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Comparing visual comfort metrics for fourteen spaces using simulation-based luminance mapping

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COMPARING VISUAL COMFORT METRICS FOR FOURTEEN SPACES USING
SIMULATION-BASED LUMINANCE MAPPING

by

William Vicent
________________________________________________________________________

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

August 2012

Copyright 2012 William Vicent
ii

ACKNOWLEDGMENTS
To Chris Buntine: I would like to express my deepest appreciation. Though not directly
involved with this research, your encouragement to mine the natural world for technical
design-solutions has been a guiding light. You are an uncompromised pillar of
sustainability and will continue to be a professional and personal inspiration to me.
To Lisa Heschong: Thank you for your kindness, generosity and support with this work.
For years, you have encouraged in me a more thoughtful and delightful approach to
design; first through written word, now in person. Thank you for always being positive,
motivating, and most importantly, for making yourself accessible to those aspiring.
To Kosta Papamichael: Thank you for your sincere and enthusiastic guidance. Your
insights and detailed explanations were invaluable in maturing my understanding of this
subject matter. I could not have completed this research without your support.
To Marcela Oliva and Michael Rendler: Thank you for your compassion and your vision.
Through your selfless efforts, you’ve constructed a bridge between learning and practice,
gifting many – including myself – the opportunity to play an active role in the built
environment.
To Michael Bulander, Sylvia Wallis, Elisabeth Newell, Dan Benjamin and Alok Singh:
Thank you for your mentorship and for your steadfast support in pursuing this degree. I
have learned so much from you.
iii

To my thesis committee – Professors Marc Schiler, Karen Kensek and Anders Carlson:
Thank you for your patience in steering me towards an end result I can be proud of.
Lastly to my family – Ivette, Mom, Dad, Val, Juju, Bella, B, and T: Your unconditional
love and support are my foundation. Through this work, you have been so understanding
in my time of absence and so reassuring in my time of doubt. I love you with all my
heart. Thank you.

iv

TABLE OF CONTENTS
ACKNOWLEDGMENTS .................................................................................................. ii
LIST OF FIGURES .......................................................................................................... vii
LIST OF TABLES ............................................................................................................. xi
ABSTRACT ...................................................................................................................... xii
CHAPTER 1: INTRODUCTION ....................................................................................... 1
1.1 Hypothesis ................................................................................................................. 1
1.2 Daylighting in Buildings ........................................................................................... 1
1.3 Quantifying Daylighting ........................................................................................... 2
1.4 Daylight Caveats ....................................................................................................... 4
1.5 Daylighting Codes and Standards ............................................................................. 5
CHAPTER 2: BACKGROUND ......................................................................................... 7
2.1 Two Daylighting Metrics .......................................................................................... 7
2.2 Visual Comfort .......................................................................................................... 7
2.3 Illuminance vs. Luminance ....................................................................................... 8
2.4 Glare Metrics ........................................................................................................... 10
2.5 Glare Definitions ..................................................................................................... 11
2.6 Visual Comfort Simulation Processes ..................................................................... 13
2.7 High Dynamic Range (HDR) Luminance Maps ..................................................... 14
2.8 Rendered Luminance Maps ..................................................................................... 16
2.9 Analyzing Luminance Maps ................................................................................... 17
2.10 Evalglare ................................................................................................................ 18
2.12 The Visual Comfort Conundrum........................................................................... 22
CHAPTER 3: RESEARCH METHOD ............................................................................ 26
3.1 Research Method Overview .................................................................................... 26
3.2 Daylight Metrics Project ......................................................................................... 26
3.3 Simulation Modeling Host ...................................................................................... 28
v

3.4 Simulation Overview ............................................................................................... 29
3.5 Material Definitions ................................................................................................ 29
3.6 Import Master Ecotect Material Library ................................................................. 30
3.7 Import Radiance Geometry File .............................................................................. 31
3.8 Import Weather File ................................................................................................ 33
3.9 Setup Camera Views ............................................................................................... 33
3.10 Radiance Export .................................................................................................... 34
3.11 Evalglare ................................................................................................................ 36
3.12 Batch Processing and Consolidating Results ........................................................ 37
3.13 Statistical Methods ................................................................................................ 40
CHAPTER 4: RESULTS .................................................................................................. 41
4.1 Results Overview .................................................................................................... 41
4.2 Ecotect Models ........................................................................................................ 41
4.3 Luminance Maps ..................................................................................................... 42
4.4 Sky Conditions ........................................................................................................ 43
4.5 Days of the Year ...................................................................................................... 44
4.6 Times of Day ........................................................................................................... 45
4.7 View Orientations ................................................................................................... 46
4.8 Evalglare Check Files .............................................................................................. 48
4.9 Evalglare Numeric Results ...................................................................................... 49
CHAPTER 5: ANALYSIS ............................................................................................... 50
5.1 Indices Normalization ............................................................................................. 50
5.2 Glare Indices Agreement ......................................................................................... 56
5.3 Effects of Conditions on Agreement ....................................................................... 62
5.4 Time of Year ........................................................................................................... 62
5.5 Sky Conditions ........................................................................................................ 64
5.6 Daylight Glare Probability ...................................................................................... 68
5.7 Daylight Metrics Project ......................................................................................... 70
5.8 Correlations with DMP Survey Data ...................................................................... 72

vi

CHAPTER 6: CONCLUSIONS ....................................................................................... 76
6.1 Summary of Findings .............................................................................................. 76
6.2 Future Work ............................................................................................................ 76
ENDNOTES ..................................................................................................................... 79
BIBLIOGRAPHY ............................................................................................................. 82
APPENDIX A: ECOTECT MODELS ............................................................................. 84
APPENDIX B: SIMULATION PARAMETERS ............................................................. 98
APPENDIX C: EVALGLARE VIEWS ......................................................................... 100
APPENDIX D: ALL VISUAL COMFORT RESULTS ................................................. 114

vii

LIST OF FIGURES
Figure 1: Ancient and Modern Daylighting Apertures ....................................................... 2
Figure 2: Walt Disney Concert Hall and View Showing Specular Glare ........................... 5
Figure 3: Illuminance vs. Luminance ................................................................................. 9
Figure 4: Luminance Maps with Perspective View vs. Fish Eye View ............................ 14
Figure 5: Multiple LDR Exposures Imported Into Bracket .............................................. 15
Figure 6: Single HDR Image Created from Multiple LDR Images .................................. 16
Figure 7: Evalglare Check File Highlighting Potential Glare ........................................... 19
Figure 8: Advanced Export to Radiance Using Ecotect ................................................... 30
Figure 9: Custom Material Library Import in Ecotect ...................................................... 31
Figure 10: Radiance Geometry Import Dialogue in Ecotect ............................................ 32
Figure 11: Radiance Geometry Imported, Materials Assigned in Ecotect ....................... 32
Figure 12: View Cameras Created in Ecotect ................................................................... 33
Figure 13: View Cameras Shown in Plan in Ecotect ........................................................ 34
Figure 14: Ecotect Export to Radiance Control Panel ...................................................... 35
Figure 15: Ecotect Camera Simulated in Radiance .......................................................... 35
Figure 16: Window Command Processor Showing Evalglare ......................................... 36
Figure 17: Evalglare Check File Highlighting Glare Locations ....................................... 37
Figure 18: Example Batch Execution Using Evalglare .................................................... 38
Figure 19: Batch Results Automatically Written to Text File .......................................... 39
Figure 20: Batch Glare Results Imported Into Excel ........................................................ 39
Figure 21: Four Sample Luminance Maps Simulated with Radiance .............................. 42
viii

Figure 22: CIE Clear Sky Model vs.CIE Overcast Sky Model ........................................ 43
Figure 23: Luminance Maps Showing Sky Variation....................................................... 44
Figure 24: Luminance Maps Showing Seasonal Variation ............................................... 45
Figure 25: Luminance Maps Showing Day Variation ...................................................... 46
Figure 26: Luminance Maps Showing View Orientation Variation ................................. 47
Figure 27: Luminance Map Before and After Evalglare .................................................. 48
Figure 28: Partial View of Master Spreadsheet for Numeric Glare Results ..................... 49
Figure 29: Glare Dataset for a Single Space ..................................................................... 54
Figure 30: Annual Glare Map from Diva-for-Rhino ........................................................ 55
Figure 31: Evalglare Results for Low Brightness Scene .................................................. 55
Figure 32: Luminance Map Highlighting VCP with Overcast Sky .................................. 58
Figure 33: 5 Scaled Glare Indices for 1008 Views ........................................................... 59
Figure 34: 5 Scaled Glare Indices for a Single Space ....................................................... 61
Figure 35: Clear Sky Views for a Single Space ................................................................ 67
Figure 36: Overcast Sky Views for a Single Space .......................................................... 68
Figure 37: DGP Results for 1008 Views .......................................................................... 69
Figure 38: Ecotect Model #1 (Perspective and Plan Showing Views) ............................. 84
Figure 39: Ecotect Model #2 (Perspective and Plan Showing Views) ............................. 85
Figure 40: Ecotect Model #3 (Perspective and Plan Showing Views) ............................. 86
Figure 41: Ecotect Model #4 (Perspective and Plan Showing Views) ............................. 87
Figure 42: Ecotect Model #5 (Perspective and Plan Showing Views) ............................. 88
Figure 43: Ecotect Model #6 (Perspective and Plan Showing Views) ............................. 89
ix

Figure 44: Ecotect Model #7 (Perspective and Plan Showing Views) ............................. 90
Figure 45: Ecotect Model #8 (Perspective and Plan Showing Views) ............................. 91
Figure 46: Ecotect Model #9 (Perspective and Plan Showing Views) ............................. 92
Figure 47: Ecotect Model #10 (Perspective and Plan Showing Views) ........................... 93
Figure 48: Ecotect Model #11 (Perspective and Plan Showing Views) ........................... 94
Figure 49: Ecotect Model #12 (Perspective and Plan Showing Views) ........................... 95
Figure 50: Ecotect Model #13 (Perspective and Plan Showing Views) ........................... 96
Figure 51: Ecotect Model #14 (Perspective and Plan Showing Views) ........................... 97
Figure 52: Ecotect to RadianceCP Export Settings .......................................................... 98
Figure 53: Radiance CP Scene Definitions ....................................................................... 99
Figure 54: RadianceCP Batch Render Dialogue ............................................................... 99
Figure 55: Evalglare Views for Model #1 ...................................................................... 100
Figure 56: Evalglare Views for Model #2 ...................................................................... 101
Figure 57: Evalglare Views for Model #3 ...................................................................... 102
Figure 58: Evalglare Views for Model #4 ...................................................................... 103
Figure 59: Evalglare Views for Model #5 ...................................................................... 104
Figure 60: Evalglare Views for Model #6 ...................................................................... 105
Figure 61: Evalglare Views for Model #7 ...................................................................... 106
Figure 62: Evalglare Views for Model #8 ...................................................................... 107
Figure 63: Evalglare Views for Model #9 ...................................................................... 108
Figure 64: Evalglare Views for Model #10 .................................................................... 109
Figure 65: Evalglare Views for Model #11 .................................................................... 110
x

Figure 66: Evalglare Views for Model #12 .................................................................... 111
Figure 67: Evalglare Views for Model #13 .................................................................... 112
Figure 68: Evalglare Views for Model #14 .................................................................... 113

xi

LIST OF TABLES
Table 1: Typical Luminance Values ................................................................................... 9
Table 2: Glare Indices Evaluation Ranges ........................................................................ 51
Table 3: Scaled Glare Indices Evaluation Ranges ............................................................ 51
Table 4: Glare Indices Agreement .................................................................................... 56
Table 5: September Views Agreement ............................................................................. 63
Table 6: December Views Agreement .............................................................................. 64
Table 7: Clear Sky Views Agreement .............................................................................. 65
Table 8: Overcast Sky Views Agreement ......................................................................... 66
Table 9: DMP Survey Question Agreements.................................................................... 74
Table 10: All Visual Comfort Results ............................................................................ 114

xii

ABSTRACT
As annual daylight simulation methods become more prominent in the building design
industry there exists a stronger need and a clearer path for daylight simulation programs
to calculate annual visual comfort metrics. A single metric for predicting visual comfort
for an entire space and for an entire year could be incredibly useful if one could be
created. Though nascent and very time-intensive, capabilities for calculating annual glare
probabilities for whole spaces currently exist. However, unlike daylight sufficiency
metrics, there seems to be no clear, undisputed industry consensus when it comes to
visual comfort metrics in daylight conditions, making annual glare capabilities slightly
preemptive. Accordingly, this work aims to highlight some of the strengths and
weaknesses of some of the leading visual comfort metrics (DGP, DGI, UGR, VCP and
CGI) under annualized processes. Ultimately, this work outlines a luminance-based
simulation process for predicting annual visual comfort and correlates these results with
an existing dataset of field administered occupant surveys. The two metrics developed for
this work, DGPmax and DGPave, are shown to have the high potential for metric
candidacy.

1

CHAPTER 1: INTRODUCTION
1.1 Hypothesis
Simulation-based luminance maps can be used in aggregate to predict annual visual
comfort for a daylit space.

1.2 Daylighting in Buildings
For over five thousand years, natural light has helped sculpt the forms and functions of
some of the most well-known man-made structures the Earth has seen. The Megalithic
Temples at Malta (3500-2500 BC), the Pyramid of Zoser (2667-2648 BC) and the
Pantheon in Rome (125 AD) (Figure 1) are all considered by many to be ancient
masterpieces. It is without coincidence that all of these structures demonstrate a high-
level of respect for the sun. Ancient civilizations not only worshipped the sun but also
displayed masterful uses of its dynamic nature. The Mayans’ Kukulkan Pyramid casts a
shadow of a serpent on its north steps twice each year at the fall and spring equinoxes.
The Neolithic monument in Eastern Ireland fills with light only once a year to reveal an
ornate central chamber. Historically, builders and designers have continued to
demonstrate magnificent responses to the sun within buildings as exemplified through
Gothic cathedrals, the mosques of Islamic Architecture, and the relatively recent works of
Alvar Aalto and Renzo Piano (California Academy of Sciences shown in Figure 1).
Presently – even with the magnificent invention of artificial, electric light – contemporary
architecture continues to deploy a proliferation of imaginative daylighting strategies.

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 reduced mechanical heating and cooling loads
 reduced peak energy usage
 increased property value
 increased occupancy health
ii

 increased worker productivity
iii

 higher sales for retail environments
iv

 increased student learning in classroom environments
v

With all the apparent benefits of daylighting design, daylight itself should be the primary
chisel with which the human-built environment is shaped. Daylighting and views are
essential to the human well-being; the counter condition of being confined for long
periods of time without light or view to the outside is considered a form of punishment.
In understanding the value and need for well-daylit buildings, the building industry itself
has begun to shift its paradigm by insisting that daylighting in buildings be mandatory for
newly constructed buildings. For example, the U.S. Army has adopted ASHRAE
Standard 189.1, Standard for the Design of High-Performance, Green Buildings. This
standard has specific minimum requirements for daylighting including sidelighting for
offices and classrooms as well as skylights for large open spaces under a roof. Similar
examples of daylighting requirements in new buildings have been adopted by the
University of California, the Los Angeles Community College District, and even the
State of California.

4

1.4 Daylight Caveats
Although there are many benefits associated with daylighting in buildings, there are also
several detriments associated with poor daylighting design including overheating and
glare. Overheating occurs when too much daylight is allowed into occupied spaces,
increasing space temperatures, and thereby increasing mechanical cooling loads and the
buildings overall energy consumption. In all climates – but especially in hot climates –
daylighting should be invited into buildings in a delicate balance with lighting, heating,
and cooling all considered. Overheating or over-daylighting can overwork a building’s
mechanical systems and can also compromise occupant thermal comfort. Imagine a
scenario when the direct summer sun finds its way into a building and onto your back
while you are reading. This can be quite uncomfortable, can force you to move, close
some window shades, or in extreme cases can force you to leave a room. The other, less
understood detriment to poor daylighting design is glare. Though the term glare is
common to most people, the quantitative interpretation of this phenomenon is quite
complex and can have some very serious implications if ignored. The Walt Disney
Concert Hall (Figure 2) is a fantastic example of the potential implications of ignoring
glare.
5

Figure 2: Walt Disney Concert Hall and View Showing Specular Glare

After completion, repeated complaints from nearby residents forced the County of Los
Angeles to commission a remediation effort to mitigate the glare being reflected by the
building. Ultimately, selected portions of the building’s metal façade (4,000 square feet
of the 200,000 square feet of cladding) were sanded down so as to reduce the material’s
specularity.
vi

1.5 Daylighting Codes and Standards
Consistently, one major driver affecting daylighting design decisions in the building
industry are codes and standards. Codes are meant to provide minimum safeguards for
people with regard to building health, safety and welfare; standards are consensus-based
extensions of code requirements. In California, the International Building Code (IBC)
6

and the California Energy Commission’s (CEC) Title-24 Standard serve to outline these
minimum quantitative requirements for new construction. These documents are not
meant to be cutting-edge design guidelines but rather specifications of a minimum level
of building performance. Compliance with these documents is mandatory, and thus they
are typically aimed at lowest common denominators. There are also various voluntary
building design standards, such as: Leadership in Energy and Environmental Design
(LEED), California High Performance Schools (CHPS), and Build It Green. These
standards tend to be more aggressive than mandatory code requirements. Both of these
types of standards, mandatory and voluntary, rely heavily on quantitative targets and
scales (also known as metrics) for verification of performance. As is done with building
life-safety, structure, egress, and energy consumption, quantitative targets must be
arranged before they can be adopted by codes and standards. Specifically with regards to
visual comfort, little or no requirements exist within codes and standards to mandate
minimum levels for new construction. This is not a trivial task, especially since visual
comfort is a highly subjective phenomenon.

7

CHAPTER 2: BACKGROUND
2.1 Two Daylighting Metrics
Defining daylighting metrics can be very difficult in that daylighting is both highly
quantitative and highly qualitative. The term daylight sufficiency can be used to refer to
daylight quantity while the term visual comfort can be used to refer to daylighting
quality. The building industry has had repeated success in creating daylighting metrics
adopted by codes and standards programs with respect to daylight sufficiency. Daylight
Factor and IESNA Task Illuminance are two examples of industry consented daylight
sufficiency metrics. With each of these metrics, a certain degree of industry consensus
helped to popularize their respective uses in practice before being absorbed in building
codes and standards. Visual comfort on the other hand has seen little success with metrics
adopted by codes and standards. Because visual comfort is highly subjective – what may
be enough daylight for one person might be completely unsatisfactory to another – it is
hard to be certain that numerical calculations will accurately predict the occupant's
response. This is unlike other metrics like energy usage, structural drift and even daylight
sufficiency, which are less subjective.

2.2 Visual Comfort
Visual comfort is a term used to describe the overarching subjective performance of
visual quality within buildings. This metric is separate from daylight sufficiency. For
example, varying occupants can report high levels of visual comfort while receiving
8

varying amounts of daylighting. Visual comfort is a biophysical metric dependent on
occupant perception and therefore encompasses a wide variety of visual and
environmental factors such as: color, brightness, contrast, direction of light source, view
size, view quality, light uniformity, and even thermal visual comfort conditions can affect
visual comfort.
vii

Currently, visual comfort data is best captured by occupant surveys, soliciting feedback
from those who actually utilize the space. Surveys are the most direct method for
acquiring visual comfort information, yet this type of data can be time-consuming to
collect, can be socially compromising to occupants, and requires that the building already
be built and occupied. In effect, surveys may be the best method for acquiring visual
comfort information in existing buildings, but for new projects, predictive models – either
physical or computer-based – to simulate actual building conditions for building design.
Knowing this, many have gone through exhaustive lengths to try to quantify the
subjective sensation of visual comfort, and of the numerous models used to simulate
visual comfort; the subject of glare has attracted by far the most attention.
viii

2.3 Illuminance vs. Luminance
It is essential to understand illuminance, luminance, and the differences between the two.
Illuminance is the amount of luminous flux per unit area; luminance is the amount of
luminous intensity per unit area. The major difference between the two is that
illuminance is the amount of light arriving at a surface while luminance is the amount of

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10

2.4 Glare Metrics
In addition to understanding the impacts and uses of daylighting from a quantitative point
of view, daylighting from a qualitative perspective (color, contrast, source direction, etc.)
plays a large role in how daylight is utilized in buildings. Glare – light sources that cause
difficulty in vision – is one phenomenon that attempts account for visual quality in
buildings, mainly by identifying conditions for visual discomfort rather than visual
comfort. Though there are currently numerous definitions and types of glare used in
building science, most if not all types of glare can be pooled into one of three prevalent
categories: absolute glare, relative glare, and reflected glare. Absolute glare is the
sensation of too much light from a single or multiple light sources such that it is visually
obstructing no matter how bright one’s background or adaptive field of vision may be; for
example, the sun on a bright day is considered an absolute glare source. relative glare is
the sensation of too much light from a single or multiple light sources in contrast to one’s
surrounding field of vision, for example when looking at a car’s headlights at night. A
viewer may barely notice the brightness of a car’s headlights during the day but as soon
as the ambient brightness decreases the viewer’s sensitivity to light increases. Reflected
glare is when a single or multiple sources of light outside one’s field of vision disrupts
vision within one’s field of vision, for example light reflected from a computer screen
that may not be harmful or painful yet disables the viewer from completing a visual task
like reading. Other known glare sub-categories include blinding glare, disability glare,
discomfort glare, imperceptible glare, intolerable glare, and perceptible glare. The many
sub-categories or measures of glare help to articulate levels of intensity and associated
11

visual effects, however discomfort glare by definition – glare that causes discomfort
without necessarily impairing the visibility of objects
xi
– identifies visual problems
(instances of visual discomfort).

2.5 Glare Definitions
Glare is the biophysical sensation of visual discomfort. In the last sixty years countless
formulae, indices and probabilities have been proposed to predict the human response of
glare, a majority which are based on the following core glare equation:
xii

ℎ

Where:
G = subjective glare
= luminance of glare source (cd/m²)
= solid angle subtended glare source (sr)
= luminance of background (cd/m²)
= line of sight position index
e,f,g,h = weighted coefficients

This equation contains four variables basic to our understanding of discomfort glare:
glare source luminance, glare source direction, background luminance, and line of sight.
Many variants of this equation exist through extended mathematics and or the inclusion
of additional variables. For example, the relatively new glare metric Daylight Glare
12

Probability (DGP) additionally considers vertical eye illuminance to account for the
amount of luminous flux arriving at the eye. DGP has shown so much promise that a
modified version of this metric called Simplified Daylight Glare Probability (DGPs)
considers only vertical eye illuminance. This view-dependent illuminance-based metric
has been shown to produce reliable results for views without direct transmission
components (like the sun) and without peak specular reflections.
xiii
Some of the other
well-known definitions of glare are listed here.
 British Glare Index (BGI)
 CIE Glare Index (CGI)
 Daylight Glare Index (DGI)
 Daylight Glare Probability (DGP)
 Predictive Glare Sensation Vote (PGSV)
 Subjective Rating (SR)
 Unified Glare Rating (UGR)
 Visual Comfort Probability (VCP)
xiv

The glare formulas listed above are view-dependent, luminance-based formulas. This
means that to calculate them a specific view, sky condition, and time must be known, for
example, on June 21 at 3:00p with overcast sky conditions and with the observer standing
at coordinates (x, y, z) and looking in the direction of coordinates (x, y, z). As indicators
of visual comfort, typically these formulas are accompanied by pre-defined scales to help
users interpret their numeric results. For example, a DGI of 18 or below is considered
13

Barely Perceptible while a DGI of 31 or more is considered Intolerable Glare. However, a
DGP below .3 is considered Barely Perceptible while a DGP of .45 or more is considered
Intolerable Glare.

2.6 Visual Comfort Simulation Processes
In addition to the many mathematical definitions of glare, many simulation-based
processes are available to assist designers with computation and the analysis of spaces
with respect to glare and visual comfort. The foundation of much of this analysis is
luminance mapping or digital imagery with luminance metadata. Luminance maps are
fields of view overlaid with physical luminance values. The view itself is either rendered
by computer simulation or produced by High Dynamic Range (HDR) imaging
techniques. These images are often represented with hemispherical field of views (180°)
or in the case of HDR photography taken with a fish eye lens, as this experience more
closely resembles a human field of view (Figure 4). The resulting luminance maps are
then analyzed by separate software for visual comfort and or various types of glare.
14

Figure 4: Luminance Maps with Perspective View vs. Fish Eye View

2.7 High Dynamic Range (HDR) Luminance Maps
When producing luminance maps with HDR imaging techniques, a digital camera is used
to capture varying exposures of a single scene; this produces consolidated images that are
physically more accurate and richer with information. Because HDR images contain a
much broader range of visual information, the images they produce can act as proxies to
an actual human view and thus can act as the basis for visual comfort analysis.
Traditional images are made from single exposures that often lose visual information in
the darkest and lightest areas of the image and are not considered reliable proxies to the
human experience. After Low Dynamic Range (LDR) or Standard Dynamic Range
(SDR) images are captured, they must be imported into HDR imaging software such as
Photosphere, Photolux, or Bracket for luminance interpretation and also calibration.
Calibration of HDR imagery is particularly important when being used for luminance
15

based analysis because though HDR cameras capture wide ranges of relative visual
information; they do not necessarily capture absolute luminance values for that wide
range of information. The resulting calibrated image is a luminance map similar to those
rendered by Radiance or other luminance map rendering programs.
xv

Figure 5: Multiple LDR Exposures Imported Into Bracket
xvi

16

Figure 6: Single HDR Image Created from Multiple LDR Images

2.8 Rendered Luminance Maps
For computer rendering methods, a majority of luminance maps are rendered with
Radiance. Radiance is a sophisticated lighting simulation software package developed by
Greg Ward and others with funding primarily from the U.S. Department of Energy and
distributed by Lawrence Berkeley National Laboratory. The software was originally
released in 1990 (v.1) for fast and accurate image rendering with UNIX computers but
has since taken on a bulk of daylight simulation processes for buildings, acting as the
backbone for numerous analytical packages such as DAYSIM, IES Radiance and
SPOT.
xvii
Radiance – along with Thea Render, 3ds Studio Max Design, and others – relies
17

highly on computer graphic algorithms known as ray tracing to render physically accurate
images from a virtual environment. In ray tracing, realistic images are created pixel by
pixel, by calculating the paths taken by rays of light within a virtual scene. The paths are
traced backwards from a specific viewpoint – through parallel processing – which acts as
a proxy to a human view.
xviii
Light intensity of each of these pixels can be computed
through ray-tracing techniques, yet often additional computational methods such as
radiosity are deployed in combination with ray tracing to produce even more physically
accurate images. Radiosity itself applies finite element analysis to compute the amount of
light energy transferred among surfaces in a virtual scene. Some simulation programs
such as Ecotect, Lightscape and AGI32 use radiosity methods to calculate luminance and
or illuminance values. However, unlike ray tracing techniques, radiosity methods are
independent of view and more importantly, do not consider specularity.
xix
So, even
though some of these programs can produce luminance maps, the images they produce
cannot be considered reliable proxies to the human view without consideration of
specularity.

2.9 Analyzing Luminance Maps
Once a luminance map is produced or acquired, visual comfort and glare analysis can be
calculated with some HDR imaging software packages, whole building analysis software
packages, stand alone software packages, or manually. The HDR imaging software
package Photolux, for example, has the capability to mathematically calculate UGR,
18

DGR, CGI and several other luminance based metrics. Varying HDR imaging software
packages have varying capabilities with respect to glare and visual comfort, some of
which don’t do any glare analysis at all. A handful of whole building simulation software
packages tout limited capabilities with glare such as Bentley Hevacomp and IES Virtual
Environment that calculates CGI and UGI. Another C++ based glare analysis program
called GlareIndices imports luminance maps (HDR images) to create luminance
histograms; these in turn are used to calculate ratios between the histogram bell region
and histogram spikes (called the Schiler Index).
xx
Yet, of all the available options for
calculating glare metrics, the relatively new program Evalglare seems to draw the most
attention from visual comfort enthusiasts.

2.10 Evalglare
Evalglare was developed by Fraunhofer ISE and is a free stand-alone program with
robust capabilities, allowing users to analyze an existing HDRI or .pic (Radiance image
format) for DGP, DGI, UGR, VCP and CGI.
xxi
Evalglare – which is a command line
based glare calculator – allows users to visualize glare sources directly on luminance
maps called check files (Figure 7), summoning detailed information about each
calculated glare and accepting custom commands for time saving processes such as
writing results to excel and batching. Other daylight simulation programs such as DIVA-
for-Rhino and Daysim use Evalglare for glare calculations but with limited functionality.
19

Figure 7: Evalglare Check File Highlighting Potential Glare

2.11 Annual Simulation Processes
New annual daylight simulation software offers some advances over instantaneous visual
comfort analysis. Multiple daylighting tools have already started to incorporate annual
glare functionality into their workflows; currently, this analysis is nascent and very time-
consuming. Yet, much like hourly whole building energy analysis, it is assumed that
these time-consuming processes will become more practical as computational power
matures. Whole building energy analysis software has become very popular in recent
times with the advent of quick annual capabilities. Many calculation engines such as
DOE2, EnergyPlus, ApacheSim, and many others, can calculate a whole year’s worth of
20

analysis in a matter of minutes (depending on model complexity of course), where fifteen
years ago this task would have taken in the order days to complete. These thermal
modeling techniques can vary with robustness and granularity, allowing users to choose
their level of analytical resolution. Thermal modeling techniques can range from single
analysis nodes per thermal zone (weighted coefficient engines like DOE2) to thousands
of analysis nodes per zone (thermal network engines like Energy-10). The same level of
analytical freedom is believed to develop with annual glare analysis. For whole building
daylight simulation, quick annualized capabilities arrived only recently. In 2003,
Harvard’s Graduate School of Design released an elaborated version of Radiance called
Daysim.
xxii
This free Java-based program calculates illuminance levels over a specified
grid for an entire year using coefficients to accelerate calculation speeds.

Daysim automatically bins illuminance values and reports back various annual
illuminance-based metrics. These metrics are Daylight Autonomy, Daylight Autonomy
Max, Continuous Daylight Autonomy, Useful Daylight Illuminance, and Daylight
Saturation Percentage.
xxiii

 Daylight Autonomy (DA): percentage of annual hours that a given point in space
is above a specified minimum illumination level. It was originally proposed by
the Association Suisse des Electriciens in 1989 and was improved by Christoph
Reinhart from 2001 to 2004.

21

 Daylight Autonomy Max (DAmax): percentage of annual hours that a given
point in space is ten times above a specified minimum illumination level. This
metric is meant to indicate areas of potential over-illumination.

 Continuous Daylight Autonomy (DAcon): in contrast to conventional Daylight
Autonomy, attributes partial credit to time steps when the calculated illuminance
lies below the specified minimum illuminance level. For example, in the case
where 500 lux are required and 400 lux are provided by daylight at a given time
step, a partial credit of 400lux/500lux=0.8 is given for that time step. The result is
that instead of a hard threshold the transition between compliance and non-
compliance becomes softened. DAcon was proposed by Z. Rogers in 2006.

 Useful Daylight Illuminance (UDI): percentage of annual hours that a given
point in space falls between 100 and 2000 lux. It was conceived by architectural
researcher John Mardaljevic in 2005.

 Daylight Saturation Percentage (DSP): modification of Useful Daylight
Illuminance that modifies the lower limit to 431 lux (40 foot-candles) and
increases the upper limit to 4306 lux (400 foot-candles). DSP goes further by
subtracting annual hour values above 400 foot-candles to account for areas of
over-illumination. The Lighting and Daylighting Committee for the Collaborative
for High Performance Schools program (CHPS) developed this in 2006.
22

The Daysim simulation process coupled with re-imagined daylight sufficiency metrics
(not all of which are described here) have helped to reshape modern daylight simulation
practices for designers and the building industry. With such advancements in daylight
sufficiency, and as annualized simulation practices becoming more popular and used for
building analysis, there exists an even stronger need, and a clearer path for daylight
simulation programs to quickly calculate annual visual comfort metrics (daylight quality)
for whole buildings. In fact, Daysim v.3 just recently incorporated glare functionality into
its program, allowing users to input DGP View Files for simultaneous annual daylight
analysis and annual daylight glare probability.
xxiv
As the demand for annual glare profiles
increases and as simulation time decreases, it is projected that these workflows will
become more practical and more prominent within the building design industry.

2.12 The Visual Comfort Conundrum
With respect to luminance-based visual comfort and glare processes, great strides have
been made and continue to be made within the subject of Building Science. One of the
many excellent applications of luminance-based analysis was done on the Walt Disney
Concert Hall by the University of Southern California (mentioned in Chapter 1). In Post
Treatment Analysis of the Glare Remediation of the Walt Disney Concert Hall,
xxv
the
iconic and world famous design by Frank Gehry is analyzed and mended for thermal and
visual glare. Commissioned by the County of Los Angeles, the team at USC used
23

conventional automatic digital photography to produce luminance histograms (graphical
plots showing pixel luminance versus frequency) which were then evaluated for visual
glare characteristic. This analysis was accompanied by ground and mid-air temperatures
taken by dataloggers in strategic locations around the building. As a result of this
analysis, select areas the building’s façade (4,000 square feet of the 200,000 square feet
of cladding) were sanded down, so as to reduce the material’s specularity. The
remediation techniques used in this work successfully relieved concerns for both
neighbors and the County of Los Angeles while maintaining the aesthetic value for the
Concert Hall. Another excellent application of luminance-based analysis – and an
exception to the trend of doing so for remediation purposes – is the New York Times
building, which used HDR imaging techniques to carefully calibrate the building’s
automated shading system based on average window luminance.
xxvi

Though there have been successes with luminance-based metrics, there are currently
several industry adoption barriers that make these methods unattractive to those who
influence building design. Existing luminance-based success stories typically come from
built applications, conceding visual comfort analysis to afterthought problem fixes (like
the Disney Concert Hall example) rather than pre-construction design success. This is
due to two primary reasons. First, current visual comfort analysis with luminance-based
methods can be quite time and resource intensive with comparatively little perceived
benefit. Most buildings aren’t fully clad with super specular materials like the Disney
Concert Hall, nor do building designers usually make visual comfort a top design
priority. For example, suppose a building designer wants to perform luminance mapping
24

techniques for his or her building. Initially, the designer would have to accurately model
a space with geometry, materiality, furniture, equipment, etc. Then various glare metrics
could be produced for a specific field of view for a specific time of the year. This field of
view may be only one of thousands representative of their building, while the selected
time of year may be only one of thousands represented in their building throughout the
year. The multiplicity of simulation parameters associated with simulating glare metrics
for an entire building could appear exhaustive for building designers. Given the fast-
evolving nature of computation, this barrier is less of a concern. Second, with regards to
visual comfort metrics, little consensus on the subject has been established by the
building industry. This means that despite a long history of clever efforts to concoct
mathematical descriptions of discomfort glare, the building industry is still without an
undisputed method for doing so. On some of the difficulties associated with discomfort
glare, the IES Lighting Handbook states:
Some relationships established from experimental data can be weak or of very
limited utility because of the nature of the experiments that produced the data. In
some cases the variables used in the experiment are vague and difficult to
measure. Examples are discomfort glare and mood. Assessing these as dependent
variables often involves questionnaires, bur these have proven to be difficult to
design and use in ways that yield reliable and statistically defensible data.
xxvii

This is not to say that the glare models examined in this study have not been used
successfully for specific applications, it is merely alluding to the inconsistency of these
25

models when applied to generalized applications. This uncertainty associated with
selecting the “best” visual comfort metrics for the “right” visual scenarios leaves
designers with little certainty about making design decisions, commonly resulting in
afterthought problem fixes or no visual comfort analysis at all.

26

CHAPTER 3: RESEARCH METHOD
3.1 Research Method Overview
This thesis work uses an existing daylight datasets to investigate fourteen daylit spaces
under a variety of luminance-based conditions with five visual comfort metrics. A visual
comfort design process is constructed and described to further examine the obstacles
associated with creating annual glare profiles and to extrapolate trends from the resultant
datasets.

3.2 Daylight Metrics Project
Select project data from the Daylight Metrics Project (DMP)
xxviii
is on loan for this thesis
work courtesy of Heschong Mahone Group. The Daylight Metrics Project data was
collected on behalf of the Daylighting Plus program for the Public Interest Energy
Research of the California Energy Commission. The Daylight Metrics Project studied 61
spaces in six different climate zones for daylighting characteristics. The main goal of the
DMP was to develop a set of metrics that could be used to usefully describe a “well daylit
space”. These metrics were focused first on human visual comfort and not on energy
performance, much like minimum ventilation requirements. Three space types were
studied (classrooms, open office spaces and library/lobby spaces) in six urban areas from
three states: California, Washington, and New York (San Francisco/Oakland,
Sacramento, Truckee, Seattle/Tacoma, Albany, and New York City). The 61 spaces were
selected to represent a wide-variety of daylighting strategies including top lighting, side
27

lighting, clerestories, skylights, light shelves; automatic blinds that respond to exterior
lighting conditions, and translucent glazing. These spaces were documented carefully to a
level consistent with model calibration procedures including detailed geometric space
descriptions, space adjacencies (including trees and neighboring buildings), furniture
descriptions for objects larger than 3’ (e.g. tables but not chairs), operating schedules,
measured surface reflectance, and glazing visual light transmission. Detailed 3dmodels of
the 61 spaces were then created and used to simulate annual daylighting conditions for
the entire year with Typical Meteorological Year (TMY) weather data. For each space,
three conditions were simulated to simulate the full range of daylighting value within the
space: blinds open, blinds closed, and blinds operated. To simulate the blinds operated
condition, it was assumed that occupants would close blinds for a window group when
direct sun entered the space (defined as 1000 lux).
To complement this set of data, an average of 5.2 expert surveys and an average 9.5
occupant surveys were administered for each of the 61 spaces. Selected lighting experts
were asked to answer 49 questions about a given space for a single time. Occupants were
asked to answer 15 questions about their experience over time in a given space. The
Likert scale (9-point) surveys taken by both experts and occupants were about the space
as a whole and not about individual locations within the space. It was assumed that
experts would provide an in-depth understanding of spaces and continuity across multiple
spaces, while occupant assessments provided a more experiential understanding of the
space over time.
28

The Daylight Metrics Project was sponsored by the California Energy Commission and is
part of a larger ongoing project referred to as the Daylighting Plus Program. The project
itself was primarily funded by the Public Interest Energy Research (PIER) program that
provides energy-efficiency research, development, and demonstration for the state of
California. The project was managed by the Heschong Mahone Group (HMG) and
included a wide variety of subcontractors including Greg Ward of Anyhere Software,
Christoph Reinhart of Harvard University, Marilyne Andersen at EPFL, Joel Loveland of
the IDL, and many others. Additional direction and review was provided by many
members of the IES Daylighting Metrics Committee (DMC).

3.3 Simulation Modeling Host
Autodesk Ecotect was chosen as the visual interface and general modeling repository for
this process for a number of reasons focusing on the nature of data exchange and types of
visualizations possible. The existing datasets were Radiance geometry files (.rad). These
are not inherently visualized in Radiance or any of the Radiance variations (Radiance
Control Panel, Desktop Radiance). Ecotect has the ability to import Radiance geometry
files (.rad) and visualize them in a number of ways. Ecotect is a visually compelling tool
and liked by many because of its broad range of visualization options. Ecotect exports to
Radiance Control Panel which allows users to import custom radiance material
definitions for translucent materials: a necessity for this research. Radiance Control Panel
also allows for batch processing; in some cases this can save days of simulation time.
29

3.4 Simulation Overview
The simulation processes used to create the dataset for this research is outlined here. The
methodology was as follows: define Ecotect material library, import Ecotect material
library, import building geometry and weather files, setup camera views, export Ecotect
definitions to Radiance, create luminance maps with Radiance, evaluate luminance maps
in Evalglare by batch processing, import glare numeric results into Excel, and compare
the results using statistical methods.

3.5 Material Definitions
The first step of the simulation process was to create a luminance map with Ecotect and
Radiance. To create luminance maps, Radiance material definitions (library) had to be
checked to ensure correct translation when imported into Autodesk Ecotect. Standard
materials imported correctly, custom materials (translucent materials) did not. These had
to be recreated one by one in Ecotect adding custom radiance definitions to the advanced
Radiance Export tab. Once these materials were fixed and all the materials were named
exactly as they were in the Radiance material definitions file, a master Ecotect library
(DMP.lib) could be saved.
30

Figure 8: Advanced Export to Radiance Using Ecotect

3.6 Import Master Ecotect Material Library
The adjusted master Ecotect material library (shown in Figure 9) was loaded into the
Element Library. Note that it is very important to load the material library (DMP.lib) into
Ecotect before importing Radiance geometry. If these two steps are switched in order,
materials will not be automatically assigned; material assignments will have to be done
manually, which can be very tedious.

31

Figure 9: Custom Material Library Import in Ecotect

3.7 Import Radiance Geometry File
Once the master material library (DMP.lib) was loaded in Ecotect, Radiance geometry
was imported; this geometry was scaled to inches. Geometry was automatically assigned
materials based on existing Radiance definitions. Like the Radiance material definitions,
the Radiance geometry files did not import perfectly. Each geometry files required at
least some cleaning and patching in Ecotect; only one model imported simulation-ready.
The reason for geometry misinterpretation in Ecotect is the programs sensitivity to non-
planar elements. Polygons imported into Ecotect that are not mathematically planar (two-
dimensional) are not filled with a surface, only outlined. Omitted surfaces were redrawn
in the fourteen models.
32

Figure 10: Radiance Geometry Import Dialogue in Ecotect

Figure 11: Radiance Geometry Imported, Materials Assigned in Ecotect
33

3.8 Import Weather File
Ecotect weather files were then imported in the form of .wea files to ensure that the
daylight analysis was based on local meteorological weather data.

3.9 Setup Camera Views
Because the five visual comfort metrics are all luminance-based, specific views were
setup in Ecotect in order to create luminance maps with Radiance. These cameras were
selected to be angular in lens type with 180 degree horizontal and vertical view angles.

Figure 12: View Cameras Created in Ecotect

34

Figure 13: View Cameras Shown in Plan in Ecotect

3.10 Radiance Export
Once materials, geometry, a weather file, and a view camera were defined, the entire
scene was exported to Radiance Control Panel for creation of a luminance map. Once
rendered, the image was launched in Radiance Image Viewer.

35

Figure 14: Ecotect Export to Radiance Control Panel

Figure 15: Ecotect Camera Simulated in Radiance
36

3.11 Evalglare
The resultant view (.pic file from Radiance) was then analyzed in Evalglare using the
following command lines. A check file was then launched highlighting areas of potential
glare.

Figure 16: Window Command Processor Showing Evalglare

37

Figure 17: Evalglare Check File Highlighting Glare Locations

3.12 Batch Processing and Consolidating Results
In addition to creating visual luminance check files, numeric results were written to text
files using custom commands in Evalglare. Batch processing (executing a series of
jobs/renderings with a single action) was deployed in both the Radiance Control Panel
and in Evalglare. This was necessary to create the large number of views and check files
in a reasonable time, otherwise creating this number of views would have taken at least
twice as long. The Radiance Control Panel has a built in batch processor, which allowed
64 views to be rendered from a single command (this does not reduce simulation time,
38

only simulation setup time). Because Evalglare is a command line based program, a
custom script could be created to deploy batch analysis. The following image shows the
default program command for analyzing a single image with Evalglare followed by the
newly created command for analyzing many images (in this case three images). Not only
does this newly created command analyze large numbers of images for a single
command, it also creates check files (luminance maps identifying glare) for each of these
views, and records the numeric results into a consolidated text file (glare.txt).

Figure 18: Example Batch Execution Using Evalglare

Evalglare batch command:
for %a in (*.pic) do (evalglare -c %a "%a") >>glare.txt
39

Finally, all the text files (glare.txt) like the one shown in Figure 19 were consolidated into
a master Excel spreadsheet containing all of the numeric glare results; this spreadsheet
was used extensively for analysis.

Figure 19: Batch Results Automatically Written to Text File

Figure 20: Batch Glare Results Imported Into Excel
40

3.13 Statistical Methods
The datasets, consisting of 5040 numeric glare indices, were analyzed using statistical
methods, primarily:
 Coefficient of correlation (R): The non-cause and effect relationship between
two variables, where 1 indicates a perfectly positive relationship and -1 indicates
a perfectly negative relationship.
 Coefficient of determination (R²): The proportion of variability in a datasets. R²
is an indicator of how well future outcomes are likely to be predicted.

41

CHAPTER 4: RESULTS
4.1 Results Overview
The process outlined in Chapter 3 yielded the following:
 Analysis for 14 spaces – including classrooms, offices, and libraries/lobbies
 72 views (luminance maps) for each of the 14 spaces (1008 total)
 Views with both clear sky and overcast sky conditions
 Views for 3 dates – June 21, September 21, December 21
 Views for 3 times – 9:00AM, 1:00PM, 5:00PM (daylight savings)
 View for 4 orientations – standing eye level in four orthogonal directions
 Evalglare check files for every view highlight locations of glare
 DGP, DGI, UGR, VCP, CGI numeric results for each view

4.2 Ecotect Models
The Ecotect models generated through these processes provided invaluable feedback.
When any of the results seemed questionable, the visual representations of these spaces
were used to re-evaluate the information. In particular, when it came to material
assignments and shading devices, the three-dimensional models really helped to ensure
that these features were simulated appropriately. The Ecotect model offered another level
of analytical reassurance where if one were to use Radiance by itself, no 3D visualization
would accompany the scene description.
42

4.3 Luminance Maps
Luminance maps for each of the 1008 views were created, at times generating wonderful
visuals of detailed spaces. Four examples are displayed below.

Figure 21: Four Sample Luminance Maps Simulated with Radiance
43

4.4 Sky Conditions
Two sky conditions were simulated for each of the 14 spaces: thirty-six clear sky
conditions, thirty-six overcast sky conditions (72 total views for each space). The CIE
overcast sky model was used to simulate overcast sky conditions, this sky model is
uniform in luminous distribution and rotationally invariant (Figure 22, right).

Figure 22: CIE Clear Sky Model vs.CIE Overcast Sky Model
xxix

The same view is shown here under clear sky and overcast conditions. Date, time of day,
and exposure are kept constant.
44

Figure 23: Luminance Maps Showing Sky Variation

4.5 Days of the Year
Three days of the year were simulated for each of the 14 spaces: twenty-four on June 21,
twenty-four on September 21, and twenty-four on December 21 (72 total views for each
space). The same view is shown here in June and December. Time of day, sky condition,
and exposure are kept constant.
45

Figure 24: Luminance Maps Showing Seasonal Variation

4.6 Times of Day
Three times of the day were simulated for each of the 14 spaces: twenty-four at 9:00AM,
twenty-four at 1:00PM, and twenty-four at 5:00PM daylight savings time (72 total views
for each space). The same view is shown at 9:00AM and at 5:00PM. Date, sky condition,
and exposure are kept constant.
46

Figure 25: Luminance Maps Showing Day Variation

4.7 View Orientations
Four view orientations were simulated for each of the 14 spaces: eighteen at 0 degrees
from North, eighteen at 90 degrees from North, eighteen at 180 degrees from North, and
eighteen at 270 degrees from North (72 total views for each space). Four different view
orientations of the same space are shown with constant time and sky conditions.
47

Figure 26: Luminance Maps Showing View Orientation Variation

48

4.8 Evalglare Check Files
Evalglare check files were created for each of the 1008 views. A single view (luminance
map) is shown with its partner check file generated from Evalglare. Notice on the check
file (right) the corners being blocked out in black and omitted from analysis. In attempt to
emulate the human field of view, luminance maps created for this study were created
with a 180°angular lens (also a necessity for using Evalglare). Because the resultant
image is a parallel projection of a hemisphere onto a circle (also known as fisheye
images), the areas in black would be beyond a 180° field of view. The neon spots
highlight areas of potential glare. Also notice that the rendered view (left) has a brownish
colored tint because of the material finishes in the scene where the check file (right) is
converted to grayscale. This is because Evalglare calculates visual comfort metrics from
luminous intensities derived by pixel value and not by pixel hue.

Figure 27: Luminance Map Before and After Evalglare
49

4.9 Evalglare Numeric Results
In addition to the check files just described, each Evalglare simulation calculates numeric
results for five visual comfort metrics: DGP, DGI, UGR, VCP and CGI. Through batch
processing, each of these values (1008 views x 5 metrics = 5040 glare results) were
written to text files and ultimately consolidated into a single master results spreadsheet in
Excel for analysis.

Figure 28: Partial View of Master Spreadsheet for Numeric Glare Results

50

CHAPTER 5: ANALYSIS
5.1 Indices Normalization
With the results produces, the next step was to determine if five metrics agreed with each
other. To visually compare (not statistically compare) the results of five metrics against
each other, the numeric values were scaled (multiplied by coefficients) to the same
numeric scale, in this case from 0 to 1. This step was done primarily for visualizing
results onto a common graphic scale. The following tables were taken primarily from the
DIVA-for-Rhino
xxx
workflow and show both the inherent evaluation ranges for the
Evalglare glare indices (Table 2) and the scaled evaluation ranges after being multiplied
by the listed coefficients (Table 3). It is crucial to mention that the five glare metrics
analyzed in this study have four different non-linear evaluation ranges, thus they cannot
be directly compared against each other! For example a scaled DGP value of .3 indicates
Imperceptible Glare, while a scaled UGR value of .3 indicates Perceptible Glare; two
different predictions for the same scaled value.

51

Table 2: Glare Indices Evaluation Ranges

Imperceptible Perceptible Disturbing Intolerable Scaling Factor
DGP <.35 .35-.40 .40-.45 >.45 None
DGI <18 18-24 24-31 >31 DGI x 0.01452
UGR <13 13-22 22-28 >28 UGR x 0.01607
VCP >80 60-80 40-60 <40 (1-VCP) x .01
CGI

<13

13-22

22-28

>28

CGI x 0.01607

Table 3: Scaled Glare Indices Evaluation Ranges

Imperceptible Perceptible Disturbing Intolerable
DGP <.35 .35-.40 .40-.45 >.45
DGI <.26 .26-.35 .35-.45 >.45
UGR <.21 .21-.35 .35-.45 >.45
VCP <.20 .20-.40 .40-.60 >.60
CGI

<.21

.21-.35

.35-.45

>.45

52

To statistically compare the results it was imperative to translate the numeric results into
simple subjective categories, where: 1=Imperceptible, 2=Perceptible, 3=Disturbing and
4=Intolerable Glare. By doing this, the resultant glare predictions can be statistically
analyzed, which could not be done with the non-linear numeric results originally
obtained. Figure 29 shows the aggregated results for one of the fourteen spaces, in this
case NYC01.SP1. The first column on the left lists the view number (72 total views per
space) while the five adjacent columns with the orange headings list the parameters
which make that view unique: Sky Condition, Date and Time, View. The next columns
with the blue headings list the numeric glare results generated by Evalglare (DGP, DGI,
UGR, VCP and CGI) for that particular view. Lastly the columns with the green headings
show the same glare results scaled from 0 to 1 for use in visualizing the analysis. A color
legend corresponding to glare type is included at the top of the spreadsheet where green
is Imperceptible Glare, yellow is Perceptible Glare, orange is Disturbing Glare, and red is
Intolerable Glare. This is very important because again, it is the colors (glare predictions)
that are being compared for statistical analysis and not the non-linear numeric values.
Notice the similarity to the sample results taken from the DIVA-for-Rhino workflow
shown in Figure 30. As an example, view #1 in this spreadsheet was simulated with a
clear sky condition, on June 21
st
at 9:00AM, and looking east from the center of the
space. The corresponding results for this view indicate DGP and DGI do not predict glare
(Imperceptible), UGR and CGI predict perceptible glare, while VCP predicts disturbing
glare. Notice that the scaled results under the blue headings in Table 4 show different
numeric values from the results under the green headings, yet the colors are exactly the
53

same. Using conditional formatting in Excel, the glare evaluation ranges from Tables 2
and 2 could be input manually to infer numeric results with a color scale to help excavate
relationships quicker and more effectively. By looking at this spreadsheet and the color
variety across individual rows, almost instantly one can see that the five different glare
metrics give very different results for the same space.
54

Figure 29: Glare Dataset for a Single Space
55

Figure 30: Annual Glare Map from Diva-for-Rhino
xxxi

The white cells in Figure 29 (labeled as "No Data" in the color legend) are blank because
Evalglare cannot calculate indices under very low scene brightness ( (Figure 31).
Notice that the rows with "No Data" values are all in views looking south. In this
particular space there are only windows and view apertures on the north end of the space,
making south-facing views low in ambient brightness. These cells are left blank and not
as a zero so as not to influence statistical analysis.

Figure 31: Evalglare Results for Low Brightness Scene
56

5.2 Glare Indices Agreement
The datasets for all 1008 views were compared against each other to produce coefficients
of correlation and coefficients of determination (R and R² described in Chapter 3).

Table 4: Glare Indices Agreement

R R²
DGP-DGI 0.645 0.416
DGP-UGR 0.646 0.418
DGP-VCP -0.868 0.753
DGP-CGI 0.677 0.458
DGI-UGR 0.983 0.966
DGI-VCP -0.715 0.511
DGI-CGI 0.977 0.954
UGR-VCP -0.707 0.499
UGR-CGI 0.992 0.984
VCP-CGI

-0.707

0.500

57

The first row of Table 5 shows a DGP-DGI coefficient of correlation (R) of 0.645; this
single value is the calculated result of comparing 1008 DGP values with 1008 DGI values
for correlation; the same can be said for the R² value of 0.416. Interestingly enough, the
two metrics DGP and DGI – the only two of the five metrics that were constructed
specifically to analyze daylit conditions – have the lowest correlation with each other.
The other three metrics were created for electric lighting applications. On the other hand,
Table 5 shows very starkly that DGI, UGR and CGI agree very highly with each other,
showing coefficients of determination (R²'s) of 0.968 on average between the three of
them. This finding is in alignment with previous research findings and is not very
surprising given the mathematical similarity between these three indices.
DGP and VCP have the lowest R and R² values, meaning that they relate to the other
metrics the least. This does not mean that these two metrics are worse at predicting glare
than the other three; this only means that their results are quite different from the other
metrics. In fact, DGP’s novel approach – introducing vertical eye illuminance – can be
quite accurate for many conditions. So DGP may be different from the other metrics in a
good way. As far as VCP’s low relation to the other metrics, this research suggests that it
is likely different in a bad way: consistently overestimating glare when luminance
conditions are low, sometimes very low. An example luminance map is shown in Figure
32 highlighting VCP in green; the highlighted region in green is also the overcast sky
seen from inside of the space. The maximum luminance in this view is 3733 cd/m²; VCP
predicts intolerable glare (12% Visual Comfort Probability).
58

An alternative explanation is that DGP is more sensitive to absolute luminance levels
(and the resultant illuminance) and VCP is more sensitive to relatives glare levels, still
showing glare at much lower absolute levels.

Figure 32: Luminance Map Highlighting VCP with Overcast Sky

Though we can never be one hundred percent certain that there would be no glare in this
scene (as glare is a subjective sensation), judgment tells us that 88% of people would not
experience intolerable glare under this overcast sky condition and that VCP is highly
underestimating visual comfort.

F
an
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esults for 10
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or these thre
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59
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ation.
r, this
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60

large sample size that DGI, UGR, and CGI are all very similar to each other in behavior
and scale. We also see that the darker blue (DGP) dataset follows a very similar trend to
the three metrics just mentioned. However similar to these three metrics, DGP differs
from DGI, UGR, and CGI in two major ways: DGP has a lower limit seen in Figure 33 at
about 0.18 on the y-axis, and DGP is meant to respond to daylight conditions more
accurately because it takes into account vertical illuminance. The latter of the two DGP
differences does not seem to be apparent in Figure 33. This will be discussed in further
detail in Chapter 5. Another observation that can be supported by Figure 33 is that VCP
values are wildly different than the rest of the metrics: indicating Disturbing or
Intolerable Glare in over half of the simulated views. This strong evidence plainly
suggests that VCP should not be used for analyzing visual comfort in direct daylit
conditions. Figure 34 displays results for a single space instead all fourteen, more clearly
articulating the same deductions.
61

Figure 34: 5 Scaled Glare Indices for a Single Space

The comparisons of the five metrics show the following:
 Normalization factors– used to force different glare indices to the same numeric
scale – should not be used to statistically compare metrics with non-linear
evaluation ranges. For this study, subjective glare categories (Imperceptible,
Perceptible, Disturbing and Intolerable) were used to statistically analyze across
varying metric ranges.
 DGP and DGI show the weakest correlation with each other even though they
were both conceived to account for daylight conditions.
 DGI, UGR, and CGI correlate very strongly with each other.
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1 6 11 16 21 26 31 36 41 46 51 56 61 66 71
VCP
CGI
UGR
DGI
DGP
62

 Though similar to DGI, UGR, and CGI, DGP had the least dramatic behavior of
the five metrics, predicting glare the fewest amount of times.
 VCP predicted glare the most and highly over-estimated glare in daylight
conditions. VCP should not be considered a good indicator of visual comfort in
daylit conditions.

5.3 Effects of Conditions on Agreement
In addition to comparing the five metrics against each other for non-causal relationships,
the data produced was also mined for trends under specific conditions. Unfortunately,
because the data was produced by "unproven metrics," our statistical analysis cannot be
used to deduce that one metric performs better or worse under certain conditions. The
following sets of analysis are used to infer deductions amongst the five metrics, for
example one metric becomes less like another metric under specific conditions. For this
reason the tables presented in the following sections list R values and deltas. The delta
values ( Δ%) listed in these tables are used as indicators of change in relationship, and
again, not as percentages of change with accuracy of predicting glare.

5.4 Time of Year
When looking at the results separated by time of year (June, September and December),
some interesting trends immerge. The following tables list R value relationships for three
view groups as well as the percentage of difference when compared to looking at all
63

views. For example, Table 6 lists the R values for all inter glare relationships as well as
deltas ( Δ%) to show if these relationships improves or worsens under specific conditions.
In this particular case, the metrics generally agree better for views in September and
agree less strongly for views in December. Since typically building interiors have more
direct sun penetration in the low sun angle months (like December), this could reveal that
Visual Comfort Probability (VCP) and Daylight Glare Probability (DGP) react stronger
(negatively or positively) to extreme luminosities.

Table 5: September Views Agreement

R² Δ%
DGP-DGI 0.581 40%
DGP-UGR 0.612 46%
DGP-VCP 0.767 2%
DGP-CGI 0.685 49%
DGI-UGR 0.950 -2%
DGI-VCP 0.706 38%
DGI-CGI 0.932 -2%
UGR-VCP 0.729 46%
UGR-CGI 0.972 -1%
VCP-CGI 0.745 49%
64

Table 6: December Views Agreement

R² Δ%
DGP-DGI 0.356 -15%
DGP-UGR 0.344 -18%
DGP-VCP 0.828 10%
DGP-CGI 0.357 -22%
DGI-UGR 0.980 1%
DGI-VCP 0.381 -25%
DGI-CGI 0.974 2%
UGR-VCP 0.366 -27%
UGR-CGI 0.991 1%
VCP-CGI 0.360 -28%

5.5 Sky Conditions
Two sky conditions that were simulated were clear sky (with direct and diffuse
components) and uniform overcast sky. Tables 8 and 9 show VCP disagreeing with the
other metrics more dramatically under overcast sky conditions.
65

Table 7: Clear Sky Views Agreement

R R² Δ%
DGP-DGI 0.693 0.480 15%
DGP-UGR 0.720 0.518 24%
DGP-VCP 0.845 0.715 -5%
DGP-CGI 0.771 0.595 30%
DGI-UGR 0.979 0.959 -1%
DGI-VCP 0.820 0.672 31%
DGI-CGI 0.969 0.938 -2%
UGR-VCP 0.832 0.693 39%
UGR-CGI 0.987 0.974 -1%
VCP-CGI

0.842

0.709

42%

66

Table 8: Overcast Sky Views Agreement

R R² Δ%
DGP-DGI 0.645 0.416 0%
DGP-UGR 0.631 0.398 -5%
DGP-VCP 0.934 0.873 16%
DGP-CGI 0.619 0.383 -17%
DGI-UGR 0.985 0.971 0%
DGI-VCP 0.613 0.376 -26%
DGI-CGI 0.981 0.963 1%
UGR-VCP 0.601 0.361 -28%
UGR-CGI 0.995 0.989 1%
VCP-CGI

0.578

0.334

-33%

Under further investigation, some peculiar results were found with regards to overcast
sky conditions. Because overcast sky models assume uniform luminous distribution from
the outside sky component, time of year and even time of day have little or no influence
on glare predictions! Below are two graphs (Figures 35 and 36), the first graph shows
glare results for all clear sky conditions in a single space, the second shows glare results
for all overcast sky conditions in the same space. The first graph (Figure 35) shows
67

slaloming results indicating an analytical reaction to time of year and time of day. The
orange arrow on the first graph points to a clear sky view at 1:00PM in June while the red
arrow points to the same clear sky view at 1:00PM but in December, illustrating a clear
reaction to time of year.

Figure 35: Clear Sky Views for a Single Space

On the second graph however (Figure 36), with only overcast sky conditions, the same
two views have the same glare prediction results for June and December. Though
overcast sky models are expected to distribute light evenly, they are not expected to
maintain constant luminous magnitudes throughout the duration of the year. These results
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1 6 11 16 21 26 31
DGP
DGI
UGR
VCP
CGI
68

insinuate that glare indices under overcast sky conditions are insensitive to luminous sky
intensity or are responding to the even sky distribution, in contrast to the variation
evident in a clear sky distribution. It may also be that there is less variation between
outside luminance and inside luminance and among interior surface values within the
field of view.

Figure 36: Overcast Sky Views for a Single Space

5.6 Daylight Glare Probability
As mentioned earlier, DGP differs from the other metrics in that it has a lower limit,
similar to VCP but not DGI, UGR or CGI and that is considers vertical eye illuminance.
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1 6 11 16
DGP
DGI
UGR
VCP
CGI
69

None of the other glare metrics take illuminance into consideration. Figure 37 shows
DGP values for all 1008 views, for all fourteen spaces. None of the DGP values go below
0.18; this is the lower limit described earlier. The yellow line on this graph indicates
Perceptible Glare, the orange line indicates Disturbing Glare, and the red line indicates
Intolerable Glare. What is surprising is that none of the recorded DGP values predicted
glare! That means that for 1008 views, representing fourteen spaces, with varying
simulation times, orientations and sky conditions, DGP predicted no glare! To better
understand these alarming results, the datasets used for this research must be revisited.

Figure 37: DGP Results for 1008 Views

0.150
0.200
0.250
0.300
0.350
0.400
0.450
1 101 201 301 401 501 601 701 801 901 1001
DGP
Disturbing Glare
Intolerable Glare
Perceptible Glare
70

5.7 Daylight Metrics Project
(Also discussed in Chapter 3)
To produce the luminance-based glare results for this research an existing dataset was
utilized. The Daylight Metrics Project (DMP) – perhaps one of the richest daylighting
datasets currently available – comprehensively examined 61 well-daylit spaces. This
work initiated a massive undertaking:
“…the DMC envisions a suite of daylight performance metrics, that taken
together, can better predict occupant comfort in daylit spaces, and thus be used to
set minimum standards for daylighting in buildings.”
xxxii

Though the DMP could not fully summit the extensive effort of laying out inconclusive
minimum standards for daylighting, the Project did successfully initiate procedures for
doing so. Understanding the complexities of such an undertaking, the DMP extensively
documented their efforts, and remarkably, encourage future development of this work:
“The research reported herein is only just the beginning. The findings on the
three space types should be validated by others, and extended to other space types
and climate locations. Our understanding of visual comfort under daylight
conditions is very limited, and needs more comprehensive study…”
This statement, along with HMG’s enthusiasm for cooperative research inspired the use
of this dataset for visual comfort research. It is worth stating, yet again, that the DMP
analyzed “well-daylit spaces”. This is completely understandable given the primary focus
71

of the project in describing a “well-daylit space”. However, this objective poses some
inherent conflict with visual comfort research as most methods of visual comfort analysis
concentrate on instances of visual discomfort (glare). Because the DMP spaces were
considered “well daylit” spaces, instances of “bad daylighting” were more difficult to
identify. Of the spaces analyzed, only 15% of all occupied hours experienced direct
daylight penetration (only four of the fourteen spaces analyzed have unprotected glazing
on the south, east or west). In general, the spaces analyzed were well thought-out in
daylight design, which may partially explain why no DGP glare instances were
forecasted. This is one of two postulated reasons for the lack of DGP predicted glare in
Figure 37.
The second postulate for lack of DGP predicted glare has to do with location of the
views. Four cameras were placed orthogonally near the center of each analyzed space
looking north, east, south and west. Initially, when developing procedures for analyzing
an entire space for visual comfort, views near the periphery (near sidelighting) and views
near the core (away from sidelighting) were accounted for. This schematic procedure
proved to be unrealistic with the DMP spaces. Again, the location of the views within
these spaces was partially driven by the fact that the DMP spaces are well-daylit. Many
of the spaces include top lighting, translucent glazing, some have no sidelighting at-all,
and some are atriums, making it very difficult to distinguish between a core and a
perimeter. Of the fourteen spaces analyzed, only five had clearly identified perimeters.
This hindrance along with the nature of the DMP project of studying well-daylit
buildings made understanding bad daylighting a bit of a challenge.
72

One of the objectives of creating so many views was to try to outline a procedure for
wholly analyzing a space for visual comfort. This consideration meant that the author had
to follow the same guidelines indiscriminately for all the spaces. In the end, it was
decided to simulate all views from the center of the zone looking in four orthogonal
directions. This time-intensive process generated a large number of views and glare
results. Yet, based on the results – in particular the DGP results – it is now recommended
that future research consider a workflow that incorporates multiple view locations within
the analyzed space, effectively increasing analytical resolution of the space to account for
direct sun scenarios and greater amounts of view variability.

5.8 Correlations with DMP Survey Data
Some of the most valuable inclusions of the DMP dataset that differentiate it when
compared to other existing daylighting datasets are the Expert and Occupant
Assessments. Survey information is absolutely essential for bridging analytics with
subjective human sensations (in this case visual comfort). Visual comfort surveys are
very hard to come by and even harder to conduct in the field with a substantial sample
size. Though the DMP managed to administer approximately 9.5 occupant surveys per
space and 5.2 expert surveys per space, these accomplishments come with some
limitations. Again, understanding their limitations with the dataset, the DMP stated about
the surveys:
73

“One limitation of the study is that all field responses were completed relative to
the study spaces as a whole, rather than individual locations within the space.
Thus, the ‘study space’ is the finest spatial granularity of the subsequent
analysis.”
It was this nature of the surveys that restricted comparisons between instantaneous (point-
in-time) luminance-based analysis and field responses. For this research, individual
luminance maps could not be related to reported space assessments because the surveys
themselves are not view-dependent.
Despite this, and keeping in mind that the DMP questions are relative to the study space
as a whole, an attempt was made to correlate the luminance based data with the survey
questions. Of the many questions asked to occupants, the three questions that seem to
correlate strongest with indications of visual comfort are:
 Occupant Survey Question 9: I find this room visually attractive.
 Occupant Survey Question 21: The daylight in this room never is too bright.
 Occupant Survey Question 22: I am able to do my work here without any
problems from glare or troubling reflections.
Occupants responded to these questions on a 9-point Likert scale; 9 meaning “strongly
agree” and 1 meaning “strongly disagree.” The occupant responses to these three
questions were correlated with the results for the five glare indices (DGP, DGI, VCP,
UGR and CGI); averages as well as maximum and minimums were considered. Table 9
summarizes these results.
74

Table 9: DMP Survey Question Agreements

R R² Rank
DGPave-Q9 0.782 0.612 2
DGPave-Q21 -0.355 0.126 23
DGPave-Q22 -0.354 0.125 24
DGPmax-Q9 0.790 0.624 1
DGPmax-Q21 -0.374 0.140 22
DGPmax-Q22 -0.351 0.123 25

DGIave-Q9 0.407 0.165 20
DGIave-Q21 -0.413 0.171 19
DGIave-Q22 -0.232 0.054 30
DGImax-Q9 0.563 0.317 7
DGImax-Q21 -0.422 0.178 17
DGImax-Q22 -0.129 0.017 33

UGRave-Q9 0.464 0.216 13
UGRave-Q21 -0.466 0.217 12
UGRave-Q22 -0.308 0.095 26
UGRmax-Q9 0.577 0.333 5
UGRmax-Q21 -0.436 0.190 16
UGRmax-Q22 -0.148 0.022 32

VCPave-Q9 -0.645 0.415 4
VCPave-Q21 0.439 0.193 15
VCPave-Q22 0.299 0.089 28
VCPmin-Q9 -0.570 0.325 6
VCPmin-Q21 0.476 0.227 11
VCPmin-Q22 0.272 0.074 29

CGIave-Q9 0.523 0.273 9
CGIave-Q21 -0.478 0.229 10
CGIave-Q22 -0.380 0.144 21
CGImax-Q9 0.687 0.472 3
CGImax-Q21 -0.416 0.173 18
CGImax-Q22

-0.218

0.047

31

75

Table 9 shows 30 data relationships, each ranked based on their strength of correlation to
one of three survey questions. The first three rows, for example, show the average DGP
value (DGPave) for each space correlated with the averaged numeric survey response for
Q9, Q21 and Q22 respectively. The fourth, fifth and sixth rows show the highest DGP
value for each space (DGPmax) correlated with the averaged numeric survey response for
Q9, Q21 and Q22. The same correlations were calculated for DGI, UGR, VCP, and CGI.
This table highlights that Average Daylight Glare Probability (DGPave) and Maximum
Daylight Glare Probability (DGPmax) have the strongest correlations with occupant
responses, in this case both correlations were with Question 9: I find this room visually
attractive. The coefficients of determination (R²) for these two cases are 0.612 and 0.624,
indeed the highest of all the relationships (the next highest R² value being 0.472). These
results tell us that perhaps DGPave correlates strongest with occupant assessments.
Unfortunately, the calculated R² would need to be much larger to indicate a strong linear
association between DGPave and reported values. An R² value of 0.624 implies that 38%
of the total variation remains unexplained. Thus, the author admits that an R² of 0.624 is
not statistically conclusive. However, given the admitted shortcomings of this research
(previously described in this chapter), this value is high enough to suggest that further-
tuned research in this direction would be of tremendous value.

76

CHAPTER 6: CONCLUSIONS
6.1 Summary of Findings
 DGI, UGR, CGI are very similar to each other. Software programs that calculate
these indices (Evalglare, Diva-for-Rhino, IES VE, etc.) likely only need to
consider one of these metrics.
 VCP is a poor metric for daylight glare analysis and should not be used to
evaluate spaces with direct sun penetration.
 DGP is the best luminance-based metric evaluated in this research, yet DGP still
needs work to account for direct sun conditions and reflected specularity.
 Overcast sky models may not be detailed enough to perform luminance based
visual comfort analysis; overcast sky models may over-simplify distributed
luminous intensities.
 DGPave and DGPmax correlate strongest with DMP occupant assessments,
yielding R² values of 0.612 and 0.624 respectively. Though these values are not
high enough to be considered statistically conclusive, they are high enough and
exciting enough to recommend for future research.

6.2 Future Work
Understandably, the Daylight Metrics Project examined well-daylit buildings with
primary findings in daylight sufficiency. Such a dataset may have proven poor for visual
comfort analysis, as current methods identify visual discomfort (instances of poor
77

daylighting) to inversely predict visual comfort. It is recommended that future visual
comfort research consider spaces with poor daylighting as well. These spaces would help
to answer questions like: do spaces with no windows equally report levels of visual
comfort in simulation and with occupant assessments? Do spaces with more windows
report higher levels of visual comfort and higher levels glare? Can poorly daylit spaces
report high levels of visual comfort? To what extent do daylighting and glare controls
impact visual comfort?
Additionally, it is recommended that view cameras be placed in locations other than the
center of the space, effectively increasing the analytical resolution of the outlined
process. This should be done with care, as adding more cameras does not necessarily
equate to a better representation of a given space. For example, if cameras are placed near
the perimeter of a space where there is no regular seating, results could be seriously
diluted. Hand in hand with placing cameras in more locations is developing the process
for representing an entire space with view cameras. This is an extremely challenging task.
Representing a single space with view cameras is hard enough, let alone developing
routine methodologies for representing all spaces with view cameras. Future work in this
subject would be of great value.
Lastly, the work outlined in this research shows high potential for luminance based
annual visual comfort metrics. The primary findings of this research (DGPave and
DGPmax correlations) show that luminance based metrics can indeed be used to
understand the visual comfort probability of an entire space, over an entire year. Though
78

the methods used in this work are tedious and time-consuming, future refinement of this
process and advancements in computation will only help to make this framework more
practical for use in visual comfort analysis.

79

ENDNOTES

i
U.S. Energy Information Agency. (2003). Commercial Buildings Energy Consumption
Survey. http://www.eia.gov/emeu/cbecs/contents.html
ii
Boyce, P., Howlett, O., Hunter, C. (2003). The Benefits of Daylight through Windows.
Prepared for the United Stated Department of Energy.
iii
Heschong Mahone Group (2003). Windows and Offices: A Study of Office Worker
Performance and the Indoor Environment. Prepared for the California Energy
Commission.
iv
Heschong Mahone Group (2003). Daylight and Retail Sales. Prepared for the
California Energy Commission.
v
Heschong Mahone Group (1999). Daylighting in Schools, An Investigation into the
Relationship Between Daylighting and Human Performance. Prepared for Pacific Gas
and Electric Company.
vi
Suk, J., Schiler, M., Kensek, K. (2007). Post Treatment Analysis of the Glare
Remediation of the Walt Disney Concert Hall.
vii
DiLaura, D., Houser, K., Mistrick, R., Steffy, G., (2010) The Lighting Handbook,
Tenth Edition, Reference and Application. Illuminating Engineering Society. p.12.6
viii
DiLaura, D., Houser, K., Mistrick, R., Steffy, G., (2010) The Lighting Handbook,
Tenth Edition, Reference and Application. Illuminating Engineering Society. p.4.25
ix
DiLaura, D., Houser, K., Mistrick, R., Steffy, G., (2010) The Lighting Handbook, Tenth
Edition, Reference and Application. Illuminating Engineering Society. p.12.14
x
Schorsch.com, (2004-2011) Lighting Design Glossary.
http://www.schorsch.com/en/kbase/glossary/luminance.html
xi
Auckland Council. (2011).
http://www.northshorecity.govt.nz/idsm/idsm2009/2071.htm.
xii
Wienold, J., Christofferson, J., (2006). Evaluation methods and development of new
glare prediction model for daylighting environments with the use of CCD cameras.
Energy and Buildings 38.
xiii
Wienold, J., (2009). Dynamic Daylight Glare Evaluation. International IBPSA
Conference 2009.
80

xiv
Gibbons, R., (2003). Glare Modeling Formulae. Virginia Tech Transportation
Institute.
xv
Wienold, J., Christofferson, J., (2006). Evaluation methods and development of new
glare prediction model for daylighting environments with the use of CCD cameras.
Energy and Buildings 38.
xvi
Ahmet Oguz Akyuz (2009). Bracket: HDR Photo Manager v1.0.0 (beta).
xvii
U.S. Department of Energy (2012). http://radsite.lbl.gov/radiance/framew.html
xviii
Dictionary.com (2012). http://dictionary.reference.com/browse/ray+tracing.
xix
AGi32 Lighting Analysts Inc. (1999-2012), Radiosity Limitations.
http://docs.agi32.com/AGi32/Content/calculate/Calculation_Concepts.htm
xx
Yin, H., (2011). Glare Studies: Comparison of Three Glare Indices, HDR Imaging and
Measured Values.
xxi
Weinold, J., (2005). Evalglare – A new Radiance based tool to evaluate daylight glare
in office spaces. http://www.radiance-online.org/radiance-
workshop3/cd/Wienold_extabs.pdf
xxii
Reinhart, C. (2006). Tutorial on the Use of Daysim Simulations for Sustainable
Design. National Research Council Canada.
xxiii
Reinhart, C. (2006). Tutorial on the Use of Daysim Simulations for Sustainable
Design. National Research Council Canada.
xxiv
Reinhart, C. (2006). Tutorial on the Use of Daysim Simulations for Sustainable
Design. National Research Council Canada.
xxv
Suk, J., Schiler, M., Kensek, K. (2007). Post Treatment Analysis of the Glare
Remediation of the Walt Disney Concert Hall.
xxvi
Inanici, Mehlika (2009). Daylighting the New York Times Headquarters Building.
http://windows.lbl.gov/comm_perf/newyorktimes.
xxvii
DiLaura, D., Houser, K., Mistrick, R., Steffy, G., (2010) The Lighting Handbook,
Tenth Edition, Reference and Application. Illuminating Engineering Society. p.4.2
xxviii
Heschong Mahone Group Inc. (2011). Daylighting Metrics Report. California
Energy Commission.
81

xxix
Reinhart, C. (2006). Tutorial on the Use of Daysim Simulations for Sustainable
Design. National Research Council Canada.
xxx
Jakubiec, Reinhart (2011). ‘The Adaptive Zone’ – A Concept for Assessing Glare
throughout Daylit Spaces. Building Simulation 2011. P.21
xxxi
Niemasz (2012). Annual Glare – DIVA for Rhino Environmental Analysis for
Buildings. http://diva4rhino.com/user-guide/simulation-types/annual-glare
xxxii
Heschong Mahone Group Inc. (2011). Daylighting Metrics Report. California Energy
Commission.
82

BIBLIOGRAPHY
AGi32 Lighting Analysts Inc. (1999-2012), Radiosity Limitations.
http://docs.agi32.com/AGi32/Content/calculate/Calculation_Concepts.htm
Ahmet Oguz Akyuz (2009). Bracket: HDR Photo Manager v1.0.0 (beta).
Auckland Council. (2011). http://www.northshorecity.govt.nz/idsm/idsm2009/2071.htm.
Boyce, P., Howlett, O., Hunter, C. (2003). The Benefits of Daylight through Windows.
Prepared for the United Stated Department of Energy.
DiLaura, D., Houser, K., Mistrick, R., Steffy, G., (2010) The Lighting Handbook, Tenth
Edition, Reference and Application. Illuminating Engineering Society.
Gibbons, R., (2003). Glare Modeling Formulae. Virginia Tech Transportation Institute.
Heschong Mahone Group (1999). Daylighting in Schools, An Investigation into the
Relationship Between Daylighting and Human Performance. Prepared for Pacific Gas
and Electric Company.
Heschong Mahone Group (2003). Daylight and Retail Sales. Prepared for the California
Energy Commission.
Heschong Mahone Group (2003). Windows and Offices: A Study of Office Worker
Performance and the Indoor Environment. Prepared for the California Energy
Commission.
Heschong Mahone Group Inc. (2011). Daylighting Metrics Report. California Energy
Commission.
Inanici, Mehlika (2009). Daylighting the New York Times Headquarters Building.
http://windows.lbl.gov/comm_perf/newyorktimes.
Jakubiec, Reinhart (2011). ‘The Adaptive Zone’ – A Concept for Assessing Glare
throughout Daylit Spaces. Building Simulation 2011.
Niemasz (2012). Annual Glare – DIVA for Rhino Environmental Analysis for Buildings.
http://diva4rhino.com/user-guide/simulation-types/annual-glare
Reinhart, C. (2006). Tutorial on the Use of Daysim Simulations for Sustainable Design.
National Research Council Canada.
83

Schorsch.com, (2004-2011) Lighting Design Glossary.
http://www.schorsch.com/en/kbase/glossary/luminance.html
Suk, J., Schiler, M., Kensek, K. (2007). Post Treatment Analysis of the Glare
Remediation of the Walt Disney Concert Hall.
U.S. Energy Information Agency. (2003). Commercial Buildings Energy Consumption
Survey. http://www.eia.gov/emeu/cbecs/contents.html
U.S. Department of Energy (2012). http://radsite.lbl.gov/radiance/framew.html
Weinold, J., (2005). Evalglare – A new Radiance based tool to evaluate daylight glare in
office spaces. http://www.radiance-online.org/radiance-
workshop3/cd/Wienold_extabs.pdf
Wienold, J., Christofferson, J., (2006). Evaluation methods and development of new glare
prediction model for daylighting environments with the use of CCD cameras. Energy and
Buildings 38.
Wienold, J., (2009). Dynamic Daylight Glare Evaluation. International IBPSA
Conference 2009.
Yin, H., (2011). Glare Studies: Comparison of Three Glare Indices, HDR Imaging and
Measured Values.

84

APPENDIX A: ECOTECT MODELS

Figure 38: Ecotect Model #1 (Perspective and Plan Showing Views)

85

Figure 39: Ecotect Model #2 (Perspective and Plan Showing Views)

86

Figure 40: Ecotect Model #3 (Perspective and Plan Showing Views)

87

Figure 41: Ecotect Model #4 (Perspective and Plan Showing Views)

88

Figure 42: Ecotect Model #5 (Perspective and Plan Showing Views)

89

Figure 43: Ecotect Model #6 (Perspective and Plan Showing Views)

90

Figure 44: Ecotect Model #7 (Perspective and Plan Showing Views)

91

=

Figure 45: Ecotect Model #8 (Perspective and Plan Showing Views)

92

Figure 46: Ecotect Model #9 (Perspective and Plan Showing Views)

93

Figure 47: Ecotect Model #10 (Perspective and Plan Showing Views)

94

Figure 48: Ecotect Model #11 (Perspective and Plan Showing Views)
95

Figure 49: Ecotect Model #12 (Perspective and Plan Showing Views)

96

Figure 50: Ecotect Model #13 (Perspective and Plan Showing Views)

97

Figure 51: Ecotect Model #14 (Perspective and Plan Showing Views)

98

APPENDIX B: SIMULATION PARAMETERS

Figure 52: Ecotect to RadianceCP Export Settings

99

Figure 53: Radiance CP Scene Definitions

Figure 54: RadianceCP Batch Render Dialogue

100

APPENDIX C: EVALGLARE VIEWS

Figure 55: Evalglare Views for Model #1

101

Figure 56: Evalglare Views for Model #2

102

Figure 57: Evalglare Views for Model #3

103

Figure 58: Evalglare Views for Model #4

104

Figure 59: Evalglare Views for Model #5

105

Figure 60: Evalglare Views for Model #6

106

Figure 61: Evalglare Views for Model #7

107

Figure 62: Evalglare Views for Model #8

108

Figure 63: Evalglare Views for Model #9

109

Figure 64: Evalglare Views for Model #10

110

Figure 65: Evalglare Views for Model #11

111

Figure 66: Evalglare Views for Model #12

112

Figure 67: Evalglare Views for Model #13

113

Figure 68: Evalglare Views for Model #14

114

APPENDIX D: ALL VISUAL COMFORT RESULTS
Table 10: All Visual Comfort Results
View # Sky Month Time Looking DGP DGI UGR VCP CGI
1 clear 6 900 east 0.21 10.68 15.47 49.24 18.68
2 clear 6 900 north 0.27 15.82 19.31 52.39 23.74
3 clear 6 900 south 0.17 100.00
4 clear 6 900 west 0.20 6.26 10.40 92.32 13.58
5 clear 6 1300 east 0.22 12.90 17.81 45.09 20.90
6 clear 6 1300 north 0.31 20.31 25.12 0.95 29.85
7 clear 6 1300 south 0.18 100.00
8 clear 6 1300 west 0.21 12.32 17.50 34.03 20.23
9 clear 6 1700 east 0.19 10.50 15.10 47.68 17.16
10 clear 6 1700 north 0.24 13.38 15.93 54.54 19.77
11 clear 6 1700 south 0.17 100.00
12 clear 6 1700 west 0.19 10.63 15.64 48.40 17.48
13 clear 9 900 east 0.21 12.32 17.55 32.69 19.68
14 clear 9 900 north 0.27 18.10 22.59 2.94 26.77
15 clear 9 900 south 0.17 100.00
16 clear 9 900 west 0.20 10.55 15.50 48.10 17.64
17 clear 9 1300 east 0.22 14.24 19.76 22.40 22.64
18 clear 9 1300 north 0.33 22.81 28.30 0.00 32.59
19 clear 9 1300 south 0.18 100.00
20 clear 9 1300 west 0.22 14.08 19.83 24.94 22.47
21 clear 9 1700 east 0.18 9.96 14.67 59.09 15.51
22 clear 9 1700 north 0.22 15.97 19.94 9.43 22.46
23 clear 9 1700 south 0.16 100.00
24 clear 9 1700 west 0.18 9.59 14.49 63.34 15.27
25 clear 12 900 east 0.20 12.22 17.54 39.05 18.69
26 clear 12 900 north 0.25 20.03 24.65 1.70 27.39
27 clear 12 900 south 0.17 100.00
28 clear 12 900 west 0.19 10.45 15.67 53.73 16.83
29 clear 12 1300 east 0.22 14.13 19.85 24.25 22.44
30 clear 12 1300 north 0.33 23.17 28.84 0.00 32.65
31 clear 12 1300 south 0.17 100.00
32 clear 12 1300 west 0.22 14.14 20.12 25.59 22.42
33 clear 12 1700 east 0.17 4.80 7.96 95.61 8.22
34 clear 12 1700 north 0.18 10.36 13.05 59.32 13.79
35 clear 12 1700 south 0.16 100.00
36 clear 12 1700 west 0.17 4.90 8.34 95.64 8.34
37 overcast 6 900 east 0.19 8.93 13.89 68.30 16.41
38 overcast 6 900 north 0.24 14.53 19.43 15.20 22.96
39 overcast 6 900 south 0.17 100.00
115

Table 10: All Visual Comfort Metrics, Continued
40 overcast 6 900 west 0.19 7.51 12.30 86.41 14.80
41 overcast 6 1300 east 0.20 9.39 14.51 63.29 17.26
42 overcast 6 1300 north 0.26 15.04 20.11 12.08 24.03
43 overcast 6 1300 south 0.17 100.00
44 overcast 6 1300 west 0.19 7.70 12.85 85.33 15.57
45 overcast 6 1700 east 0.18 7.49 11.97 81.05 14.06
46 overcast 6 1700 north 0.21 13.09 17.50 26.71 20.10
47 overcast 6 1700 south 0.16 100.00
48 overcast 6 1700 west 0.18 5.76 10.28 89.96 12.44
49 overcast 9 900 east 0.19 8.08 12.75 76.09 15.01
50 overcast 9 900 north 0.22 13.70 18.32 21.35 21.28
51 overcast 9 900 south 0.17 100.00
52 overcast 9 900 west 0.18 6.40 11.08 91.49 13.38
53 overcast 9 1300 east 0.19 8.68 13.55 70.45 16.05
54 overcast 9 1300 north 0.24 14.30 19.12 16.66 22.55
55 overcast 9 1300 south 0.17 100.00
56 overcast 9 1300 west 0.19 6.94 11.83 82.49 14.35
57 overcast 9 1700 east 0.17 5.05 8.69 94.31 10.32
58 overcast 9 1700 north 0.18 10.60 14.18 53.55 15.65
59 overcast 9 1700 south 0.16 100.00
60 overcast 9 1700 west 0.17 3.28 6.96 97.67 8.74
61 overcast 12 900 east 0.17 5.81 9.72 91.27 11.48
62 overcast 12 900 north 0.19 11.45 15.32 43.98 17.08
63 overcast 12 900 south 0.16 100.00
64 overcast 12 900 west 0.17 4.11 8.07 96.00 9.94
65 overcast 12 1300 east 0.18 7.10 11.45 83.88 13.44
66 overcast 12 1300 north 0.21 12.72 17.01 30.30 19.38
67 overcast 12 1300 south 0.16 100.00
68 overcast 12 1300 west 0.18 5.43 9.79 94.94 11.87
69 overcast 12 1700 east 0.16 -21.21 -26.69 100.00 -23.73
70 overcast 12 1700 north 0.16 -33.94 -39.78 100.00 -36.57
71 overcast 12 1700 south 0.16 -34.41 -39.86 100.00 -36.66
72 overcast 12 1700 west 0.16 100.00
73 clear 6 900 northeast 0.33 18.64 23.19 17.03 28.12
74 clear 6 900 northwest 0.26 12.87 16.93 58.50 20.95
75 clear 6 900 southeast 0.24 10.82 14.34 78.27 17.88
76 clear 6 900 southwest 0.21 100.00
77 clear 6 1300 northeast 0.33 21.94 26.36 4.83 31.45
78 clear 6 1300 northwest 0.25 15.68 19.53 28.49 23.49
79 clear 6 1300 southeast 0.23 12.51 15.99 54.57 19.64
80 clear 6 1300 southwest 0.20 100.00
81 clear 6 1700 northeast 0.31 22.96 27.51 6.24 31.41
82 clear 6 1700 northwest 0.22 15.22 18.85 34.89 22.08
83 clear 6 1700 southeast 0.22 15.67 19.44 37.96 22.58
116

Table 10: All Visual Comfort Metrics, Continued
84 clear 6 1700 southwest 0.19 100.00
85 clear 9 900 northeast 0.30 21.47 25.52 22.93 29.95
86 clear 9 900 northwest 0.26 17.77 21.19 29.70 25.34
87 clear 9 900 southeast 0.21 11.82 15.19 69.90 18.55
88 clear 9 900 southwest 0.22 12.61 16.73 67.50 20.03
89 clear 9 1300 northeast 0.30 21.61 25.84 11.27 30.32
90 clear 9 1300 northwest 0.24 15.06 18.84 34.99 22.56
91 clear 9 1300 southeast 0.22 11.71 15.01 61.47 18.47
92 clear 9 1300 southwest 0.19 100.00
93 clear 9 1700 northeast 0.24 19.55 23.40 18.41 25.87
94 clear 9 1700 northwest 0.19 11.40 14.07 70.76 16.83
95 clear 9 1700 southeast 0.20 13.93 17.10 59.95 19.46
96 clear 9 1700 southwest 0.17 100.00
97 clear 12 900 northeast 0.27 21.54 25.68 19.54 28.85
98 clear 12 900 northwest 0.21 15.51 18.93 58.97 21.77
99 clear 12 900 southeast 0.19 11.28 14.23 67.68 17.19
100 clear 12 900 southwest 0.18 100.00
101 clear 12 1300 northeast 0.26 17.79 21.30 29.17 25.26
102 clear 12 1300 northwest 0.22 15.26 18.91 38.76 22.25
103 clear 12 1300 southeast 0.20 10.23 13.19 83.77 16.48
104 clear 12 1300 southwest 0.18 100.00
105 clear 12 1700 northeast 0.18 12.73 14.05 76.54 15.42
106 clear 12 1700 northwest 0.17 7.71 8.96 95.63 10.93
107 clear 12 1700 southeast 0.17 5.56 6.30 98.61 8.59
108 clear 12 1700 southwest 0.16 100.00
109 overcast 6 900 northeast 0.21 14.40 17.07 65.38 20.20
110 overcast 6 900 northwest 0.19 10.72 13.31 72.96 16.09
111 overcast 6 900 southeast 0.18 7.22 9.38 91.15 12.33
112 overcast 6 900 southwest 0.17 100.00
113 overcast 6 1300 northeast 0.22 15.86 18.29 53.67 21.51
114 overcast 6 1300 northwest 0.19 11.81 14.61 64.00 17.39
115 overcast 6 1300 southeast 0.18 7.88 10.21 88.35 13.19
116 overcast 6 1300 southwest 0.17 -28.41 -26.34 100.00 -23.09
117 overcast 6 1700 northeast 0.19 12.98 15.26 72.53 18.08
118 overcast 6 1700 northwest 0.18 9.32 11.44 83.54 13.99
119 overcast 6 1700 southeast 0.17 5.75 7.43 96.00 10.27
120 overcast 6 1700 southwest 0.17 100.00
121 overcast 9 900 northeast 0.20 13.65 15.72 70.46 18.75
122 overcast 9 900 northwest 0.18 9.22 11.54 87.08 14.34
123 overcast 9 900 southeast 0.17 6.06 8.00 94.77 10.93
124 overcast 9 900 southwest 0.17 100.00
125 overcast 9 1300 northeast 0.21 14.52 16.77 63.79 19.92
126 overcast 9 1300 northwest 0.19 10.57 13.07 72.87 15.90
127 overcast 9 1300 southeast 0.18 6.71 8.85 92.65 11.82
117

Table 10: All Visual Comfort Metrics, Continued
128 overcast 9 1300 southwest 0.17 100.00
129 overcast 9 1700 northeast 0.18 10.98 12.44 89.20 14.89
130 overcast 9 1700 northwest 0.17 7.22 8.55 94.05 10.84
131 overcast 9 1700 southeast 0.17 3.63 4.50 99.06 7.22
132 overcast 9 1700 southwest 0.16 100.00
133 overcast 12 900 northeast 0.19 11.92 13.26 83.52 15.95
134 overcast 12 900 northwest 0.17 8.07 9.69 90.14 12.17
135 overcast 12 900 southeast 0.17 4.17 5.41 98.41 8.22
136 overcast 12 900 southwest 0.16 100.00
137 overcast 12 1300 northeast 0.19 13.08 14.82 75.87 17.68
138 overcast 12 1300 northwest 0.18 8.79 10.80 89.16 13.49
139 overcast 12 1300 southeast 0.17 5.20 6.86 96.70 9.73
140 overcast 12 1300 southwest 0.17 -23.50 -21.98 100.00 -18.74
141 overcast 12 1700 northeast 0.16 100.00
142 overcast 12 1700 northwest 0.16 100.00
143 overcast 12 1700 southeast 0.16 100.00
144 overcast 12 1700 southwest 0.16 100.00
145 clear 6 900 east 0.19 13.94 16.17 88.37 16.84
146 clear 6 900 north 0.21 18.83 21.18 63.11 21.36
147 clear 6 900 south 0.18 11.46 17.30 90.97 16.15
148 clear 6 900 west 0.18 8.70 12.33 95.74 14.13
149 clear 6 1300 east 0.27 21.47 30.26 36.09 29.15
150 clear 6 1300 north 0.26 21.95 30.41 18.67 29.26
151 clear 6 1300 south 0.23 19.84 23.72 66.02 23.69
152 clear 6 1300 west 0.18 8.24 11.45 96.19 13.22
153 clear 6 1700 east 0.18 8.91 13.30 96.85 14.12
154 clear 6 1700 north 0.17 5.78 11.28 97.29 11.14
155 clear 6 1700 south 0.19 14.70 19.03 85.43 17.86
156 clear 6 1700 west 0.17 7.20 9.91 98.13 11.77
157 clear 9 900 east 0.17 8.35 12.03 97.72 12.75
158 clear 9 900 north 0.18 13.21 15.17 88.48 14.82
159 clear 9 900 south 0.18 9.53 14.04 95.82 12.61
160 clear 9 900 west 0.17 7.85 10.53 97.87 11.51
161 clear 9 1300 east 0.17 6.94 10.60 98.50 11.84
162 clear 9 1300 north 0.17 5.24 9.80 98.09 9.91
163 clear 9 1300 south 0.17 8.80 11.54 96.68 11.14
164 clear 9 1300 west 0.17 7.32 9.93 98.04 11.21
165 clear 9 1700 east 0.17 5.84 10.00 100.00 10.49
166 clear 9 1700 north 0.17 3.67 8.38 100.00 7.68
167 clear 9 1700 south 0.17 7.40 9.89 98.76 9.03
168 clear 9 1700 west 0.17 5.08 6.96 100.00 8.41
169 clear 12 900 east 0.17 4.87 8.09 100.00 8.87
170 clear 12 900 north 0.17 2.35 5.50 100.00 5.19
171 clear 12 900 south 0.17 6.72 9.79 99.14 8.33
118

Table 10: All Visual Comfort Metrics, Continued
172 clear 12 900 west 0.17 4.78 6.40 100.00 7.25
173 clear 12 1300 east 0.17 5.36 8.37 100.00 9.48
174 clear 12 1300 north 0.17 3.85 7.57 100.00 7.32
175 clear 12 1300 south 0.17 7.91 10.45 98.37 9.43
176 clear 12 1300 west 0.17 6.37 8.51 99.00 9.07
177 clear 12 1700 east 0.16 1.20 3.29 100.00 3.94
178 clear 12 1700 north 0.16 -1.62 1.02 100.00 0.60
179 clear 12 1700 south 0.16 1.99 3.47 100.00 2.41
180 clear 12 1700 west 0.16 -0.32 -0.13 100.00 1.58
181 overcast 6 900 east 0.19 10.15 15.33 92.45 16.22
182 overcast 6 900 north 0.18 6.90 12.63 94.52 13.22
183 overcast 6 900 south 0.18 10.96 15.57 90.57 15.14
184 overcast 6 900 west 0.18 8.50 11.80 94.94 13.85
185 overcast 6 1300 east 0.19 10.78 16.16 90.18 17.11
186 overcast 6 1300 north 0.18 7.56 13.58 92.55 14.28
187 overcast 6 1300 south 0.18 11.46 16.17 88.21 16.05
188 overcast 6 1300 west 0.18 9.03 12.51 93.36 14.64
189 overcast 6 1700 east 0.18 8.98 13.59 95.48 14.57
190 overcast 6 1700 north 0.17 5.86 11.22 96.90 11.59
191 overcast 6 1700 south 0.18 9.91 14.12 94.10 13.52
192 overcast 6 1700 west 0.17 7.47 10.42 97.02 12.42
193 overcast 9 900 east 0.18 9.09 13.86 95.42 14.70
194 overcast 9 900 north 0.17 5.89 11.28 96.84 11.62
195 overcast 9 900 south 0.18 9.92 14.16 94.06 13.52
196 overcast 9 900 west 0.17 7.56 10.60 96.98 12.53
197 overcast 9 1300 east 0.19 9.90 14.92 93.22 15.85
198 overcast 9 1300 north 0.18 6.69 12.34 95.12 12.87
199 overcast 9 1300 south 0.18 10.67 15.16 91.56 14.75
200 overcast 9 1300 west 0.18 8.27 11.50 95.41 13.55
201 overcast 9 1700 east 0.17 6.71 10.65 98.79 11.39
202 overcast 9 1700 north 0.17 3.53 8.15 100.00 8.11
203 overcast 9 1700 south 0.17 7.45 10.77 98.34 9.96
204 overcast 9 1700 west 0.17 5.05 7.17 100.00 9.10
205 overcast 12 900 east 0.17 5.89 9.53 100.00 10.26
206 overcast 12 900 north 0.17 2.81 7.22 100.00 7.05
207 overcast 12 900 south 0.17 6.60 9.61 98.98 8.84
208 overcast 12 900 west 0.17 4.30 6.20 100.00 8.10
209 overcast 12 1300 east 0.17 7.99 12.36 97.46 13.12
210 overcast 12 1300 north 0.17 4.88 10.02 98.35 10.02
211 overcast 12 1300 south 0.17 8.79 12.66 96.58 11.86
212 overcast 12 1300 west 0.17 6.50 9.17 98.39 11.03
213 overcast 12 1700 east 0.16 100.00
214 overcast 12 1700 north 0.16 100.00
215 overcast 12 1700 south 0.16 100.00
119

Table 10: All Visual Comfort Metrics, Continued
216 overcast 12 1700 west 0.16 100.00
217 clear 6 900 east 0.23 17.69 24.26 14.14 24.37
218 clear 6 900 north 0.22 19.40 23.21 38.33 23.55
219 clear 6 900 south 0.19 12.79 17.80 81.69 17.94
220 clear 6 900 west 0.20 14.45 19.99 71.29 20.39
221 clear 6 1300 east 0.21 15.83 21.01 24.16 21.83
222 clear 6 1300 north 0.23 20.54 23.91 28.41 24.81
223 clear 6 1300 south 0.19 11.44 15.55 86.49 16.39
224 clear 6 1300 west 0.21 16.55 21.92 59.41 21.93
225 clear 6 1700 east 0.21 15.85 22.13 26.00 21.88
226 clear 6 1700 north 0.25 21.78 26.90 28.99 27.01
227 clear 6 1700 south 0.18 11.11 15.64 83.98 16.08
228 clear 6 1700 west 0.21 16.12 21.37 50.76 21.56
229 clear 9 900 east 0.25 18.42 24.65 12.23 25.11
230 clear 9 900 north 0.22 19.96 23.14 33.54 23.37
231 clear 9 900 south 0.19 12.20 16.89 73.60 16.79
232 clear 9 900 west 0.20 16.01 21.02 60.71 20.91
233 clear 9 1300 east 0.25 20.43 26.02 13.41 27.27
234 clear 9 1300 north 0.25 21.98 25.34 16.01 27.10
235 clear 9 1300 south 0.23 19.26 24.59 32.54 24.93
236 clear 9 1300 west 0.23 18.31 24.73 34.77 25.33
237 clear 9 1700 east 0.21 14.07 18.93 59.32 19.13
238 clear 9 1700 north 0.28 23.75 31.71 13.22 30.25
239 clear 9 1700 south 0.18 11.66 15.13 88.02 14.99
240 clear 9 1700 west 0.23 17.59 24.39 31.22 23.65
241 clear 12 900 east 0.22 16.13 21.59 43.43 21.39
242 clear 12 900 north 0.21 17.97 21.40 33.89 20.98
243 clear 12 900 south 0.18 10.69 14.78 86.30 14.45
244 clear 12 900 west 0.20 13.85 19.75 60.12 19.11
245 clear 12 1300 east 0.25 22.14 26.58 12.68 27.38
246 clear 12 1300 north 0.22 18.94 21.78 40.04 23.36
247 clear 12 1300 south 0.21 17.54 22.40 58.04 22.75
248 clear 12 1300 west 0.21 15.63 20.83 39.66 21.75
249 clear 12 1700 east 0.17 9.30 12.45 88.38 12.53
250 clear 12 1700 north 0.23 19.46 26.33 48.78 23.61
251 clear 12 1700 south 0.17 5.86 8.28 100.00 8.36
252 clear 12 1700 west 0.18 12.81 19.16 78.69 17.01
253 overcast 6 900 east 0.22 17.37 24.72 18.64 23.15
254 overcast 6 900 north 0.22 18.02 22.65 32.79 22.60
255 overcast 6 900 south 0.19 12.48 18.32 72.55 18.01
256 overcast 6 900 west 0.21 15.81 22.58 60.27 21.54
257 overcast 6 1300 east 0.22 17.91 25.50 14.62 24.12
258 overcast 6 1300 north 0.22 18.54 23.30 27.80 23.49
259 overcast 6 1300 south 0.20 13.09 19.20 67.05 18.98
120

Table 10: All Visual Comfort Metrics, Continued
260 overcast 6 1300 west 0.21 16.42 23.42 38.88 22.60
261 overcast 6 1700 east 0.21 16.02 22.86 29.07 21.08
262 overcast 6 1700 north 0.21 16.80 20.95 44.28 20.71
263 overcast 6 1700 south 0.19 11.17 16.60 89.10 16.12
264 overcast 6 1700 west 0.20 14.80 21.22 64.18 19.85
265 overcast 9 900 east 0.21 16.08 23.05 28.86 21.11
266 overcast 9 900 north 0.21 16.86 21.06 44.06 20.74
267 overcast 9 900 south 0.19 11.25 16.71 81.75 16.23
268 overcast 9 900 west 0.20 14.81 21.27 55.90 19.85
269 overcast 9 1300 east 0.22 17.27 24.58 19.69 22.89
270 overcast 9 1300 north 0.22 17.68 22.15 35.59 22.13
271 overcast 9 1300 south 0.19 12.51 18.30 79.31 17.95
272 overcast 9 1300 west 0.21 15.62 22.33 62.33 21.20
273 overcast 9 1700 east 0.19 13.96 20.11 52.79 17.77
274 overcast 9 1700 north 0.19 14.58 18.04 67.77 17.30
275 overcast 9 1700 south 0.17 9.11 13.82 95.26 13.04
276 overcast 9 1700 west 0.18 12.44 18.09 83.52 16.21
277 overcast 12 900 east 0.18 13.13 19.10 61.72 16.54
278 overcast 12 900 north 0.18 13.78 16.96 75.32 16.08
279 overcast 12 900 south 0.17 8.27 12.64 96.93 11.92
280 overcast 12 900 west 0.18 11.67 17.07 87.93 15.09
281 overcast 12 1300 east 0.21 15.06 21.66 39.61 19.47
282 overcast 12 1300 north 0.21 15.83 19.68 55.28 19.10
283 overcast 12 1300 south 0.18 10.15 15.31 93.26 14.60
284 overcast 12 1300 west 0.20 13.72 19.81 74.13 18.12
285 overcast 12 1700 east 0.16 -12.96 -19.58 100.00 -19.03
286 overcast 12 1700 north 0.16 -20.40 -26.97 100.00 -25.29
287 overcast 12 1700 south 0.16 -25.37 -32.61 100.00 -29.99
288 overcast 12 1700 west 0.16 -40.33 -49.40 100.00 -46.17
289 clear 6 900 east 0.17 -0.59 2.84 100.00 5.16
290 clear 6 900 north 0.16 -23.44 -23.53 100.00 -20.28
291 clear 6 900 south 0.18 5.60 9.71 88.12 10.86
292 clear 6 900 west 0.17 2.17 7.12 98.58 8.11
293 clear 6 1300 east 0.17 2.02 7.42 98.88 7.99
294 clear 6 1300 north 0.16 100.00
295 clear 6 1300 south 0.17 7.00 12.59 86.44 11.42
296 clear 6 1300 west 0.17 1.74 7.05 99.13 7.76
297 clear 6 1700 east 0.17 3.47 10.09 97.38 9.74
298 clear 6 1700 north 0.16 100.00
299 clear 6 1700 south 0.18 7.90 14.28 81.31 12.74
300 clear 6 1700 west 0.17 2.05 7.46 98.88 8.27
301 clear 9 900 east 0.17 -1.85 1.16 100.00 3.60
302 clear 9 900 north 0.16 -17.64 -18.50 100.00 -15.25
303 clear 9 900 south 0.17 4.62 8.37 91.92 9.63
121

Table 10: All Visual Comfort Metrics, Continued
304 clear 9 900 west 0.17 1.50 6.17 99.08 7.10
305 clear 9 1300 east 0.17 1.64 6.97 100.00 7.39
306 clear 9 1300 north 0.16 100.00
307 clear 9 1300 south 0.17 6.38 11.77 89.63 10.57
308 clear 9 1300 west 0.17 1.07 6.05 100.00 6.85
309 clear 9 1700 east 0.17 0.82 6.60 100.00 5.82
310 clear 9 1700 north 0.16 100.00
311 clear 9 1700 south 0.17 4.92 10.07 95.62 8.42
312 clear 9 1700 west 0.17 -1.32 2.72 100.00 3.62
313 clear 12 900 east 0.16 -3.80 -1.43 100.00 0.73
314 clear 12 900 north 0.16 -19.45 -20.96 100.00 -17.71
315 clear 12 900 south 0.17 2.28 5.28 98.34 5.84
316 clear 12 900 west 0.17 -1.21 2.62 100.00 3.41
317 clear 12 1300 east 0.17 0.29 5.19 100.00 5.48
318 clear 12 1300 north 0.16 100.00
319 clear 12 1300 south 0.17 4.96 9.85 95.14 8.47
320 clear 12 1300 west 0.17 -0.35 4.17 100.00 4.89
321 clear 12 1700 east 0.16 -5.59 -2.76 100.00 -2.29
322 clear 12 1700 north 0.16 100.00
323 clear 12 1700 south 0.16 -0.50 2.62 100.00 0.71
324 clear 12 1700 west 0.16 -5.69 -2.81 100.00 -2.31
325 overcast 6 900 east 0.17 0.27 4.93 100.00 5.73
326 overcast 6 900 north 0.16 100.00
327 overcast 6 900 south 0.17 5.53 10.63 93.60 9.11
328 overcast 6 900 west 0.17 0.49 5.45 100.00 6.03
329 overcast 6 1300 east 0.17 0.86 5.72 100.00 6.55
330 overcast 6 1300 north 0.16 100.00
331 overcast 6 1300 south 0.17 6.13 11.43 91.17 10.01
332 overcast 6 1300 west 0.17 1.10 6.28 100.00 6.87
333 overcast 6 1700 east 0.17 -0.75 3.57 100.00 4.35
334 overcast 6 1700 north 0.16 100.00
335 overcast 6 1700 south 0.17 4.53 9.30 96.46 7.63
336 overcast 6 1700 west 0.17 -0.49 4.18 100.00 4.69
337 overcast 9 900 east 0.17 -0.74 3.59 100.00 4.35
338 overcast 9 900 north 0.16 100.00
339 overcast 9 900 south 0.17 4.53 9.30 96.47 7.63
340 overcast 9 900 west 0.17 -0.51 4.14 100.00 4.66
341 overcast 9 1300 east 0.17 0.07 4.68 100.00 5.47
342 overcast 9 1300 north 0.16 100.00
343 overcast 9 1300 south 0.17 5.34 10.39 94.25 8.82
344 overcast 9 1300 west 0.17 0.31 5.24 100.00 5.78
345 overcast 9 1700 east 0.16 -3.11 0.42 100.00 1.15
346 overcast 9 1700 north 0.16 100.00
347 overcast 9 1700 south 0.17 2.17 6.15 100.00 4.31
122

Table 10: All Visual Comfort Metrics, Continued
348 overcast 9 1700 west 0.16 -2.88 0.96 100.00 1.46
349 overcast 12 900 east 0.16 -3.88 -0.60 100.00 0.12
350 overcast 12 900 north 0.16 100.00
351 overcast 12 900 south 0.17 1.39 5.11 100.00 3.24
352 overcast 12 900 west 0.16 -3.64 -0.04 100.00 0.43
353 overcast 12 1300 east 0.16 -1.85 2.11 100.00 2.85
354 overcast 12 1300 north 0.16 100.00
355 overcast 12 1300 south 0.17 3.42 7.82 98.30 6.06
356 overcast 12 1300 west 0.16 -1.63 2.62 100.00 3.15
357 overcast 12 1700 east 0.16 -21.63 -28.90 100.00 -27.07
358 overcast 12 1700 north 0.16 -17.96 -25.32 100.00 -23.72
359 overcast 12 1700 south 0.16 100.00
360 overcast 12 1700 west 0.16 100.00
361 clear 6 900 northeast 0.27 20.02 24.30 25.41 27.96
362 clear 6 900 northwest 0.21 10.27 13.37 76.89 16.47
363 clear 6 900 southeast 0.21 12.55 16.93 57.70 20.01
364 clear 6 900 southwest 0.18 4.40 9.61 94.99 12.71
365 clear 6 1300 northeast 0.21 5.43 10.87 77.75 14.25
366 clear 6 1300 northwest 0.21 5.92 11.44 80.86 14.44
367 clear 6 1300 southeast 0.20 4.49 9.60 89.38 12.79
368 clear 6 1300 southwest 0.18 4.18 9.32 95.85 12.37
369 clear 6 1700 northeast 0.17 2.43 6.09 98.15 8.97
370 clear 6 1700 northwest 0.17 7.20 8.93 94.02 10.44
371 clear 6 1700 southeast 0.17 0.99 4.56 100.00 6.73
372 clear 6 1700 southwest 0.17 -2.02 0.93 100.00 3.91
373 clear 9 900 northeast 0.26 21.32 24.87 29.17 27.99
374 clear 9 900 northwest 0.20 10.80 13.68 77.40 16.28
375 clear 9 900 southeast 0.21 14.74 18.95 57.01 21.60
376 clear 9 900 southwest 0.18 3.62 8.58 97.13 11.62
377 clear 9 1300 northeast 0.19 4.76 9.69 90.66 12.77
378 clear 9 1300 northwest 0.19 5.84 10.29 92.57 12.59
379 clear 9 1300 southeast 0.19 6.58 10.21 91.61 12.97
380 clear 9 1300 southwest 0.17 2.18 6.57 99.07 9.52
381 clear 9 1700 northeast 0.19 14.49 15.07 83.66 16.11
382 clear 9 1700 northwest 0.17 8.01 8.29 97.16 9.10
383 clear 9 1700 southeast 0.17 3.50 5.05 100.00 6.66
384 clear 9 1700 southwest 0.16 -4.19 -1.95 100.00 1.05
385 clear 12 900 northeast 0.24 20.38 24.00 45.56 25.97
386 clear 12 900 northwest 0.17 6.70 8.14 96.95 10.08
387 clear 12 900 southeast 0.20 14.32 18.78 74.58 20.43
388 clear 12 900 southwest 0.17 -0.02 3.62 100.00 6.59
389 clear 12 1300 northeast 0.18 8.07 9.99 94.92 12.74
390 clear 12 1300 northwest 0.17 5.57 7.03 98.02 8.50
391 clear 12 1300 southeast 0.17 4.97 7.17 98.11 9.18
123

Table 10: All Visual Comfort Metrics, Continued
392 clear 12 1300 southwest 0.17 1.29 5.59 100.00 8.27
393 clear 12 1700 northeast 0.17 12.12 11.97 94.64 12.86
394 clear 12 1700 northwest 0.17 4.34 4.12 100.00 4.88
395 clear 12 1700 southeast 0.17 1.35 2.18 100.00 3.70
396 clear 12 1700 southwest 0.16 -6.62 -5.20 100.00 -2.20
397 overcast 6 900 northeast 0.18 8.23 9.44 93.28 12.34
398 overcast 6 900 northwest 0.17 7.75 9.14 95.14 10.48
399 overcast 6 900 southeast 0.17 5.29 7.50 96.35 9.44
400 overcast 6 900 southwest 0.17 -0.70 2.73 100.00 5.71
401 overcast 6 1300 northeast 0.18 8.38 10.06 93.68 13.01
402 overcast 6 1300 northwest 0.18 7.21 9.39 94.23 10.81
403 overcast 6 1300 southeast 0.17 7.09 8.96 95.70 11.00
404 overcast 6 1300 southwest 0.17 0.03 3.70 100.00 6.69
405 overcast 6 1700 northeast 0.17 8.21 8.75 94.74 11.52
406 overcast 6 1700 northwest 0.17 6.19 7.26 97.38 8.33
407 overcast 6 1700 southeast 0.17 4.09 5.91 98.24 7.73
408 overcast 6 1700 southwest 0.17 -1.91 1.11 100.00 4.09
409 overcast 9 900 northeast 0.18 8.92 9.63 93.55 12.42
410 overcast 9 900 northwest 0.17 6.54 7.78 96.66 8.95
411 overcast 9 900 southeast 0.17 4.70 6.68 97.51 8.55
412 overcast 9 900 southwest 0.17 -1.44 1.74 100.00 4.72
413 overcast 9 1300 northeast 0.18 8.65 9.82 92.82 12.71
414 overcast 9 1300 northwest 0.17 6.77 8.62 95.96 9.96
415 overcast 9 1300 southeast 0.17 6.55 8.22 96.90 10.16
416 overcast 9 1300 southwest 0.17 -0.51 2.98 100.00 5.97
417 overcast 9 1700 northeast 0.17 5.40 5.43 98.65 8.17
418 overcast 9 1700 northwest 0.17 3.47 4.28 100.00 5.15
419 overcast 9 1700 southeast 0.17 3.28 3.88 100.00 5.61
420 overcast 9 1700 southwest 0.16 -3.83 -1.45 100.00 1.52
421 overcast 12 900 northeast 0.17 5.10 5.30 98.45 8.10
422 overcast 12 900 northwest 0.17 4.49 5.07 100.00 6.11
423 overcast 12 900 southeast 0.17 2.58 3.91 100.00 5.66
424 overcast 12 900 southwest 0.16 -3.42 -0.92 100.00 2.05
425 overcast 12 1300 northeast 0.17 5.33 6.31 97.81 9.19
426 overcast 12 1300 northwest 0.17 5.99 7.09 97.89 8.24
427 overcast 12 1300 southeast 0.17 5.12 6.37 98.23 8.25
428 overcast 12 1300 southwest 0.17 -1.85 1.18 100.00 4.17
429 overcast 12 1700 northeast 0.16 100.00
430 overcast 12 1700 northwest 0.16 100.00
431 overcast 12 1700 southeast 0.16 100.00
432 overcast 12 1700 southwest 0.16 100.00
433 clear 6 900 east 0.27 22.53 27.65 1.09 29.87
434 clear 6 900 north 0.20 11.61 16.24 56.11 19.15
435 clear 6 900 south 0.21 14.51 19.71 43.72 21.70
124

Table 10: All Visual Comfort Metrics, Continued
436 clear 6 900 west 0.17 1.81 3.70 100.00 6.91
437 clear 6 1300 east 0.26 22.64 28.18 3.05 27.98
438 clear 6 1300 north 0.18 8.97 12.79 90.18 15.71
439 clear 6 1300 south 0.21 13.75 18.86 62.97 20.33
440 clear 6 1300 west 0.17 7.83 9.61 94.34 12.61
441 clear 6 1700 east 0.26 21.84 27.16 5.38 26.64
442 clear 6 1700 north 0.17 7.89 11.37 90.64 14.31
443 clear 6 1700 south 0.19 13.14 17.83 71.33 19.28
444 clear 6 1700 west 0.17 6.82 8.29 97.61 11.14
445 clear 9 900 east 0.26 22.88 28.37 1.38 29.33
446 clear 9 900 north 0.21 11.65 16.44 59.90 19.28
447 clear 9 900 south 0.22 14.41 19.96 48.68 21.42
448 clear 9 900 west 0.17 0.92 2.48 100.00 5.68
449 clear 9 1300 east 0.26 22.20 27.60 10.43 27.24
450 clear 9 1300 north 0.18 8.50 12.18 87.18 15.09
451 clear 9 1300 south 0.20 13.22 18.20 67.69 19.68
452 clear 9 1300 west 0.17 6.92 8.47 96.49 11.49
453 clear 9 1700 east 0.25 20.63 25.52 10.35 24.75
454 clear 9 1700 north 0.17 6.69 9.77 95.21 12.70
455 clear 9 1700 south 0.18 11.40 15.84 83.27 17.39
456 clear 9 1700 west 0.17 4.05 4.84 100.00 7.72
457 clear 12 900 east 0.24 21.24 26.20 4.81 26.00
458 clear 12 900 north 0.18 9.34 13.33 81.45 16.13
459 clear 12 900 south 0.20 12.23 17.46 71.14 18.65
460 clear 12 900 west 0.17 -2.00 -1.19 100.00 2.02
461 clear 12 1300 east 0.25 21.31 26.37 6.68 25.77
462 clear 12 1300 north 0.17 7.61 10.98 91.63 13.89
463 clear 12 1300 south 0.19 12.25 16.97 76.47 18.39
464 clear 12 1300 west 0.17 5.71 6.92 98.64 9.89
465 clear 12 1700 east 0.20 17.82 21.71 31.36 20.66
466 clear 12 1700 north 0.17 4.05 6.25 100.00 9.14
467 clear 12 1700 south 0.17 7.59 11.88 96.77 13.42
468 clear 12 1700 west 0.16 -6.54 -7.68 100.00 -4.50
469 overcast 6 900 east 0.23 18.65 22.48 15.73 22.32
470 overcast 6 900 north 0.17 6.07 8.85 95.80 11.72
471 overcast 6 900 south 0.18 10.74 14.80 83.72 16.08
472 overcast 6 900 west 0.17 1.13 1.64 100.00 4.76
473 overcast 6 1300 east 0.23 19.36 23.45 11.49 23.39
474 overcast 6 1300 north 0.17 6.76 9.76 93.78 12.64
475 overcast 6 1300 south 0.18 11.02 15.47 80.72 16.86
476 overcast 6 1300 west 0.17 -0.84 -0.29 100.00 2.89
477 overcast 6 1700 east 0.22 17.51 20.97 24.90 20.59
478 overcast 6 1700 north 0.17 4.89 7.27 98.05 10.14
479 overcast 6 1700 south 0.17 9.28 13.13 90.97 14.40
125

Table 10: All Visual Comfort Metrics, Continued
480 overcast 6 1700 west 0.16 -2.46 -2.54 100.00 0.63
481 overcast 9 900 east 0.23 17.98 21.60 20.87 21.28
482 overcast 9 900 north 0.17 5.39 7.94 97.27 10.81
483 overcast 9 900 south 0.17 9.74 13.65 88.91 14.98
484 overcast 9 900 west 0.16 -0.57 -0.36 100.00 2.78
485 overcast 9 1300 east 0.23 18.77 22.65 14.98 22.53
486 overcast 9 1300 north 0.17 6.18 8.99 95.47 11.87
487 overcast 9 1300 south 0.18 10.51 14.70 84.31 16.07
488 overcast 9 1300 west 0.17 -0.48 -0.09 100.00 3.05
489 overcast 9 1700 east 0.18 15.61 18.43 44.45 17.85
490 overcast 9 1700 north 0.17 3.00 4.75 100.00 7.62
491 overcast 9 1700 south 0.17 7.32 10.41 96.85 11.72
492 overcast 9 1700 west 0.16 -3.94 -4.60 100.00 -1.47
493 overcast 12 900 east 0.19 16.02 18.99 39.97 18.46
494 overcast 12 900 north 0.17 3.34 5.19 100.00 8.07
495 overcast 12 900 south 0.17 7.67 10.98 96.03 12.29
496 overcast 12 900 west 0.16 -4.04 -4.58 100.00 -1.40
497 overcast 12 1300 east 0.22 17.51 20.96 24.79 20.59
498 overcast 12 1300 north 0.17 4.89 7.26 98.04 10.14
499 overcast 12 1300 south 0.17 9.30 13.07 90.95 14.36
500 overcast 12 1300 west 0.16 -0.24 -0.14 100.00 3.00
501 overcast 12 1700 east 0.16 100.00
502 overcast 12 1700 north 0.16 100.00
503 overcast 12 1700 south 0.16 100.00
504 overcast 12 1700 west 0.16 100.00
505 clear 6 900 east 0.19 5.25 10.69 92.15 13.58
506 clear 6 900 north 0.18 4.39 9.60 93.23 12.50
507 clear 6 900 south 0.18 5.39 10.75 91.54 13.56
508 clear 6 900 west 0.18 4.22 9.36 94.21 12.33
509 clear 6 1300 east 0.19 6.13 11.86 88.62 14.84
510 clear 6 1300 north 0.18 4.76 10.06 92.27 13.08
511 clear 6 1300 south 0.19 6.13 11.79 88.73 14.71
512 clear 6 1300 west 0.18 4.46 9.63 93.77 12.70
513 clear 6 1700 east 0.18 4.12 9.40 96.36 11.78
514 clear 6 1700 north 0.17 2.39 6.93 98.39 9.72
515 clear 6 1700 south 0.17 3.95 8.80 96.66 11.26
516 clear 6 1700 west 0.17 0.24 3.94 100.00 7.00
517 clear 9 900 east 0.18 4.45 9.65 94.92 12.38
518 clear 9 900 north 0.18 3.55 8.47 95.84 11.28
519 clear 9 900 south 0.18 4.67 9.70 94.10 12.37
520 clear 9 900 west 0.18 3.39 8.24 96.46 11.15
521 clear 9 1300 east 0.18 5.42 11.07 92.58 13.74
522 clear 9 1300 north 0.18 3.39 8.21 96.92 11.20
523 clear 9 1300 south 0.18 5.57 11.18 91.86 13.82
126

Table 10: All Visual Comfort Metrics, Continued
524 clear 9 1300 west 0.18 3.32 8.11 97.17 11.09
525 clear 9 1700 east 0.17 0.35 4.04 100.00 5.77
526 clear 9 1700 north 0.17 -1.33 2.07 100.00 4.55
527 clear 9 1700 south 0.17 0.20 2.49 100.00 4.81
528 clear 9 1700 west 0.16 -4.67 -2.60 100.00 0.33
529 clear 12 900 east 0.17 1.69 5.96 100.00 8.34
530 clear 12 900 north 0.17 -0.18 3.42 100.00 6.23
531 clear 12 900 south 0.17 2.12 6.39 98.86 8.70
532 clear 12 900 west 0.17 0.27 4.05 100.00 6.84
533 clear 12 1300 east 0.17 2.75 7.29 98.48 9.63
534 clear 12 1300 north 0.17 -2.53 0.32 100.00 3.38
535 clear 12 1300 south 0.17 4.16 9.46 96.91 11.54
536 clear 12 1300 west 0.17 1.93 6.36 98.98 9.09
537 clear 12 1700 east 0.16 -4.31 -2.19 100.00 -0.01
538 clear 12 1700 north 0.16 -5.97 -4.26 100.00 -1.65
539 clear 12 1700 south 0.16 -3.48 -1.96 100.00 0.19
540 clear 12 1700 west 0.16 -6.19 -4.57 100.00 -1.82
541 overcast 6 900 east 0.17 1.16 5.28 100.00 7.65
542 overcast 6 900 north 0.17 -0.08 3.60 100.00 6.25
543 overcast 6 900 south 0.17 1.32 5.33 100.00 7.65
544 overcast 6 900 west 0.17 -0.29 3.31 100.00 6.10
545 overcast 6 1300 east 0.17 1.88 6.17 98.97 8.58
546 overcast 6 1300 north 0.17 0.57 4.46 100.00 7.14
547 overcast 6 1300 south 0.17 2.09 6.25 98.85 8.61
548 overcast 6 1300 west 0.17 0.38 4.20 100.00 7.00
549 overcast 6 1700 east 0.17 -0.01 3.69 100.00 6.02
550 overcast 6 1700 north 0.17 -1.29 1.99 100.00 4.62
551 overcast 6 1700 south 0.17 -0.01 3.74 100.00 6.01
552 overcast 6 1700 west 0.17 -1.47 1.74 100.00 4.51
553 overcast 9 900 east 0.17 0.46 4.35 100.00 6.70
554 overcast 9 900 north 0.17 -0.79 2.65 100.00 5.29
555 overcast 9 900 south 0.17 0.58 4.41 100.00 6.70
556 overcast 9 900 west 0.17 -0.98 2.38 100.00 5.16
557 overcast 9 1300 east 0.17 1.34 5.46 100.00 7.84
558 overcast 9 1300 north 0.17 0.02 3.73 100.00 6.39
559 overcast 9 1300 south 0.17 1.77 5.56 99.13 7.89
560 overcast 9 1300 west 0.17 -0.17 3.46 100.00 6.25
561 overcast 9 1700 east 0.17 -1.90 1.23 100.00 3.50
562 overcast 9 1700 north 0.16 -3.15 -0.48 100.00 2.12
563 overcast 9 1700 south 0.17 -1.71 1.25 100.00 3.47
564 overcast 9 1700 west 0.16 -3.38 -0.81 100.00 1.94
565 overcast 12 900 east 0.17 -1.49 1.77 100.00 4.05
566 overcast 12 900 north 0.17 -2.73 0.07 100.00 2.67
567 overcast 12 900 south 0.17 -1.39 1.79 100.00 4.02
127

Table 10: All Visual Comfort Metrics, Continued
568 overcast 12 900 west 0.17 -2.95 -0.24 100.00 2.52
569 overcast 12 1300 east 0.17 0.01 3.72 100.00 6.05
570 overcast 12 1300 north 0.17 -1.25 2.04 100.00 4.67
571 overcast 12 1300 south 0.17 0.13 3.78 100.00 6.05
572 overcast 12 1300 west 0.17 -1.44 1.78 100.00 4.54
573 overcast 12 1700 east 0.16 100.00
574 overcast 12 1700 north 0.16 100.00
575 overcast 12 1700 south 0.16 100.00
576 overcast 12 1700 west 0.16 100.00
577 clear 6 900 northeast 0.25 16.23 18.46 53.49 22.46
578 clear 6 900 northwest 0.25 -4.17 -0.19 100.00 3.13
579 clear 6 900 southeast 0.23 14.29 16.52 61.54 20.29
580 clear 6 900 southwest 0.26 -6.09 -1.93 100.00 1.36
581 clear 6 1300 northeast 0.26 16.03 18.43 56.02 22.59
582 clear 6 1300 northwest 0.30 -0.64 4.06 98.68 7.80
583 clear 6 1300 southeast 0.25 11.41 13.73 73.65 17.89
584 clear 6 1300 southwest 0.32 6.11 11.10 73.74 16.10
585 clear 6 1700 northeast 0.22 3.46 8.34 94.32 11.95
586 clear 6 1700 northwest 0.27 7.74 13.21 64.59 17.84
587 clear 6 1700 southeast 0.22 4.17 9.04 92.54 12.69
588 clear 6 1700 southwest 0.27 8.15 13.57 59.48 18.20
589 clear 9 900 northeast 0.22 15.45 17.30 62.33 20.82
590 clear 9 900 northwest 0.23 2.17 5.47 98.49 8.79
591 clear 9 900 southeast 0.23 15.40 17.64 61.11 21.18
592 clear 9 900 southwest 0.24 -3.53 0.35 100.00 3.64
593 clear 9 1300 northeast 0.24 14.62 17.02 65.11 20.81
594 clear 9 1300 northwest 0.28 1.79 6.65 96.12 10.51
595 clear 9 1300 southeast 0.25 9.66 13.01 76.21 17.18
596 clear 9 1300 southwest 0.31 8.43 13.66 70.85 18.86
597 clear 9 1700 northeast 0.19 1.45 5.66 98.47 8.78
598 clear 9 1700 northwest 0.21 6.78 11.92 77.51 15.19
599 clear 9 1700 southeast 0.19 4.30 9.19 92.88 12.19
600 clear 9 1700 southwest 0.22 8.01 13.36 67.10 16.77
601 clear 12 900 northeast 0.19 13.15 14.13 78.96 16.89
602 clear 12 900 northwest 0.19 6.21 8.69 97.15 11.91
603 clear 12 900 southeast 0.20 15.69 17.61 68.73 20.14
604 clear 12 900 southwest 0.19 3.62 6.00 96.30 9.20
605 clear 12 1300 northeast 0.21 12.87 14.95 73.62 18.33
606 clear 12 1300 northwest 0.23 3.18 8.07 94.32 11.76
607 clear 12 1300 southeast 0.23 11.49 14.70 72.79 18.54
608 clear 12 1300 southwest 0.27 9.70 15.07 65.71 19.75
609 clear 12 1700 northeast 0.17 9.49 9.15 96.96 11.20
610 clear 12 1700 northwest 0.17 7.67 9.55 97.55 11.39
611 clear 12 1700 southeast 0.17 7.29 6.91 97.65 8.88
128

Table 10: All Visual Comfort Metrics, Continued
612 clear 12 1700 southwest 0.19 13.98 16.31 71.85 17.39
613 overcast 6 900 northeast 0.18 11.24 12.14 88.98 14.80
614 overcast 6 900 northwest 0.19 0.88 4.14 99.08 7.16
615 overcast 6 900 southeast 0.18 8.12 8.79 93.10 11.56
616 overcast 6 900 southwest 0.19 1.49 4.98 97.89 8.01
617 overcast 6 1300 northeast 0.19 11.84 12.97 86.06 15.78
618 overcast 6 1300 northwest 0.19 1.53 5.02 98.58 8.20
619 overcast 6 1300 southeast 0.18 8.79 9.68 90.83 12.56
620 overcast 6 1300 southwest 0.20 2.19 5.90 97.73 9.11
621 overcast 6 1700 northeast 0.18 10.00 10.52 93.68 13.00
622 overcast 6 1700 northwest 0.18 -0.32 2.55 100.00 5.37
623 overcast 6 1700 southeast 0.17 6.93 7.20 96.00 9.83
624 overcast 6 1700 southwest 0.18 0.32 3.42 100.00 6.22
625 overcast 9 900 northeast 0.18 10.51 11.19 92.59 13.74
626 overcast 9 900 northwest 0.18 0.16 3.19 100.00 6.09
627 overcast 9 900 southeast 0.18 7.47 7.89 94.92 10.57
628 overcast 9 900 southwest 0.18 0.81 4.06 98.66 6.95
629 overcast 9 1300 northeast 0.19 11.35 12.29 88.41 14.98
630 overcast 9 1300 northwest 0.19 0.99 4.29 100.00 7.34
631 overcast 9 1300 southeast 0.18 8.26 8.97 92.68 11.76
632 overcast 9 1300 southwest 0.19 1.63 5.15 98.40 8.22
633 overcast 9 1700 northeast 0.17 8.15 8.03 97.42 10.33
634 overcast 9 1700 northwest 0.17 -2.18 0.07 100.00 2.69
635 overcast 9 1700 southeast 0.17 5.01 4.65 98.56 7.13
636 overcast 9 1700 southwest 0.17 -1.55 0.92 100.00 3.50
637 overcast 12 900 northeast 0.17 8.63 8.64 96.72 10.96
638 overcast 12 900 northwest 0.17 -1.79 0.60 100.00 3.26
639 overcast 12 900 southeast 0.17 5.49 5.26 98.14 7.77
640 overcast 12 900 southwest 0.17 -1.16 1.44 100.00 4.06
641 overcast 12 1300 northeast 0.18 10.01 10.52 93.28 13.01
642 overcast 12 1300 northwest 0.18 -0.32 2.56 100.00 5.38
643 overcast 12 1300 southeast 0.17 6.99 7.26 95.93 9.88
644 overcast 12 1300 southwest 0.18 0.36 3.46 99.03 6.26
645 overcast 12 1700 northeast 0.16 -40.51 -48.02 100.00 -44.80
646 overcast 12 1700 northwest 0.16 -37.34 -45.29 100.00 -42.11
647 overcast 12 1700 southeast 0.16 -31.22 -38.65 100.00 -35.49
648 overcast 12 1700 southwest 0.16 -37.30 -44.51 100.00 -41.33
649 clear 6 900 east 0.17 9.31 12.03 91.23 13.61
650 clear 6 900 north 0.16 -3.90 -3.53 100.00 -0.47
651 clear 6 900 south 0.18 12.35 14.90 82.99 16.07
652 clear 6 900 west 0.17 4.97 4.59 100.00 7.20
653 clear 6 1300 east 0.17 4.33 5.58 100.00 7.52
654 clear 6 1300 north 0.16 -0.66 -0.09 100.00 2.64
655 clear 6 1300 south 0.17 10.07 10.28 96.28 11.33
129

Table 10: All Visual Comfort Metrics, Continued
656 clear 6 1300 west 0.17 12.19 12.61 91.56 12.29
657 clear 6 1700 east 0.17 3.22 3.89 100.00 5.77
658 clear 6 1700 north 0.16 -3.04 -3.18 100.00 -0.40
659 clear 6 1700 south 0.17 7.15 6.80 99.11 8.13
660 clear 6 1700 west 0.17 8.65 8.12 97.46 8.61
661 clear 9 900 east 0.17 9.02 11.64 95.42 13.30
662 clear 9 900 north 0.16 -0.62 0.17 100.00 3.16
663 clear 9 900 south 0.19 13.80 15.90 82.96 17.06
664 clear 9 900 west 0.17 11.87 11.69 92.38 13.53
665 clear 9 1300 east 0.17 3.27 4.15 100.00 6.31
666 clear 9 1300 north 0.16 0.15 0.97 100.00 3.62
667 clear 9 1300 south 0.17 9.72 9.75 96.85 11.04
668 clear 9 1300 west 0.17 12.19 12.72 87.61 13.37
669 clear 9 1700 east 0.16 1.60 1.87 100.00 3.65
670 clear 9 1700 north 0.16 -5.18 -6.04 100.00 -3.24
671 clear 9 1700 south 0.17 6.46 5.89 100.00 7.23
672 clear 9 1700 west 0.16 6.70 5.43 100.00 5.93
673 clear 12 900 east 0.17 7.63 9.83 93.69 11.45
674 clear 12 900 north 0.16 -7.87 -8.28 100.00 -5.14
675 clear 12 900 south 0.17 11.32 13.08 90.98 14.15
676 clear 12 900 west 0.17 3.73 2.70 100.00 5.50
677 clear 12 1300 east 0.17 1.93 2.50 100.00 4.82
678 clear 12 1300 north 0.16 -1.92 -1.69 100.00 1.12
679 clear 12 1300 south 0.17 8.40 8.53 97.58 10.23
680 clear 12 1300 west 0.17 10.83 10.72 94.21 11.20
681 clear 12 1700 east 0.16 -1.25 -1.99 100.00 -0.28
682 clear 12 1700 north 0.16 -10.67 -13.07 100.00 -10.13
683 clear 12 1700 south 0.16 1.68 0.53 100.00 2.01
684 clear 12 1700 west 0.16 3.13 0.78 100.00 1.55
685 overcast 6 900 east 0.16 2.75 3.25 100.00 5.15
686 overcast 6 900 north 0.16 -5.51 -6.23 100.00 -3.31
687 overcast 6 900 south 0.17 6.22 6.02 100.00 7.64
688 overcast 6 900 west 0.17 6.76 5.58 100.00 6.60
689 overcast 6 1300 east 0.17 4.01 5.01 100.00 6.70
690 overcast 6 1300 north 0.16 -5.29 -5.87 100.00 -2.92
691 overcast 6 1300 south 0.17 7.46 7.67 98.97 9.13
692 overcast 6 1300 west 0.17 7.62 6.77 99.06 7.83
693 overcast 6 1700 east 0.16 1.31 1.33 100.00 3.27
694 overcast 6 1700 north 0.16 -6.91 -8.10 100.00 -5.18
695 overcast 6 1700 south 0.17 5.08 4.18 100.00 5.88
696 overcast 6 1700 west 0.16 6.44 4.62 100.00 5.72
697 overcast 9 900 east 0.16 2.32 2.65 100.00 4.45
698 overcast 9 900 north 0.16 -6.16 -7.23 100.00 -4.32
699 overcast 9 900 south 0.17 5.77 5.26 100.00 6.84
130

Table 10: All Visual Comfort Metrics, Continued
700 overcast 9 900 west 0.16 5.99 4.68 100.00 5.82
701 overcast 9 1300 east 0.16 2.98 3.50 100.00 5.33
702 overcast 9 1300 north 0.16 -4.89 -5.58 100.00 -2.72
703 overcast 9 1300 south 0.17 6.34 6.25 100.00 7.79
704 overcast 9 1300 west 0.17 6.72 5.70 100.00 6.81
705 overcast 9 1700 east 0.16 0.17 -0.13 100.00 1.67
706 overcast 9 1700 north 0.16 -9.38 -11.24 100.00 -8.27
707 overcast 9 1700 south 0.16 3.14 2.14 100.00 3.84
708 overcast 9 1700 west 0.16 1.95 -0.96 100.00 0.71
709 overcast 12 900 east 0.16 0.02 -0.24 100.00 1.70
710 overcast 12 900 north 0.16 -9.15 -10.88 100.00 -7.88
711 overcast 12 900 south 0.16 2.90 2.24 100.00 4.00
712 overcast 12 900 west 0.16 1.73 -0.95 100.00 1.07
713 overcast 12 1300 east 0.16 1.41 1.64 100.00 3.52
714 overcast 12 1300 north 0.16 -7.07 -8.25 100.00 -5.31
715 overcast 12 1300 south 0.17 6.06 5.84 100.00 7.37
716 overcast 12 1300 west 0.16 5.59 3.70 100.00 4.85
717 overcast 12 1700 east 0.16 100.00
718 overcast 12 1700 north 0.16 100.00
719 overcast 12 1700 south 0.16 100.00
720 overcast 12 1700 west 0.16 100.00
721 clear 6 900 east 0.18 11.88 12.78 86.27 14.62
722 clear 6 900 north 0.19 11.55 12.78 82.68 14.92
723 clear 6 900 south 0.19 13.22 14.28 76.44 16.21
724 clear 6 900 west 0.18 9.61 10.95 90.96 13.47
725 clear 6 1300 east 0.18 12.39 13.43 83.36 15.54
726 clear 6 1300 north 0.19 12.06 13.53 78.96 15.95
727 clear 6 1300 south 0.19 13.95 15.26 70.91 17.40
728 clear 6 1300 west 0.19 10.26 11.84 88.03 14.58
729 clear 6 1700 east 0.17 10.08 10.41 93.50 12.06
730 clear 6 1700 north 0.18 9.95 10.72 90.53 12.46
731 clear 6 1700 south 0.18 11.72 12.32 86.24 13.89
732 clear 6 1700 west 0.18 11.88 12.78 86.27 14.62
733 clear 9 900 east 0.19 11.55 12.78 82.68 14.92
734 clear 9 900 north 0.19 13.22 14.28 76.44 16.21
735 clear 9 900 south 0.18 9.61 10.95 90.96 13.47
736 clear 9 900 west 0.18 12.39 13.43 83.36 15.54
737 clear 9 1300 east 0.19 12.06 13.53 78.96 15.95
738 clear 9 1300 north 0.19 13.95 15.26 70.91 17.40
739 clear 9 1300 south 0.19 10.26 11.84 88.03 14.58
740 clear 9 1300 west 0.17 10.08 10.41 93.50 12.06
741 clear 9 1700 east 0.18 9.95 10.72 90.53 12.46
742 clear 9 1700 north 0.18 11.72 12.32 86.24 13.89
743 clear 9 1700 south 0.17 8.33 9.19 95.19 11.40
131

Table 10: All Visual Comfort Metrics, Continued
744 clear 9 1700 west 0.18 10.86 11.35 91.16 12.98
745 clear 12 900 east 0.18 10.87 11.82 87.22 13.62
746 clear 12 900 north 0.18 12.29 13.13 82.79 14.80
747 clear 12 900 south 0.18 8.95 10.02 93.49 12.34
748 clear 12 900 west 0.18 11.58 12.36 88.07 14.41
749 clear 12 1300 east 0.18 11.29 12.65 83.87 14.82
750 clear 12 1300 north 0.19 13.34 14.43 75.82 16.35
751 clear 12 1300 south 0.18 9.68 11.05 90.70 13.60
752 clear 12 1300 west 0.17 6.11 5.15 100.00 6.68
753 clear 12 1700 east 0.17 6.86 6.73 98.13 7.96
754 clear 12 1700 north 0.17 8.68 8.36 96.67 9.51
755 clear 12 1700 south 0.17 5.46 5.26 99.11 7.10
756 clear 12 1700 west 0.17 7.57 7.12 98.15 8.65
757 overcast 6 900 east 0.17 7.79 7.93 96.62 9.37
758 overcast 6 900 north 0.17 9.56 9.56 95.04 10.87
759 overcast 6 900 south 0.17 6.25 6.39 98.43 8.37
760 overcast 6 900 west 0.17 10.05 10.37 93.54 11.98
761 overcast 6 1300 east 0.18 9.88 10.65 90.79 12.38
762 overcast 6 1300 north 0.18 11.73 12.33 86.19 13.88
763 overcast 6 1300 south 0.17 8.21 9.03 95.36 11.23
764 overcast 6 1300 west 0.16 -8.13 -10.85 100.00 -8.12
765 overcast 6 1700 east 0.16 1.67 0.25 100.00 1.02
766 overcast 6 1700 north 0.16 2.08 1.26 100.00 2.19
767 overcast 6 1700 south 0.16 0.27 -1.63 100.00 0.13
768 overcast 6 1700 west 0.16 0.76 0.62 100.00 2.75
769 overcast 9 900 east 0.17 7.39 7.75 97.24 8.72
770 overcast 9 900 north 0.17 8.05 8.77 96.43 9.86
771 overcast 9 900 south 0.17 5.94 5.92 98.77 7.80
772 overcast 9 900 west 0.16 -5.11 -6.30 100.00 -3.35
773 overcast 9 1300 east 0.17 8.25 8.95 95.50 9.73
774 overcast 9 1300 north 0.17 8.46 9.75 95.22 10.74
775 overcast 9 1300 south 0.17 6.59 6.77 98.20 8.69
776 overcast 9 1300 west 0.16 -3.48 -5.13 100.00 -2.30
777 overcast 9 1700 east 0.17 5.89 5.97 98.63 6.93
778 overcast 9 1700 north 0.17 7.67 7.44 97.71 8.54
779 overcast 9 1700 south 0.17 4.63 4.20 100.00 6.05
780 overcast 9 1700 west 0.16 -3.85 -4.74 100.00 -2.06
781 overcast 12 900 east 0.17 6.43 6.67 98.08 7.64
782 overcast 12 900 north 0.17 6.99 7.78 97.83 8.80
783 overcast 12 900 south 0.17 5.23 4.99 100.00 6.85
784 overcast 12 900 west 0.16 -3.14 -4.63 100.00 -1.81
785 overcast 12 1300 east 0.17 7.43 7.94 96.80 8.85
786 overcast 12 1300 north 0.17 7.63 8.67 96.63 9.84
787 overcast 12 1300 south 0.17 6.06 6.07 98.69 7.95
132

Table 10: All Visual Comfort Metrics, Continued
788 overcast 12 1300 west 0.16 -3.66 -4.73 100.00 -2.50
789 overcast 12 1700 east 0.17 3.98 3.29 100.00 4.28
790 overcast 12 1700 north 0.17 4.39 4.35 100.00 5.36
791 overcast 12 1700 south 0.17 2.62 1.53 100.00 3.33
792 overcast 12 1700 west 0.16 -10.07 -12.67 100.00 -9.58
793 clear 6 900 east 0.25 21.53 24.94 26.84 26.92
794 clear 6 900 north 0.20 13.13 17.14 76.03 19.04
795 clear 6 900 south 0.24 20.42 23.69 39.18 25.57
796 clear 6 900 west 0.19 12.36 15.64 78.06 17.65
797 clear 6 1300 east 0.26 21.93 25.50 21.67 28.34
798 clear 6 1300 north 0.21 13.96 18.28 68.94 20.66
799 clear 6 1300 south 0.24 20.50 23.61 30.17 25.98
800 clear 6 1300 west 0.20 12.70 16.27 71.01 18.77
801 clear 6 1700 east 0.32 24.78 29.91 8.25 33.56
802 clear 6 1700 north 0.22 13.58 16.68 70.05 20.14
803 clear 6 1700 south 0.24 19.78 22.78 38.60 24.86
804 clear 6 1700 west 0.19 12.34 14.45 78.84 17.21
805 clear 9 900 east 0.24 21.93 25.51 27.15 26.71
806 clear 9 900 north 0.19 12.83 16.62 80.65 17.96
807 clear 9 900 south 0.24 20.62 23.49 39.05 25.02
808 clear 9 900 west 0.19 11.41 14.99 84.15 16.71
809 clear 9 1300 east 0.26 22.30 25.96 21.01 28.30
810 clear 9 1300 north 0.21 14.17 18.47 70.95 20.34
811 clear 9 1300 south 0.24 20.09 23.34 35.27 25.53
812 clear 9 1300 west 0.20 13.07 16.16 77.83 18.35
813 clear 9 1700 east 0.31 26.57 32.71 5.77 33.91
814 clear 9 1700 north 0.23 19.54 23.92 52.09 24.86
815 clear 9 1700 south 0.21 16.27 18.67 58.24 21.37
816 clear 9 1700 west 0.26 23.29 26.28 31.84 27.66
817 clear 12 900 east 0.23 21.91 25.81 32.65 25.25
818 clear 12 900 north 0.18 11.82 15.58 89.22 15.96
819 clear 12 900 south 0.24 20.49 23.20 42.94 23.73
820 clear 12 900 west 0.18 10.95 13.44 92.36 14.48
821 clear 12 1300 east 0.25 22.57 26.39 25.95 27.51
822 clear 12 1300 north 0.20 13.95 18.51 76.50 19.45
823 clear 12 1300 south 0.24 21.06 23.85 35.68 25.34
824 clear 12 1300 west 0.19 12.27 16.01 78.44 17.51
825 clear 12 1700 east 0.26 24.08 31.42 12.17 27.60
826 clear 12 1700 north 0.22 13.72 23.23 77.82 21.26
827 clear 12 1700 south 0.19 16.91 18.82 75.71 19.48
828 clear 12 1700 west 0.17 7.10 8.77 98.76 10.35
829 overcast 6 900 east 0.24 22.42 26.61 28.47 26.08
830 overcast 6 900 north 0.19 12.14 16.34 87.95 16.91
831 overcast 6 900 south 0.24 19.69 22.16 53.85 22.84
133

Table 10: All Visual Comfort Metrics, Continued
832 overcast 6 900 west 0.18 9.80 12.15 93.67 13.42
833 overcast 6 1300 east 0.25 22.99 27.33 23.69 27.24
834 overcast 6 1300 north 0.19 12.69 16.99 84.67 17.81
835 overcast 6 1300 south 0.24 20.01 22.79 39.55 23.62
836 overcast 6 1300 west 0.18 10.31 12.83 92.06 14.26
837 overcast 6 1700 east 0.23 21.08 24.79 39.76 23.87
838 overcast 6 1700 north 0.18 10.78 14.46 93.17 14.96
839 overcast 6 1700 south 0.22 18.34 20.37 62.09 20.95
840 overcast 6 1700 west 0.17 8.40 10.34 97.08 11.51
841 overcast 9 900 east 0.23 21.64 25.53 34.94 24.80
842 overcast 9 900 north 0.19 11.39 15.32 91.17 15.81
843 overcast 9 900 south 0.23 18.94 21.18 56.35 21.80
844 overcast 9 900 west 0.17 9.04 11.15 96.12 12.40
845 overcast 9 1300 east 0.24 22.53 26.77 27.88 26.22
846 overcast 9 1300 north 0.19 12.24 16.46 87.54 17.00
847 overcast 9 1300 south 0.24 19.76 22.27 53.84 22.94
848 overcast 9 1300 west 0.18 9.89 12.22 94.12 13.48
849 overcast 9 1700 east 0.22 19.11 22.17 59.37 20.65
850 overcast 9 1700 north 0.17 8.85 11.89 97.57 12.10
851 overcast 9 1700 south 0.18 16.45 17.84 78.85 18.18
852 overcast 9 1700 west 0.17 6.05 7.83 99.12 8.92
853 overcast 12 900 east 0.22 19.68 22.92 53.89 21.50
854 overcast 12 900 north 0.17 9.42 12.61 96.63 12.86
855 overcast 12 900 south 0.19 16.71 18.40 71.96 18.80
856 overcast 12 900 west 0.17 6.97 8.47 98.61 9.51
857 overcast 12 1300 east 0.23 21.11 24.85 39.95 23.83
858 overcast 12 1300 north 0.18 10.85 14.57 93.13 14.96
859 overcast 12 1300 south 0.22 18.36 20.40 62.22 20.93
860 overcast 12 1300 west 0.17 8.47 10.41 96.79 11.54
861 overcast 12 1700 east 0.16 100.00
862 overcast 12 1700 north 0.16 -42.93 -48.82 100.00 -45.57
863 overcast 12 1700 south 0.16 -43.33 -49.88 100.00 -46.64
864 overcast 12 1700 west 0.16 -39.66 -45.36 100.00 -42.11
865 clear 6 900 east 0.25 21.64 26.20 15.51 27.51
866 clear 6 900 north 0.21 17.18 19.48 62.80 21.47
867 clear 6 900 south 0.21 17.07 19.48 60.75 21.37
868 clear 6 900 west 0.26 23.76 28.16 11.32 28.92
869 clear 6 1300 east 0.26 23.23 27.23 11.78 28.63
870 clear 6 1300 north 0.21 17.00 19.30 62.86 21.38
871 clear 6 1300 south 0.21 17.10 19.47 62.22 21.53
872 clear 6 1300 west 0.26 23.98 28.51 10.25 29.47
873 clear 6 1700 east 0.25 22.65 26.57 16.87 26.97
874 clear 6 1700 north 0.22 18.06 21.01 60.06 22.54
875 clear 6 1700 south 0.23 18.78 22.06 55.55 23.66
134

Table 10: All Visual Comfort Metrics, Continued
876 clear 6 1700 west 0.25 22.72 27.13 11.44 28.20
877 clear 9 900 east 0.27 22.75 27.44 6.53 29.52
878 clear 9 900 north 0.21 17.24 19.64 58.85 21.83
879 clear 9 900 south 0.22 17.94 20.94 51.04 22.91
880 clear 9 900 west 0.26 23.22 27.42 13.52 28.26
881 clear 9 1300 east 0.28 23.41 28.47 5.07 30.57
882 clear 9 1300 north 0.21 17.45 20.19 52.54 22.35
883 clear 9 1300 south 0.21 16.81 19.15 61.75 21.39
884 clear 9 1300 west 0.26 23.47 27.80 12.08 28.84
885 clear 9 1700 east 0.22 18.54 22.34 35.10 21.99
886 clear 9 1700 north 0.20 14.43 16.30 80.88 17.57
887 clear 9 1700 south 0.22 17.04 20.15 74.12 20.99
888 clear 9 1700 west 0.23 20.87 25.13 20.58 24.21
889 clear 12 900 east 0.25 22.50 26.07 20.97 27.60
890 clear 12 900 north 0.20 15.14 17.14 71.25 19.60
891 clear 12 900 south 0.21 18.13 20.09 55.19 22.33
892 clear 12 900 west 0.24 22.12 25.63 35.61 26.22
893 clear 12 1300 east 0.28 21.78 26.70 13.35 29.70
894 clear 12 1300 north 0.23 19.42 22.04 37.35 24.32
895 clear 12 1300 south 0.21 17.03 19.64 58.41 21.94
896 clear 12 1300 west 0.25 22.63 26.39 19.46 27.58
897 clear 12 1700 east 0.19 16.82 18.55 68.04 17.27
898 clear 12 1700 north 0.17 12.20 13.12 95.57 13.95
899 clear 12 1700 south 0.17 13.03 14.45 93.82 14.98
900 clear 12 1700 west 0.21 19.28 22.16 51.95 19.94
901 overcast 6 900 east 0.22 20.56 24.02 28.42 24.06
902 overcast 6 900 north 0.20 14.20 15.82 82.61 17.51
903 overcast 6 900 south 0.20 14.33 16.01 82.48 17.60
904 overcast 6 900 west 0.23 22.16 25.91 20.61 25.58
905 overcast 6 1300 east 0.23 21.15 24.80 23.84 25.09
906 overcast 6 1300 north 0.20 14.82 16.64 78.90 18.38
907 overcast 6 1300 south 0.20 14.67 16.74 77.06 18.48
908 overcast 6 1300 west 0.24 22.66 26.55 16.98 26.61
909 overcast 6 1700 east 0.21 19.19 22.20 41.18 21.69
910 overcast 6 1700 north 0.18 12.82 13.99 89.88 15.53
911 overcast 6 1700 south 0.18 12.91 14.12 89.77 15.60
912 overcast 6 1700 west 0.22 20.75 24.03 31.92 23.12
913 overcast 9 900 east 0.22 19.87 23.11 34.77 22.82
914 overcast 9 900 north 0.19 13.48 14.86 86.71 16.47
915 overcast 9 900 south 0.19 13.50 14.92 86.64 16.50
916 overcast 9 900 west 0.23 21.38 24.86 26.25 24.27
917 overcast 9 1300 east 0.22 20.54 23.99 28.72 24.00
918 overcast 9 1300 north 0.20 14.21 15.82 82.87 17.48
919 overcast 9 1300 south 0.20 14.14 15.78 82.85 17.44
135

Table 10: All Visual Comfort Metrics, Continued
920 overcast 9 1300 west 0.23 22.06 25.76 21.09 25.48
921 overcast 9 1700 east 0.20 17.01 19.30 62.89 18.24
922 overcast 9 1700 north 0.17 10.61 11.03 96.47 12.45
923 overcast 9 1700 south 0.17 10.62 11.08 96.48 12.48
924 overcast 9 1700 west 0.21 18.45 20.93 53.66 19.54
925 overcast 12 900 east 0.21 17.96 20.57 54.02 19.62
926 overcast 12 900 north 0.17 11.54 12.27 94.41 13.72
927 overcast 12 900 south 0.17 11.63 12.42 94.33 13.79
928 overcast 12 900 west 0.22 18.49 22.84 39.25 21.57
929 overcast 12 1300 east 0.21 19.14 22.13 41.68 21.60
930 overcast 12 1300 north 0.18 12.68 13.80 90.20 15.39
931 overcast 12 1300 south 0.18 12.77 13.95 90.03 15.47
932 overcast 12 1300 west 0.22 20.56 23.74 32.66 22.98
933 overcast 12 1700 east 0.16 100.00
934 overcast 12 1700 north 0.16 100.00
935 overcast 12 1700 south 0.16 100.00
936 overcast 12 1700 west 0.16 100.00
937 clear 6 900 east 0.24 20.65 23.69 24.72 24.95
938 clear 6 900 north 0.18 7.64 12.56 95.65 14.73
939 clear 6 900 south 0.17 7.20 11.19 97.55 13.49
940 clear 6 900 west 0.16 100.00
941 clear 6 1300 east 0.24 20.65 23.73 15.96 25.28
942 clear 6 1300 north 0.18 7.96 12.80 96.11 15.01
943 clear 6 1300 south 0.17 7.32 11.27 96.30 13.59
944 clear 6 1300 west 0.16 100.00
945 clear 6 1700 east 0.25 20.21 24.58 11.02 25.18
946 clear 6 1700 north 0.17 7.58 13.10 92.98 15.18
947 clear 6 1700 south 0.17 6.66 10.75 97.79 13.00
948 clear 6 1700 west 0.16 -26.48 -26.36 100.00 -23.11
949 clear 9 900 east 0.25 20.80 23.95 25.46 24.82
950 clear 9 900 north 0.17 7.65 12.95 97.01 15.05
951 clear 9 900 south 0.17 6.85 10.93 97.51 13.20
952 clear 9 900 west 0.16 100.00
953 clear 9 1300 east 0.25 20.17 24.34 27.41 25.60
954 clear 9 1300 north 0.18 7.74 12.71 97.18 14.98
955 clear 9 1300 south 0.17 7.27 11.33 97.52 13.64
956 clear 9 1300 west 0.16 100.00
957 clear 9 1700 east 0.24 19.72 24.48 17.30 23.78
958 clear 9 1700 north 0.17 6.49 12.55 96.43 14.11
959 clear 9 1700 south 0.17 5.93 10.53 100.00 12.48
960 clear 9 1700 west 0.16 100.00
961 clear 12 900 east 0.26 20.40 25.27 12.84 24.88
962 clear 12 900 north 0.17 7.18 13.37 94.62 15.00
963 clear 12 900 south 0.17 6.40 11.00 98.42 13.06
136

Table 10: All Visual Comfort Metrics, Continued
964 clear 12 900 west 0.16 100.00
965 clear 12 1300 east 0.26 20.79 25.45 9.21 25.86
966 clear 12 1300 north 0.17 7.69 13.41 92.62 15.45
967 clear 12 1300 south 0.17 7.43 12.03 97.73 14.18
968 clear 12 1300 west 0.16 100.00
969 clear 12 1700 east 0.19 17.99 23.21 36.97 20.89
970 clear 12 1700 north 0.17 4.39 10.86 100.00 11.82
971 clear 12 1700 south 0.17 4.07 9.17 100.00 10.56
972 clear 12 1700 west 0.16 -22.71 -24.53 100.00 -21.29
973 overcast 6 900 east 0.23 19.04 23.36 20.57 22.96
974 overcast 6 900 north 0.17 6.09 11.69 97.17 13.44
975 overcast 6 900 south 0.17 5.68 10.00 99.01 12.00
976 overcast 6 900 west 0.16 100.00
977 overcast 6 1300 east 0.25 19.62 24.11 16.07 23.84
978 overcast 6 1300 north 0.17 6.73 12.52 95.78 14.30
979 overcast 6 1300 south 0.17 6.22 10.71 98.56 12.78
980 overcast 6 1300 west 0.16 100.00
981 overcast 6 1700 east 0.21 17.76 21.64 32.15 21.15
982 overcast 6 1700 north 0.17 4.83 10.02 98.83 11.76
983 overcast 6 1700 south 0.17 4.16 7.92 100.00 9.92
984 overcast 6 1700 west 0.16 100.00
985 overcast 9 900 east 0.22 18.26 22.29 27.29 21.85
986 overcast 9 900 north 0.17 5.41 10.79 98.23 12.53
987 overcast 9 900 south 0.17 4.83 8.89 98.97 10.94
988 overcast 9 900 west 0.16 100.00
989 overcast 9 1300 east 0.24 19.12 23.48 19.98 23.06
990 overcast 9 1300 north 0.17 6.25 11.92 96.93 13.65
991 overcast 9 1300 south 0.17 5.65 10.00 99.01 12.00
992 overcast 9 1300 west 0.16 100.00
993 overcast 9 1700 east 0.18 15.73 18.93 54.49 18.33
994 overcast 9 1700 north 0.17 2.82 7.30 100.00 9.04
995 overcast 9 1700 south 0.17 2.20 5.27 100.00 7.32
996 overcast 9 1700 west 0.16 100.00
997 overcast 12 900 east 0.18 16.33 19.73 47.86 19.14
998 overcast 12 900 north 0.17 3.37 8.03 100.00 9.77
999 overcast 12 900 south 0.17 2.89 6.31 100.00 8.34
1000 overcast 12 900 west 0.16 100.00
1001 overcast 12 1300 east 0.21 17.70 21.55 32.75 21.05
1002 overcast 12 1300 north 0.17 4.80 9.95 98.85 11.70
1003 overcast 12 1300 south 0.17 4.21 8.05 100.00 10.10
1004 overcast 12 1300 west 0.16 100.00
1005 overcast 12 1700 east 0.16 100.00
1006 overcast 12 1700 north 0.16 100.00
1007 overcast 12 1700 south 0.16 100.00
1008 overcast 12 1700 west 0.16 100.00

Abstract (if available)

Abstract As annual daylight simulation methods become more prominent in the building design industry there exists a stronger need and a clearer path for daylight simulation programs to calculate annual visual comfort metrics. A single metric for predicting visual comfort for an entire space and for an entire year could be incredibly useful if one could be created. Though nascent and very time-intensive, capabilities for calculating annual glare probabilities for whole spaces currently exist. However, unlike daylight sufficiency metrics, there seems to be no clear, undisputed industry consensus when it comes to visual comfort metrics in daylight conditions, making annual glare capabilities slightly preemptive. Accordingly, this work aims to highlight some of the strengths and weaknesses of some of the leading visual comfort metrics (DGP, DGI, UGR, VCP and CGI) under annualized processes. Ultimately, this work outlines a luminance-based simulation process for predicting annual visual comfort and correlates these results with an existing dataset of field administered occupant surveys. The two metrics developed for this work, DGPmax and DGPave, are shown to have the high potential for metric candidacy.

Linked assets

University of Southern California Dissertations and Theses

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Asset Metadata

Creator Vicent, William A. (author)

Core Title Comparing visual comfort metrics for fourteen spaces using simulation-based luminance mapping

School School of Architecture

Degree Master of Building Science

Degree Program Building Science

Publication Date 06/20/2012

Defense Date 06/19/2012

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

Tag daylight,daylighting,glare,illuminance,luminance,luminance mapping,OAI-PMH Harvest,simulation,visual comfort

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Schiler, Marc (committee chair), Carlson, Anders (committee member), Heschong, Lisa (committee member), Kensek, Karen M. (committee member), Papamichael, Konstantinos (committee member)

Creator Email wavicent@gmail.com,william_vicent@yahoo.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c3-46676

Unique identifier UC11289430

Identifier usctheses-c3-46676 (legacy record id)

Legacy Identifier etd-VicentWill-893.pdf

Dmrecord 46676

Document Type Thesis

Rights Vicent, William A.

Type texts

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

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA