfaces. The
stainless steel panels are still reflecting heat from the sun to the surroundings and
increasing ground temperatures. More effective solutions such as changing REDCAT
marquee surface reflectance or the angle towards sky would be required to reduce
thermal glare problems.

One datalogger, which was installed under trees, shows quite similar temperature
record to downtown Los Angeles’s ambient peak temperature even though the logger
is not far from the REDCAT marquee. This means the radiant heat from the marquee
did not increase the ground temperature under the trees. From the temperature data,
we can see more interesting results especially on sunny days. The datalogger under
the trees read up to 30°F less than the other dataloggers that were installed right in
the sun. A certain amount of sunlight and radiant heat was actually blocked by tree
leaves, and some passed through tree leaves. Different from building materials, the
131
living plants are absorbing heat from the sun and reradiating less heat by evaporating
water. This result suggests that trees and plants could be another solution to reduce
thermal glare problems of Disney Hall or even to reduce heat island effect in a big
city.

6.2.2. Mid-air Temperature Research Conclusion
There was a serious heat problem in mid-air in front of the REDCAT marquee. The
curvature of polished stainless steel panels were not only reflecting strong sunlight to
the surroundings but also focusing large amounts of heat at certain angle at ground
and mid-air. Different sun angles made these critical points move around in front of
REDCAT, and it was difficult to measure this focused heat using dataloggers. Instead
of dataloggers, lightweight foamcore and an infrared thermometer were used to
measure the temperature. Even though there are not many pedestrians walking or
waiting at the REDCAT, there was a serious concern that this problem might cause
damage to people. The temperature record of 348°F from previous research was
enough reason to correct the problem. The present research shows the surface
treatment of REDCAT marquee did reduce the problem, but the temperature 139°F
indicated in current study is still very high.

However, this radiant gain is not dangerous to a human body unless he or she is
staying under this temperature for a long time. This can be explained with the
different material properties of lightweight foamcore and human body. As described
132
in Chapter 05, the lightweight foamcore, which has a low thermal mass, increases
temperature more rapidly than the human body. Of course, if a human body is
exposed to the radiant heat gain for a long time, its surface temperature would also
reach 139°F. Corrective action could be taken, and the body would begin to sweat to
reduce temperature. But at the least, there would be a rapid sunburn. Additional
treatment could be suggested for reducing the mid-air surface temperature, but it is
not seriously required and there are aesthetic considerations that might preclude it
happening. In any case, it is much better than the previous ~348°F temperatures.

In general, the remediation of Disney Hall was only partly successful. It diffused the
focal point glare, but did not reduce ground temperature. There was no demonstrated
reduction in overall visual glare. This would require more extreme measures, such as
changing the shape or the material of the reflective surfaces. However, the
remediation successfully kept the aesthetic value of Disney Hall and relieved the
surrounding neighbors and LA County of their concerns by reducing the focal point
glare. It is possible to say that the remediation was the best choice for all parties of
the Disney Hall glare issue.
133
CHAPTER 7
FUTURE WORK

Future studies should be done to pursue the unknown variables in exterior glare
analysis and to further assess the known variables in the existing exterior glare
analysis methodology. The following are the research topics that need to be
addressed to make this thesis results more reliable. Some topics are closely related to
the Disney Hall glare problem and others are more related to exterior glare
methodology overall.

7.1. Recording Temperature inside the Promenade condominiums
Even though temperature measurements were not taken in the Promenade Tower
condominiums before the Disney Hall remediation and direct comparisons can not be
made, it would be interesting to know what the current temperates are inside the
units. It might even be possible to do computer simulations for the before state and
compare with current measurements. One could then test Schiler’s assumption that
defocusing the mid-air focal points would reduce the build up in specific apartments
and diffuse the results to approximately equal to any other reflections from
surrounding reflective building surfaces.

134
Using dataloggers such as iButton and Hobo, it would be possible to measure room
temperatures and relative humidity from some units that have big windows facing to
the Disney Hall. Then one could determine if there is any unit that has extremely
higher temperatures than others during certain periods of time. Based on this result,
we can evaluate the relation between radiant heat from Disney Hall and temperature
inside Promenade Tower condominiums. The interaction of the HVAC systems in the
units would be a variable, unless two units could be left unconditioned.

7.2. Manual Camera Test for Visual Glare Analysis
This thesis has already demonstrated that an automatic camera is not an appropriate
tool to analyze visual glare problems without consideration and mitigation of serious
problems. Using a Nikon D200 (a digital SLR camera), we also found out that it
would be better to use a manual camera to get more reliable glare scores from
pictures.

It would be interesting to see whether different manual cameras make the same glare
scores from the same picture or not. It is necessary to make lots of tests with
different circumstances. A film camera also can be used to photograph glare sources.
Different from a digital camera, a film camera requires an additional step to scan the
photograph, and this additional step can be another variable that affects glare scores.

135
7.3. Measurement of Actual Luminance for Absolute Glare
The Schiler Glare Method defines a likelihood of discomfort glare based on the ratio
between glare source luminance and median background luminance. It is reasonable
to use this ratio to define discomfort glare if background luminance is in a reasonable
range. However, if both of the glare source and background luminance level is
extremely high, we can get an absolute glare problem instead of a contrast glare. This
may well account for the fact that there are no complaints now, whereas there were
complaints before remediation.

In photographs, the luminance histogram defines the maximum luminance value as
255 and the minimum luminance value as 0. With the current version of Schiler glare
method, it is impossible to recognize an absolute glare condition because the ratio
between the bright glare source and bright background can not be any higher than
that. For interior glare analysis, the Schiler Glare Method uses a known luminance
box which can indicate the actual luminance level. Thus, the exterior glare analysis
also needs to get the actual luminance value using a known luminance box or a
luminance sensor. With this additional measurement, it might be possible to define
an absolute glare threshold for problems.

There are also other possible future works related to this study. For visual glare issue,
percentage of the view occupied by higher levels or distribution of higher levels
needs to be investigated because it might cause different eye perception from glare
136
problems. It is also important to find out whether or not the line of sight is more
important than the edges in a field of view. For thermal glare issue, it is necessary to
find out if there are any other buildings or the contributions to the heat island effect
around Disney Hall.

It would be interesting to test some of the other glare methods entitled in Chapter 2
to see if their results are consistent in before and after cases.
137
BIBLIOGRAPHY

BoiFromTroy. 2004. Disney Hall Hazard. BoiFromTroy. 27 November. Available
from:
http://boifromtroy.com/?p=3233 [Accessed 4 September 2006]

Clinton, Bill. 1996, December. Radiant Panel Report. Available from:
http://www.radiant-floor-heating.com/radiant-heat.htm [Accessed 4 September 2006]

Egan, M. David. 1983. Concepts in Architectural Lighting. McGraw-Hill Book
Company. ISBN 0-07-019054-2

Egan, M. David & Olgyay, Victor W. 2002. Architectural Lighting. McGraw-Hill.
ISBN 0-07-020587-6

Environmental Protection Agency (Lead Author); Cleveland, Cutler J. (Topic Editor).
2006. Heat island [online]. Encyclopedia of Earth. Eds. Cutler J. Cleveland
(Washington, D.C.: Environmental Information Coalition, National Council for
Science and the Environment). Available from:
http://en.wikipedia.org/wiki/Light_pollution#Glare [Accessed 4 September 2006]
http://www.eoearth.org/article/Heat_island [Accessed 5 September 2006]

Glaister, Dan. 2004. Disney Hall loses its sheen. The Sydney Morning Herald. 10
December. Available from:
http://www.smh.com.au/news/Arts/Disney-Hall-loses-its-sheen/2004/12/09/1102182
[Accessed 4 September 2006]

Hwang, Sung-Chul & Kim, Kang-Soo. 2002, May. Control of Daylight Environment
in Interior Spaces: Prediction of Dsylight Glare from Windows by Using a Computer
Program

Janssen, David E. 2004. Walt Disney Concert Hall- Glare Issue. Chief Administrative
Office. County of Los Angeles

138
Japee, Shweta & Schiler, Marc. 1995. A Method of Post Occupancy Glare Analysis
for Building Energy Performance Analysis. The American Solar Energy Conference

Köster, Helmut. 2004. Dynamic Daylighting Architecture: Basics, Systems, Projects.
Birkhäuser-Publishers for Architecture. ISBN 3-7643-6729-6

Pogrebin, Robin. 2004. Gehry Would Blast Glare Off Los Angles Showpiece. Wired
New York- Forum. 2 December. Available from:
http://www.wirednewyork.com/forum/showthread.php?t=3773&page=2 [Accessed 4
September 2006]

Pon, Brian. 1999. L.A.ISLAND [online]. Available from:
http://eetd.lbl.gov/HeatIsland/LEARN/LAIsland/ [Accessed 4 September 2006]

Rea, Mark S. & Ouelletue, Michael J. 1991, April. Relative Visual Performance: A
Basis for Application. Lighting Research and Technology. V ol. 23, No. 3, p. 135-144

Schiler and Associates. 2004, July. Disney Hall Glare Study-Final Report

Schiler, Marc. 2000, July. Toward a Definition of Glare: Can Qualitative Issues Be
Quantified?. ARCC Conference on Architectural Research

Schiler, Marc & Valmont, Elizabeth. 2005, August. Microclimatic Impact: Glare
Around the Walt Disney Concert Hall. Solar World Conference 2005

Tedjakusuma, Jonathan. 2003. A Visual and Digital Method for predicting
Discomfort Glare. University of Southern California

Temperatures.com. 2006. Temperature Sensor Types. Available from:
http://www.temperatures.com/sensors.html [Accessed 4 Semtember 2006]

Veitch, J.A., Newsham, G.R. 2006, May. Determinants of Lighting Quality I: State of
the Science. NRCC-39866. Available from:
http://irc.nrc-cnrc.gc.ca/pubs/fulltext/nrcc39866.php [Accessed 22 January 2007]
139
Wienold, Jan & Christoffersen, Jens. 2006, July. Evaluation methods and
development of a new glare prediction model for daylight environments with the use
of CCD cameras, Energy and Buildings, V olume 38, Issue 7

Wikipedia. 2006. Available from:
http://en.wikipedia.org/wiki/Microclimate [Accessed 4 September 2006]
http://en.wikipedia.org/wiki/Field_of_view [Accessed 5 September 2006]
http://en.wikipedia.org/wiki/Heat_capacity [Accessed 20 September 2006]
http://en.wikipedia.org/wiki/Specific_heat_capacity [Accessed 4 September 2006]
http://en.wikipedia.org/wiki/Data_logger [Accessed 11 September 2006]
http://en.wikipedia.org/wiki/Infrared_thermometer [Accessed 11 September 2006]
APPENDIX A
DATALOGGER LOCATIONS IN PREVIOUS RESEARCHES

Figure A. 1: Datalogger locations on March, 2003
140

Figure A. 2: Datalogger locations on July, 2004
141
APPENDIX B
PHOTOGRAPHS OF DISNEY HALL on September 23
rd
, 2006

Figure B. 1: 1
st
Street and Grand Avenue from 6:30 AM to 10:00 AM
142

Figure B. 2: 1
st
Street and Grand Avenue from 10:30 AM to 2:30 PM
143

Figure B. 3: 1
st
Street and Grand Avenue from 3:00 PM to 5:00 PM
144

Figure B. 4: 2
nd
Street and Grand Avenue from 6:30 AM to 10:00 AM
145

Figure B. 5: 2
nd
Street and Grand Avenue from 10:30 AM to 2:00 PM
146

Figure B. 6: 2
nd
Street and Grand Avenue from 2:30 PM to 6:00 PM
147

Figure B. 7: 1
st
and Hope Streets from 6:30 AM to 10:00 AM
148

Figure B. 8: 1
st
and Hope Streets 10:30 AM to 2:00 PM
149

Figure B. 9: 1
st
and Hope Streets from 2:30 PM to 6:00 PM
150

Figure B. 10: 2
nd
and Hope Streets from 6:30 AM to 10:00 AM
151

Figure B. 11: 2
nd
and Hope Streets from 10:30 AM to 2:00 PM
152

Figure B. 12: 2
nd
and Hope Streets from 2:30 PM to 6:00 PM
153
APPENDIX C
IMAGE ANALYSIS PROCEDURES MANUAL BY JEFF CULP

Figure C. 1: Image analysis procedure manual, page 1
154

Figure C. 2: Image analysis procedure manual, page 2

155

Figure C. 3: Image analysis procedure manual, page 3

156

Figure C. 4: Image analysis procedure manual, page 4

157

Figure C. 5: Image analysis procedure manual, page 5

158
APPENDIX D
GROUND TEMPERATURE DATA- 08/30/2006 ~ 03/03/2007
08/30/2006~09/16/2006
148.1 148.1
30
50
70
90
110
130
150
170
08/30/2006 09/06/2006 09/13/2006
Time
Temperature (*F)
Location #1
Location #2
Location #3
Location #4
Location #5
Location #6
Location #7
Location #8
Location #9
Figure D. 1: Ground temperature from 08/30/2006 to 09/16/2006

159
134.6
126.5
30
50
70
90
110
130
150
170
09/16/2006 09/23/2006 09/30/2006 10/07/2006
Time
Temperature (*F)
Location #01
Location #02
Location #03
Location #04
Location #05
Location #06
Location #07
Location #08
Location #09
Figure D. 2: Ground temperature from 09/16/2006 to 10/08/2006
160

122.9
135.5
30
50
70
90
110
130
150
170
10/08/2006 10/15/2006 10/22/2006 10/29/2006
Time
Temperature (*F)
Location #01
Location #02
Location #03
Location #04
Location #05
Location #06
Location #07
Location #08
Location #09
Figure D. 3: Ground temperature from 10/08/2006 to 11/04/2006
161

115.7
130.1
30
50
70
90
110
130
150
170
11/04/2006 11/11/2006 11/18/2006 11/25/2006
Time
Temperature (*F)
Location #01
Location #02
Location #03
Location #04
Location #05
Location #06
Location #07
Location #08
Location #09
Figure D. 4: Ground temperature from 11/04/2006 to 12/02/2006
162

30
50
70
90
110
130
150
170
12/02/2006 12/09/2006 12/16/2006 12/23/2006 12/30/2006 01/06/2007
Time
Temperature (*F)
Location #01
Location #02
Location #03
Location #04
Location #05
Location #06
Location #07
Location #08
Location #09
Figure D. 5: Ground temperature from 12/02/2006 to 01/07/2007
163

30
50
70
90
110
130
150
170
01/07/2007 01/14/2007 01/21/2007 01/28/2007
Time
Temperature (*F)
Location #01
Location #02
Location #03
Location #04
Location #05
Location #06
Location #07
Location #08
Location #09
Figure D. 6: Ground temperature from 01/07/2007 to 02/03/2007
164

122 122
30
50
70
90
110
130
150
170
02/03/2007 02/10/2007 02/17/2007 02/24/2007
Time
Temperature (*F)
Location #01
Location #02
Location #03
Location #04
Location #05
Location #06
Location #07
Location #08
Location #09
Figure D. 7: Ground temperature from 02/03/2007 to 03/03/2007
165

Abstract (if available)

Abstract This thesis further develops research undertaken about the Walt Disney Concert Hall. Originally admired for its beautiful, shiny, curved façade, the concert hall was also noteworthy as a source of visual glare and heat. These concerns led to the County of Los Angeles hiring of a consultant to quantify the problems and suggest resolutions. The solution undertaken was to sand key problem areas of the stainless steel façade. After this treatment, complaints stopped, but no one tested the actual resulting levels of thermal and visual glare. This study re-examines these issues after the surface treatment. An infrared thermometer and dataloggers were used to record mid-air temperature and ground temperature in front of the adjoining REDCAT theater. Using photographs of Disney Hall and luminance histograms, visual glare scores were evaluated. The comparison between previous and current research results tells whether or not the remediation was successful to reduce the glare problems.

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Asset Metadata

Creator Suk, Jae Yong (author)

Core Title Post-treatment analysis of the glare remediation of the Walt Disney Concert Hall

School School of Architecture

Degree Master of Building Science

Degree Program Building Science

Degree Conferral Date 2007-05

Publication Date 04/23/2007

Defense Date 03/28/2007

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag datalogger,heat island effect,luminance histogram,microclimate,OAI-PMH Harvest,radiant heat,visual glare,Walt Disney Concert Hall

Place Name buildings: Walt Disney Concert Hall (geographic subject), California (states), Los Angeles (city or populated place), Los Angeles (counties), USA (countries)

Language English

Advisor Schiler, Marc E. (committee chair), Brogden, Teal (committee member), Kensek, Karen (committee member), Woll, Edwin (committee member)

Creator Email jsuk@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m438

Unique identifier UC1463324

Identifier etd-Suk-20070423 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-497517 (legacy record id),usctheses-m438 (legacy record id)

Legacy Identifier etd-Suk-20070423.pdf

Dmrecord 497517

Document Type Thesis

Rights Suk, Jae Yong

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Repository Name Libraries, University of Southern California

Repository Location Los Angeles, California

Repository Email cisadmin@lib.usc.edu