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Qualitative and quantitative natural light in atria and adjacent spaces

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Qualitative and quantitative natural light in atria and adjacent spaces

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Content QUALITATIVE AND QUANTITATIVE NATURAL LIGHT IN
ATRIA AND ADJACENT SPACES
by
Ibrahim M.I. Al-Turki
A Thesis Presented to the
FACULTY OF THE SCHOOL OF ARCHITECTURE
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF BUILDING SCIENCE
August 1994
Copyright 1994 Ibrahim M.I. Al-Turki
UMI Number: EP41436
All rights reserved
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UNIVERSITY OF SOUTHERN CALIFORNIA
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This thesis, written by
J O ///A ? / / . JO.
under the direction o f h & ......... Thesis Committee,
and approved by all its members, has been pre
sented to and accepted by the Dean o f The School
o f Architecture, in partial fulfillm ent of the require
ments for the degree o f
M A S T E R .
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Date . K/. 3-i S.. < 2 >J$ .
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3?9=?n. 83
ACKNOWLEDGMENT
There are too many people whom I want to thank (friends, classmates, family
members, and faculty members) for their participation and encouragement. However, I
would like to recognize the following people for their significant participation:
Professor Marc Schiler, a professor of University of Southern California and
my chief advisor, for his extreme and significant support, guidance, encouragement
and patience. I would like to thank him for sharing his experience and knowledge and
for entrusting his valuable books.
Professor Ralph L. Knowles, a professor of University of Southern California
for his useful comments on my thesis and for his support of my ideas to broaden my
thoughts.
Professor G. Goetz Shierle, a professor of University of Southern California
for his comments on the manuscript.
Professor Douglas Noble, a professor of University of Southern California for
his guidance and help on my thesis’s layout and manuscript.
Professor Murray Milne, a professor of University of California, Los
Angeles, School of Architecture, and his students for their cooperation and assistance
by lending all the necessary equipment for measurements.
Special thanks and dedication to every member of my family, who are behind
the scene, for their support. I would like to, specially, recognize my mother and
brother, Khalid, who always were there whenever I needed someone to talk to. You
are such a great family; I am proud of you.
God bless all of you.
II
TABLE OF CONTENT
I List of Figures vi
II List of Tables ix
HI Abstract xi
IV Introduction 1
1. Atria
1.1 Courtyards in Islamic Architecture 4
1.1.1 Water in Courtyards 8
1.1.2 Planting in Courtyards 10
1.1.3 Light in Courtyards 10
1.2 Courtyards in Contemporary Architecture 11
1.3 Atria and Energy Consumption 13
1.3.1 Cooling 15
1.3.2 Day lighting 16
1.3.3 Atria as Part of the Urban Design 18
References 19
2. Sunlight and Skylight
2.1 Astronomical Relationship Between the Sun and the Earth 20
2.2 Direct Normal Extraterrestrial Solar Radiation 24
2.3 Direct Normal Radiation 25
2.4 Direct Horizontal Illuminance 27
2.5 Direct Vertical Illuminance 27
2.6 Diffuse Illuminance 28
2.7 Net Illuminance 28
References 30
3. The Distribution of Sky Illuminance
3.1 Geographical Location of the Sun 32
3.1.1 Latitude 32
3.1.2 Longitude 32
3.2 Astronomical Location of the Sun 32
III
3.2.1 The Altitude Angle of an Object Above the Horizon 33
3.2.2 Solar Azimuth Angle 33
3.2.3 Solar Zenith Angle 34
3.3 Atmospheric Condition 34
3.3.1 Atmospheric Turbidity 34
3.3.2 Sky Condition 35
3.3.2.1 Clear Sky Condition 35
3.3.2.2 Partly Cloudy Sky Condition 36
3.3.2.3 Cloudy Sky Condition 36
3.3.2.4 Overcast Sky Condition 37
References 38
4. Methods of Measuring Daylight
4.1 Exterior Illumination Methods
4.1.1 Gillette Model 39
4.1.2 Dogniaux Model 40
4.1.3 IES Model 40
4.2 Interior Illumination Methods
4.2.1 Lumen Method 41
4.2.2 Daylight Factor Method 44
4.3 Physical Models
4.3.1 Objectives of Building Physical Models 48
4.3.2 Assessing the Purpose of Modeling Projects 49
4.3.3 Measuring the Results 51
4.3.4 Equipment Used for Measurements 53
4.3.4.1 Photometric Equipment 53
4.3.4.2 Computerized Multi-Sensor Systems 54
4.3.4.3 Video and Photography 54
4.3 Evaluating the Results 56
References 57
5. Measuring the Illuminance in Atria Using Physical Models
5.1 Description of Method 58
5.2 Devices Used for Testing 61
5.2.1 286 Compatible Computer 61
5.2.2 LI-210S Photometric Sensors 61
5.2.3 The Portable Analog Input Module 63
5.3 Measuring the Results 63
5.4 Analysis 66
References 77
IV
6. Validation of the “ LIGHTSUM” Program Using Physical Models
6.1 Background 78
6.2 Collecting Data 79
6.3 Analysis 80
6.4 Summary 85
References 96
7. Quantitative and Qualitative Illumination in Adjacent Spaces to Atria
7.1 Description of Methods 97
7.2 Measuring the Results 101
7.3 Analysis 102
7.4 Summary 103
8. Conclusions. 129
9. Future W ork. 136
Appendix A: Tables for calculating daylight using lumen method. 138
Appendix B: Tables for calculating daylight using daylight factor method. 143
Appendix C: TMY format. 145
Appendix D: Data collected from the physical model for an atrium. 147
Appendix E: Data collected from LIGHTSUM for an atrium. 151
Appendix F: Latitude and Longitude of world cities. 163
Appendix G: Glossary of abbreviations. 164
Bibliography 166
V
LIST O F FIGURES
Figure 1.1 The entry of Karaouyne of Fez. 5
Figure 1.2 The north pavilion of the generalife at Granada. 7
Figure 1.3 The Patio de los Arrayanes in the Alhambra. 9
Figure 1.4 Filtering the sunlight streams through screens. 11
Figure 1.5 The Andalusia, Los Angeles. 13
Figure 1.6 Court. 14
Figure 1.7 Atrium. 14
Figure 1.8 Lightcourt. 14
Figure 1.9 Litrium. 14
Figure 1.10 Lightwell. 14
Figure 2.1 The illumination level shifts over the surface of the earth. 21
Figure 2.2 The tilt of the axis of the earth away from the sun. 22
Figure 2.3 The altitude angle at noon for 40° N Latitude. 23
Figure 2.4 The effect of the atmosphere on the solar energy. 24
Figure 2.5 Successive process affecting the sunlight. 25
Figure 2.6 The visible spectrum. 26
Figure 3.1 The relationship among azimuth, altitude and zenith angles. 34
Figure 3.2 Clear sky daylight. 36
Figure 3.3 Overcast sky condition. 37
Figure 4.1 Lumen input method 41
Figure 4.2 Daylight factor method (Stein, 1986). 45
Figure 4.3 The mirror box for simulating overcast sky. 52
Figure 4.4 Fully cosine corrected meter. 53
Figure 4.5 Daylighting model data acquisition system. 55
Figure 5.1 Using a tripod to tilt the model in different orientations. 60
Figure 5.2 The physical model next to the computer unit used for testing. 63
Figure 5.3 The location of each reference point in the atrium. 65
Figure 5.4 The sundial diagram. 65
Figure 5.5 Reference point # 1 in the atrium. 69
Figure 5.6 Reference point # 2 in the atrium. 70
Figure 5.7 Reference point # 3 in the atrium. 71
Figure 5.8 Reference point # 4 in the atrium. 72
Figure 5.9 Reference point # 5 in the atrium. 73
Figure 5.10 Reference point # 6 in the atrium. 74
Figure 5.11 Reference point # 7 in the atrium. 75
Figure 5.12 The illumination inside the atrium at particular hours. 76
Figure 6.1 Reference point # 1 for IES, Gillette and physical model. 86
Figure 6.2 Reference point # 2 for IES, Gillette and physical model. 87
Figure 6.3 Reference point # 3 for IES, Gillette and physical model. 88
Figure 6.4 Reference point # 4 for IES, Gillette and physical model. 89
Figure 6.5 Reference point # 5 for IES, Gillette and physical model. 90
VII
Figure 6.6 Reference point # 6 for IES, Gillette and physical model. 91
Figure 6.7 Reference point # 7 for IES, Gillette and physical model. 92
Figure 6.8 June 21 at 9:00 for the IES, Gillette and physical model. 93
Figure 6.9 December 21 at 9:00 for the IES, Gillette and physical model. 94
Figure 6.10 December 21 at 12:00 for the IES, Gillette and physical model. 95
Figure 7.1 Modeling specular surfaces on the opposite walls. 99
Figure 7.2 Placing the light sensors inside the adjacent spaces to atria. 100
Figure 7.3 The first floor for the south facing wall in June 21 at noon. 104
Figure 7.4 The first floor for the north facing wall in June 21 at noon. 105
Figures 7.5-7.25 Graphing the^DF in the adjacent spaces. 108-128
Figure 8.1 Applying the DF on the building. 130
Figure 8.2 The building after it is formed upon the available light. 130
Figure 8.3 40% glazing area. 132
Figure 8.4 Protrated glazing area. 132
Figure 8.5 Using reflectors to improve the illumination level. 133
Figure 8.6 Daylight factor using the lumen method. 134
Figure 8.7 Daylight factor in the physical model. 134
Figure 9.1 Extending in east-west direction. 136
Figure 9.2 Extending north-south. 136
VIII
LIST OF TABLES:
Table 6.1 Data collected for January 21 from LIGHTSUM. 81
Table 6.2 Data collected for February 21 from LIGHTSUM. 81
Table 6.3 Data collected for March 21 from LIGHTSUM . 81
Table 6.4 Data collected for April 21 from LIGHTSUM . 82
Table 6.5 Data collected for May 21 from LIGHTSUM . 82
Table 6.6 Data collected for June 21 from LIGHTSUM. 82
Table 6.7 Data collected for July 21 from LIGHTSUM . 83
Table 6.8 Data collected for August 21 from LIGHTSUM. 83
Table 6.9 Data collected for September 21 from LIGHTSUM. 83
Table 6.10 Data collected for October21 from LIGHTSUM . 84
Table 6.11 Data collected for November 21 from LIGHTSUM. 84
Table 6.12 Data collected for December 21 from LIGHTSUM. 84
Table A. 1 Solar altitude and azimuth. 138
Table A.2 Illuminance for vertical surfaces. 139
Table A.3 Exterior Hrizontal Illumination. 140
Table A.4 Ground reflectance. 141
Table A.5 Light loss factor for dirt accumulation. 141
Table A.6 Coefficient of utilization ( C & K ). 142
Table B. 1 External illuminance available for percentage of workday. 143
Table B.2 Allowable room depth for minimum daylight factor. 144
IX
Table D. 1 Data collected from the physical model for Jan & Nov 21 147
Table D.2 Data collected from the physical model for Feb. & Oct. 21. 147
Table D.3 Data collected from the physical model for Mar. & Sep. 21. 148
Table D.4 Data collected from the physical model for Apr. & Aug. 21. 148
Table D.5 Data collected from the physical model for May & Jul 21. 149
Table D.6 Data collected from the physical model for June 21. 149
Table D.7 Data collected from the physical model for December 21. 150
Tables E.1-E.12 Data collected from LIGHTSUM. 151-162
X
ABSTRACT
This research studies natural light in atria and adjacent spaces for
qualitative and quantitative energy reducing opportunities using architectural
physical models. The study is directed to simulate and measure the available
illumination level in hot and sunny climates.
The study does the following:
1) Measure the available illumination level on the ground floor of an
atrium of 20’ x 20’ x 40’ using physical models.
2) Validate a computer program called “ LIGHTSUM” which calculates
the available light on the ground of an atrium using IES, Gillette,
and Dogniaux Models by creating a TMY weather file for a sunny
climate only, in order to simulate an atrium under the same
conditions as the physical models. The output from the physical
model is used for the validation.
3) Measure the available illumination level in the adjacent spaces to
an atrium of 20’ x 20’ x 40’ using physical models. The geometry
of the adjacent spaces is 20’ x 20’ x 10’.
The physical model tests do not validate LIGHTSUM. The fourth and
third floors in the adjacent spaces receive sufficient illumination level, but the
first and second floors do not.
XI
Introduction
The relationship between people, daylight, and architectural form is
intimate. Daylight introduces life, variation and drama into spaces. Throughout
the history of civilization, our buildings have articulated this relationship.
Daylight as a design variable can profoundly influence building orientation,
form, scale, the character and function of interior spaces, and the way that
interior spaces are perceived.
“ Architecture is the masterly correct and magnificent play o f masses
brought together in light. Our eyes are made to see forms in light; light and
shade reveal these forms; cubes, cones, spheres, cylinders or pyramids are the
great primary forms which light reveals to advantage. ” Le Corbusier.
Daylight is one of the most vital elements of our life-form. It has a
psychological impact on the human beings behavior especially when the amount
of light gets low in winter as the illumination level changes from a season to
another. There is a unique group of individuals who suffer from a recently
identified syndrome known as Seasonal Affective Disorder ( SAD).1 It is a
condition characterized by an annual depression with an onset during the winter
months which is caused because of the lack of light or the lack of the sunshine.
The earth receives its energy from the sun, the only source of light
energy, and that energy is important not only for humans, but for animals and
plants too. However, since the earth rotates around the sun and around its axis,
1
and tilts toward and away from the sun, each point on the surface of the earth is
accessed by the sun in different ways which is subject to change not only daily,
but seasonally.
Because light is received in a space in many different ways (diffused,
reflected, and direct) it is extremely important to control the amount of light
coming into a space. Low illumination level causes sadness and depression. On
the other hand, high illumination level can create uncomfortable and undesirable
space to live in; it causes what is called glare. The term “ discomfort glare”
refers to discomfort, as distinct from the reduction in visibility produced by a
distractingly bright source; it occurs even when disability is absent. Most
windows which give view of the sky produce some disability glare which can be
observed by shielding the sun with one’s hand. However, disability glare
describes the area of indistinct vision around a bright light. Therefore, it is
desirable to avoid the sun view.
Glare could be avoided by reflecting daylight in a space to increase the
room brightness, avoiding direct beam sunlight on critical visual tasks, allowing
daylight penetration high in a space, filtering daylight, increasing the perimeter
daylight zones.
“Extending the perimeter form o f a building may improve the building's
performance by increasing the total daylight space. Careful attention should be
2
given to these strategies in terms o f the thermal impacts o f turning o ff electric
lights due to available daylight and increasing footage o f window wall. ” 2
Courtyards are good examples of how to extend the perimeter daylight
zone of a building, especially in hot and sunny climates where the availability of
the sun is high. Courtyards resolve thermal problems in exterior walls; in
addition to their characteristics in cooling a space, they act like private spaces
isolated from the exterior noise. Since little research has been done on daylight
in atria, in general, and spaces adjacent to atria, and due to the importance and
usefulness of atria in hot and sunny climates, this research effort attempts to
cover this particular area.
REFERENCES:
1) Slocum, Y.S. Groundhogs,
Morning Glories, and Rhythm and Blues. International Daylighting
Conference, Long Beach, International Daylighting Organizing
Committe, 1986.
2) Southern California Edison.
Daylighting. Performance and Design Conference, Southern California
Edison, 1993.
3
1. ATRIA
In most hot-arid areas, atria are used as a cooling system to maintain a
comfortable climate in those sunny and hot conditions. However, there were
other major uses for atria in the past besides cooling. Courtyards provide a
private, protected space, symbolizing the inner life of the individual. In
addition, courtyards supply light to the rooms adjacent to them.
1.1. Courtyards in Islamic Architecture
Islamic courtyards have a very special charm and attraction of their own.
The core of Islamic Architecture was located in Arabia; several very early
mosques with courtyards still remain in the region, but largely were not existing
because of climate and terrain. Some Islamic gardens have survived better in
adjacent countries.6 Courtyards are contained within a building and, therefore,
an integral part of the architecture that forms them.
Fourteen centuries ago, at the start of Islam, the dwellings were roofed
with branches and earth, and supported by columns of palm trunks. Prayers
took place under this roof. Due to climate conditions, courtyards were built and
attached to the dwelling, and courtyards were used for prayers, as well. A basic
mosque plan, with a courtyard (sahn), surrounding colonnade and sheltered
audience, or prayer hall, facing Mecca was subsequently established and soon
spread through areas of Islamic influence in the Middle East and North Africa.6
4
Figure 1.1 The entry portal into the courtyard of the Karaouyne Mosque of Fez.6
According to the establishment of the courtyard pattern in mosques,
schools (Madrassa) were developed in Iran and North Africa. A school was
similar in plan to mosques by having a central courtyard, defined on all four
sides by a large portal (iwan), and was surrounded by rooms for students on one
or more floors (Figure 1.1).
On a larger scale, there were caravan hostels for merchants and their
goods, their servants and animals; these were often placed around a courtyard,
and an iwan similar to the iwan used in madrassa. Courtyards were placed away
from the main streets of bazaars to provide fresh air, sunlight and a little quiet
removed from the commercial activities.
Courtyards are usually square, or nearly so, and they symbolize
stability.6 As the concept of a place implies a space defined by a boundary, in
Islamic courtyards such a space is created by walls. The walls contain
accommodations, and these rooms derive their light, air and view from the
space enclosed.6 Courtyards were always related to gardens. In some hot
climates, courtyards were used to cool the air and to increase the humidity in
the air; therefore, water was used in forms of fountains or pools; in addition,
planting was used, as well, to filter the air and to provide shade to the space.
Some old cities are named as gardens because of the number of gardens, which
were surrounded by four walls defining a courtyard. The city of Riyadh, the
6
capital of Saudi Arabia, means “garden”; it implies that there were gardens in
the surrounding areas.
i«•.MZ/.Y4 V
Figure 1.2 The north pavilion of the Generalife at Granada.6
As the Islamic movement arrived in Spain in the early 8th century, the
influence of Islamic Architecture reached Spain. The similarity of climate
encouraged the similarity in forms and the importation into Spain from areas
like Iran and Syria. In Granada, the most charming courtyards and gardens
7
were built, as we see in the Alhambra and Generalife Granada, by the Moors,
but under the influence of the Islamic movement in that region (Figure 1.2).
The courtyards and gardens were determined by symbolism, climate,
topography, and the promotion of coolness, shade and privacy. The layout of a
courtyard was strictly geometric and defined by walls of masonry or hedge.
The influence of Islamic Architecture was not only in Spain, but in other
regions such as, Iran, Turkey, and India.
1.1.1. Water in Courtyards
Water was appreciated in many different ways, including by pools and
fountains. The pleasant noise of water was enjoyed when it gurgled through
runnels, or was broken up by a chute. The glossy surface of water provided a
textural contrast as well as a mirror to the varied trees or floors in a courtyard.
Pools which were found in the rich houses in Iran, were filled from
storage tanks or from open canals; pools were used frequently in mosques for
ablutions; sometimes, fountains were used for the same purpose in mosques.
Pools varied in size, from large sided pools to small basins, and they sometimes
contain fountains.
Fountains, which were used a great deal in Spain, portrayed animals. It
was popular throughout the Islamic world although images of animals was
generally prohibited in Islam. The most to be seen is in the Court of the Lions
8
at Alhambra (Figure 1.3). Most of the fountains had small basins to use little
water; the basin is often circular or star octagonal decorated with small pieces
of mosaic tilcwork.
Water was used to form a continuous link between indoors and
outdoors, and to form the scale of defined rooms of dwellings.
Figure 1.3 The Patio de los Arrayanes, in the Alhambra, Granada. The
long channel of water leads the eye to a cool colonnade on
the north side.6
9
1.1.2. Planting in Courtyards
Trees were used to cast their shadow over water, against walls and over
paths. Trees and flowers, which were highly regarded with the existence of
water, were regularly planted in rows, in large scale courtyards, and in the
center in small scale courtyards. In hot, dry climates, flowers were precious
since the blooming season was short. Different kind of colors and types were
carefully selected; the location of flowers was carefully chosen, as well. Good
examples were found in Isfahan, Spain, North Africa, India, and Turkey.
1.1.3. Light in Courtyards
Light is one of the important elements for any human-being besides air,
fire, water, and earth. It was one of the great consequences in Islamic
Architecture; light symbolized the “Absolute Being”6 as its illumination is the
source of all existence. It reveals and defines the environment in terms of shape,
brightness and color. The shape of a courtyard is affected by the amount of light
received, and it is regarded as a visible form built of various qualities of light.
Light played a significant aspect of shaping not only courtyards, but any object
with color and texture. It was contributed with the space as a relative aspect to
create and manipulate human comfort; it was controlled by designers to provide
10
sufficient light in the space. The quality and the intensity of light to the adjacent
spaces were greatly influenced by filtering the light screens (Figure 1.4).
Elements in courtyards, however, like wood, stone, marble, flowers,
leaves, grass, earth, and water, had their characteristic methods of distributing
light, reflecting or absorbing it.
Figure 1.4 Filtering the sunlight streams through screens.6
1.2. Courtyards in Contem porary Architecture
A courtyard is the center of any dwelling; it facilitates life out of doors
because it is sheltered from the wind, free from being examined by neighbors
and shut off from the public noise. Thus, the key quality of a courtyard house is
privacy.
11
The courtyard house is essentially an urban type of dwelling. The
interaction between dwelling, by sharing walls with neighboring houses, creates
an urban fabric with a clear separation between public and private areas. It is
noticed that courtyards could be part of the urban design of the city; cities are
composed of detached houses surrounded by gardens, the city is a block of
roads, and the town by its green belt. So, it was suggested that everyone should
have an enclosed open field within a few minutes.5
“ The courtyard house this century is quite different from the ancient
vernacular version. It has been built fo r a smaller family and fo r more
comfortable way o f life than those which existed in previous centuries. ” 7
There have been three main lines of the development of modem courtyard
houses. In Northern Europe, the mass courtyard housing was developed without
any old Mediterranean reference types; the modem atrium houses were based
on the Roman atrium houses; the patio houses in the United States imitated the
Spanish patio house during the Spanish Colonial Revival in southern California7
(Figure 1.5). The courtyard plan was developed to achieve privacy in the
garden, which is not available in most modem gardens, and to achieve a good
orientation of the rooms.
The courtyard plan works quite differently in hot and cold climates. In
hot-dry areas, exposure to the sun is to be avoided; therefore, small courtyards
were built and shaded by high walls. In addition, sharing the external walls with
12
the neighboring houses minimizes the exposure of vertical surfaces to the sun.
Dark colors were used to reduce glare; plants and fountains were used, as well,
to cool the air.7
10
Figure 1.5 The Andalusia, view of the central courtyard, Los Angeles.
On the other hand, in cold areas, courtyards are used to allow sunlight to
penetrate into the house by giving rooms large windows without any loss of
privacy. By contrast, the courtyard in cold areas needs to be wide and open
rather than deep and they are often covered in glass if they are smaller.
1.3. A tria and Energy Consumption
Not can only atria reduce the energy-cost in buildings, but courtyards,
litria, lightcourts and lightwells can do the same, where courtyards are outdoor
13
areas open to the sky and largely or completely surrounded by buildings or
walls. Lightcourts, on the other hand, behave like courtyards, but are designed
to optimize the daylighting in the enclosed buildings. The central room of a
building which is open to the sky at the center is called an atrium. A litrium,
however, is an atrium that designed is to optimize the sunlighting to the
adjacent spaces. A small vertical opening through one or more floors in a
building is called a lightwell; it is created for the primary purpose of
distributing natural light to adjacent spaces (Figure 1.6-1.10).
o
Illi
O
tllH
Figure 1.6 Court.4 Figure 1.7 Atrium.4 Figure 1.8 Lightcourt.4
Figure 1.9 Litrium.4 Figure 1.10 Lightwell.4
14
Nevertheless, the function of each space mentioned above is dependent
upon the use of the space itself and the use of the adjacent spaces. In the next
sub-chapters, we will discuss how atria can reduce the energy consumption if
they are used as cooling and delighting tools.
1.3.1. Cooling
An atrium needs to behave as a shading device and as a store of cooling
air, especially in a building which requires continuous protection against high
air temperature, high humidity, and strong sunshine. “ The majority o f atrium
buildings in warm and hot climates are, however, being built as a part o f
exclusive climate-control strategies, with air-conditioning. 1 2 The courtyards’
shape with their light-distribution function affect the building’s thermal
performance in many ways. These effects vary with the solar properties of the
glazing system and the type of the glazing devices used.8
The open-air courtyard of Islamic architecture behaves like a cooling
system by holding the supply of cool air gained from the previous night and
using it to cool the air during the day time when the diurnal temperature is high.
Therefore, the night air is collected in the deep recess of the courtyard and
cools the walls, slowing the rate of heat build-up the next day. When an
enclosed atrium performs like a supply or a return duct for the building, it saves
a great deal in construction costs.
15
1.3.2. Daylighting
In non-residential buildings, a high proportion of delivered energy goes
to provide artificial light. “The price trend fo r energy now suggests that
daylighting will often be more economic, though heat losses and gains through
the windows make it marginal. fJ2 But if these heat problems are solved,
daylighting has a lot to offer.
Atria are considered to be light-admitting design elements of buildings.
They provide ambient light to the spaces and transfer the reflected light to the
adjacent spaces. The lighting requirement for atria depends on the consideration
of the spaces used.8 To maximize the daylighting performance in a multi-story
building, an atrium is one of the best strategies to use. In all climates, an atrium
can be used for daylighting, and can serve more building area than other
common types of daylighting strategies in large buildings.1
Atria can be one of the strongest contributions in energy conservation by
re-establishing daylight access. Nowadays, the cost of artificial lighting is
higher than the cost of daylight; however, the energy cost of daylight lies in the
low insulation and shading value of glass, causing heat gain. “Good daylighting
means lighting o f the right quality, delivered to the greatest plan-depth possible.
Quality rather quantity counts; low glare and contrast are most desirable. ”1 2
In sunny climates, daylighting is difficult to achieve successfully with
direct light. Sunlight must be either excluded by shades or converted to diffuse
16
light. In very hot-arid climates, only a small amount of light transmission is
needed to provide adequate daylight levels; therefore, most sun must be
excluded and that which is admitted must be converted to diffuse light. The
further you are from the window, the more the light levels within a room fall
off; therefore, collecting light devices could be used to direct light into the
spaces adjacent to an atrium. Devices like light shelves should be carefully
used, and their materials and shapes should provide significant daylight
performance in order to get a full benefit of the natural lighting which will not
be gained unless it is integrated with the artificial lighting and the internal
finishes of the occupied spaces, as well.
There are some strategies and design decisions regarding the distribution
of light within an atrium. The first thing that should be considered is the aspect
ratio between the atrium’s width, length and depth, which will govern the rate
of decay of light levels in the court. However, the reflectance of the materials
of the walls inside the court also has a great impact on the level of light in the
court. Another design issue is the area of the fenestration for each floor which
should differ from upper levels to bottom levels; meanwhile, the glass type
could be varied. In atrium buildings, daylight entering a room may be on its
second or third diffuse reflection from surfaces inside the atrium. Computer
programs, like DOE2, may emerge to model this complex behavior, but at
17
present, the best method is the use of physical models. Simulating physical
models will be discussed in details in 5.2.
1.3.3. Atria as Part of the Urban Design
In addition to its advantages for daylighting and cooling, an atrium can
be a place of arrival in a building; it is the point of orientation around which the
occupied spaces are grouped, and the natural location for pedestrian and
mechanical circulation systems.1 2 This kind of planning in buildings can create
buildings which are more comprehensible to users and visitors because on
arrival, you can see the various parts of the building and how to get to them.
Moreover, inside the building, you can tell where you are if the secondary
circulation routes give view into the atrium.
An atrium could be part of the urban planning of the city, as well, by
determining the relationship between the public circulation and the private
purpose of the building. “ Apart from efficient land use and the incorporation o f
akward sites, atrium buildings are major elements in urban design in that they
add to the pedestrian space o f the city. They can be routes and destinations,
truly urban spaces. As routes, they can provide mid-block passages and cut-offs,
reviviving the intricacy o f the older city. They can also allow and stimulate the
development o f pedestrian routes above or below street level.1 2
18
REFERENCES:
1) Kim K.S. & Boyer L.L.
Development o f Daylighting Prediction Methods for Atrium Building.
International Daylighting Conference, Long Beach, International
Daylighting Organizing Committee, 1986.
2) Knowles, Ralph L.
Energy and Form . Cambridge, Massachusetts, MIT Press, 1974.
3) Kuran, Aptulah.
The Mosque in Early Ottman Architecture. London, The University of
Chicago Press, 1968.
4) Lam Williams.
Sunlighting as Form giver for Architecture. New York, Van Nostrand
Reinhold Company Inc., 1986.
5) Lees, Al.
Earth -Sheltered Atrium. Popular Science, V221 (Sep. 1982):pl 16.
6) Leharman, Jonas.
Earthly Paradise. England, Thames and Hudson, 1980.
7) Macintosh, Duncan.
The Modern Courtyard House. London, Lund Humphries Publishers limited,
1973.
8) M. Nawab & V.Bazjanac.
Daylight Design for Atria. International Daylighting Conference, Long
Beach, International Daylighting Organizing Committee, 1986.
9) NBS Building Science series 152.
A Daylight Model for Building Energy Simulation. U.S. Department of
Commerce, National Bureau of Standards, 1983.
10) Polyzoides, Stephanos.
Courtyards Housing in Los Angeles. Berkeley, University of California
Press, 1982.
11) Richard, J.M.
Hassan Fathy. England, Concept Media, 1985.
12) Saxon Richard.
Atrium Building. 2nd Edition, New York, Van Nostrand Reinhold Company.
19
2. SUNLIGHT AND SKYLIGHT
2.1. Astronomical Relationship Between the Sun and Earth
The sun, which has a radius of 4.32 x 105 miles (three times as much as
the radius of the earth) is a hydrogen-fusion, nuclear furance that is powered by
shear gravitational crush. This fuel gets consumed and converted to light energy
and it is radiated away from the sun in all directions. During the travel of light
from the sun, which is one hundred times the size of the earth1 ,to earth which
takes only eight minutes to travel 93 million miles, the projected area of earth to
the sun intercepts only 5 billionths (5 x 10~9 ) of the radiated energy from the
sun1. However, that amount of solar energy brings an amazing annual total of
1 8 1
10 kilowatt hours which is more than 99 % of the available energy on earth .
The energy produced by the sun is in the form of electromagnetic
radiation. “ These rays form a continuous spectrum reaching from electric
waves more than 3000 kilometers long through radio waves, microwaves,
infrared rays, visible light, ultraviolet rays, x-rays and even the high frequency
gamma rays to and including cosmic photons. 'a The radiation arrives on earth
is visible light, although the range includes both infrared and ultraviolet which
are not visible to the human eye, but play a great factor in the human well
being.1
20
However, the earth does move, it is a sphere and it has an atmosphere;
therefore, there is a wide range of flux on the surface of the earth. The earth
moves in three distinct motions: it moves around the sun, it moves toward and
away from the sun and it spins on its axis (Figure 2.1).
Figure 2.1 The illumination level shifts over the surface of the earth.5
Twice a year, at the equinoxes (March 21 and September 21), the axis of
the earth is perpendicular on the earth’s orbital and parallel to the axis of the
sun. At this time of the year, there are equal hours of day and night over the
entire globe. As the earth moves toward the winter and summer solstice, the
earth of day and night increase and decrease respectively. Days get shorter and
nights get longer in the northern hemisphere as we approach December 21
solstice; the opposite occurs in the southern hemisphere. The further north we
21
approach (66.5° N Latitude or more), we have 24 hour night; all points further
south than 66.5° S Latitude have 24 hour day because the south pole is tilted its
maximum of 23.5° toward the sun (Figure 2.2).
fLAJ4$>
* ^
Figure 2.2 The tilt of the axis of the earth away from the sun.5
The position of the sun in the sky at noon, changes upon the change of
the season; however, it changes for all other hours, but noon is considered as
the reference angle (Figure 2.3).
Although the earth travels around the sun in almost a perfect circle, it is
closest to the sun in January 1 and farthest away from the sun in July 1 with a
difference of 3 million miles between the two extremes; that is because the sun
is not the center of the circle which the earth travels around the sun. Therefore,
22
the solar energy which reaches the earth in January is stronger than in July by
almost 7 %.
JUN& Zl z i
(9 0 -4 0 )+ ZV=>*
( 9 0 - 4 0 ) '
« pO®
(90-40) -zv?°
Figure 2.3 The altitude angle at noon for 40° N Latitude.5
The length of day varies a great deal as the latitude increases or
decreases and when the axis inclines towards or away from the sun; the factors
are the spherical shape of the earth, the tilt toward and away from the sun, and
because the earth’s orbit around the sun and its spin around its own axis.
The atmosphere of the earth is a major factor in reducing the solar
energy arriving at the ground. The solar energy reaching the ground is defined
by two major mechanisms: direct and diffuse radiation. The largest portion of
the solar energy is reflected into outer space by either the atmosphere, the top
of the clouds or both. Part of the energy is absorbed by the ozone layer of the
23
earth which contains ozone, oxygen, carbon dioxide and water vapor. Another
part of the energy gets scattered in all directions by dust particles, pollutants
and water droplets, which are minor constituents of the atmosphere (Figure
2.4).
Figure 2.4 The effect of the atmosphere on the solar energy.5
2.2. Direct Normal E xtraterrestrial Solar Radiation
The extraterrestrial solar radiation is the total illuminance measured on a
flat surface perpendicular to the sun’s rays before it penetrates the atmosphere
24
of the earth. The measurement is different not only from one day to another,
but from hour to another, and that because of the variant distance between the
sun and the earth which is caused by the tilt of the earth ( Figure 2.5).
The illuminance of the extraterrestial solar radiation is measured in
KJ/m2 s, which equals to 0.088 Btu/ft2 s.
A Extra terrestrial sunlight
B After ozone absorption
C After molecular scattering
D After aerosol scattering
E After water and oxygen
absorptions: terrestrial sunlight
£
£
•S
-c
I
i
c
o
8
C
.O
|
< k
10 02 OS
Wavelength I pm )
Figure 2.5 Successive process affecting the sunlight during penetration of the
atmosphere.1
2.3. Direct Normal Solar Radiation
The direct normal radiation is the light measured on a flat surface
perpendicular to the sun’s ray at the ground level after the sun’s rays penetrate
the atmosphere of the earth. Because most of the light is absorbed by the earth’s
25
atmosphere and scattered by molecules and dust particles before it reaches the
ground, the value of the direct normal radiation is always less than the value of
the extraterrestrial solar radiation, and it could be simply calculated by
multiplying the extraterrestial radiation by an atmospheric extinction coefficient
calculated from turbidity and moisture.
Light is defined as part of the electromagnitic radiation spectrum that
can be preceived by the human eye. This ranges from the blue light through
green, yellow, and orange light to red light and into violet.
Next we will discuss only the illumination within that range which can
be seen by the human eye. This is a subset of the spectrum, as shown in figure
2.6. Notably absent from this new measurement is the energy in the infrared
portion of the spectrum. Radiation is measured in Btu/ft2 s, and illumination is
measured in footcandles.
The intensity in the direction a angle results in two vector components
and two vector quantities: the illumination on a horizontal surface designated
Edh , and that on a vertical surface ED V .
Ultraviolet Radio Microwave Infrared X-rays
Cosmic
rays
Power Television
Gamma
Visible
spectrum
Red Green. Blue uv-c
1000 nm 900 800 700 500 600 400 300 200 nm
Figure 2.6 The visible spectrum.6
26
2.4. Direct Horizontal Illuminance
The direct horizontal solar illuminance is the direct sunlight measured on
a flat horizontal plane on the ground of the earth. It is measured by multiplying
the direct normal illuminance by the SIN of the solar altitude angle. It is
expressed by the equation:
Edh = EDNsina where:
ED h — direct horizontal solar illuminance
Edn ~ direct normal solar illuminance
a = solar altitude angle
2.5. Direct Vertical Illuminance
The direct vertical illuminance is the direct sunlight measured on a flat
vertical plane. It is measured by multiplying the direct normal illuminance by
the cosine of the incident angle . It is expressed by the equation:
Edv = Edn cosa where:
Edv = direct vertical illuminance
Edn = direct normal illuminance
a = incident angle
27
2.6. Diffuse Illuminance
The diffuse illuminance is composed of diffuse solar illuminance and
diffuse sky illuminance. It is measured on a flat horizontal surface when there
is no direct sunlight; such as, a cloudy sky condition or an overcast condition.
By defining the direct normal solar illuminance, the net illuminance and the
incident angle, the diffuse illuminance is calculated from the following
equation:
ED h = En et / Edn cosa where:
ED h = diffuse illuminance
En e t = net illuminance
Edn = direct normal solar illuminance
a = incident angle
Diffuse illumination could be measured practically, as well, under clear
sky condition by covering the measuring device from the direct beams of the
sun with a piece of paper, about four feet from the light sensor in order to
cover just the sun, but not much of the sky.
2.7. Net Illuminance
Net illuminance is the component of both the direct normal illuminance,
which is measured directly from the direct sunlight beams, and the diffuse
illuminance, which is the illumination from the sky dome.
28
Net radiation is expressed by the equation:
En et = Edh + Edn cosa where:
En et = net illuminance
^dh = diffuse illuminance
ED n — direct normal illuminance
a = incident angle
Net radiation could be measured by placing a light sensor on a flat
surface on the ground in a clear sky condition; the taken reading is the net
radiation.
29
REFERENCES:
1) Erhardt, Louis.
Radiation. Light & Illumination. California, Camarillo Reproduction
Center.
2) Henderson, S.T.
Daylight and its Spectrum. New York, Elsevier Publishing Company
LTD, 1970.
3) Lam, William M.C.
Sunlighting as formgiver for Architecture. New York, Van Nostrand
Reinhold Company, 1986.
4) Lynes, J.A.
Principles o f Natural Lighting. London, Elsevier Publishing Company
LTD, 1968.
5) Michels, Tim.
Solar Enemy Utilization. New York, Van Nostrand Reinhold Company,
1979.
6) Schiler, Marc.
Simplified Design o f Building LiQhtinQ. New York, John Wiley & Sons,
1992.
7) Walsh, John.
The Science o f Daylight. London, Macdonald, 1961.
30
3. The Distribution of Sky Illuminance
To understand the available amount of daylight on a particular site, it is
important to understand some factors which play an important rule in
calculating the behavior of daylight. It was discussed in chapter 2, the daylight
is the light energy which arrives from the sun. This light travels in space and in
the atmosphere of the earth in the form of waves until it reaches the earth’s
ground. The measurement of light when it arrives at the ground depends upon
different variables.
There are, however, three variables which affect the amount of light in a
particular site and in a particular time; they are the geographical location of the
site, the astronomical location of the sun to the earth, and the atmospherical
condition of the sky at that particular time.
Geographical location of the site includes the latitude and the longitude
of the site which are always fixed for that particular site. Solar altitude angle
and solar azimuth angle describe the astronomical location of the sun to the
earth. Although these factors vary with time, day and season, they are
predictable. There are some factors which are hard to predict like the
atmospheric condition of the sky because there are too many variables at once.
Variables like turbidity, moisture, and sky clearness affect the amount of
daylight reaching the site after traveling through the atmosphere.
31
3.1 Geographical Location of the Site
3.1.1 Latitude
Latitude is the angular distance from the equator along the meridian,
north or south, to a point on the earth’s surface, in degrees.5 The north and the
south poles are +90 and -90 degrees respectively, where the latitude of the
equator is zero. It is extremely important to know the latitude of a point on the
surface of the earth to measure the Illuminance level and its relationship with
the sun ( Appendix F).
3.1.2 Longitude
Longitude is the angular distance from the meridian (which runs through
Greenwich, England) west or east of the earth’s surface. West of the prime
meridian has positive numbers and east of the prime meridian has negative
numbers (Appendix F).
See appendix B for different latitudes and longitudes of some cities in the
world.1
3.2 Astronomical Location of the Sun
Although the astronomical location of the sun changes from one time
and season to another, it is, however, predictable. As it was discussed in section
32
2.2, the noon altitude angle of the sun decreases as we approach December 21,
which has the lowest angle; it, however, increases as we approach June 21,
which has the highest sun angle. At the same time, equinox (March 21 and
September 21) makes the absolute midpoint value between the previous two
solstices (Figure 3.1).
3.2.1 The Altitude Angle of an Object Above the Horizon
The altitude angle of an object above the horizons is the angular distance
of a heavenly body measured on that great circle which passes perpendicular to
the plane of the horizon through the body and through the zenith. It is measured
positively from the horizon to the zenith, from zero to 90 degrees.4 It could be
simply explained, as well, as the angle that measures the height of the sun up
from the horizon7 (Figure 3.1).
3.2.2 Solar Azimuth Angle
The solar azimuth angle is the angular distance between the vertical plan
of the sun and the plane of the meridian.4 It is the angle that measures the
compass orientation of the sun. The sign conversion of the angle is positive east
of south and negative west of south7 (Figure 3.1).
Zenitl
Figure 3.1 The relationship among the azimuth, the altitude and the zenith angles in a
site.5
3. 2.3 Solar Zenith Angle
The solar zenith angle is the complementary angle to the altitude angle.
Altitude angle + Zenith angle = 90° ( Figure 3.1).
3.3 Atmospheric Condition
3.3.1 Atmospheric Turbidity
When measuring the available Illuminance for a given solar elevation,
the amount of light depends upon the variable amount of dust, smog, haze and
water vapor in the atmosphere. The extinction produced by the above mentioned
components is called the atmospheric turbidity; it is used as a variable in
calculating the illumination level at a particular time of the year when using
Dogniaux Prediction Model. The turbidity and moisture in the air are counted
34
separately;5 however, they are treated as one variable when using Gillette
Prediction Model, discussed in the next chapter.
3.3.2 Sky Condition
The sky condition varies not only every day, but, sometimes, every hour
of the day; therefore, the sky condition is a major factor in determining the
illumination level at a certain point on the ground level. The sky condition,
which describes the amount of cloud in the sky, could be explained in two
methods: the sky cover, which is used by the National Oceanic and
Atmospheric Administration (NOAA)2, and the sky ratio, which is used by the
National Bureau of Standards (NBS). Cloud cover is estimated in tenth and
ranges from zero, for no clouds, to 10, for a completely covered sky; on the
other hand, the sky ratio is the ratio of horizontal sky irradiance to global
horizontal irradiance. Both methods will give similar results in daylight
calculation.
3.3.2.1 Clear Sky Condition
Sky light is a diffuse light resulting from the refraction and reflection of
the direct sunlight beams as they pass through a comparatively clear and dry
sky.8 A clear sky is one which has less than 30 per cent cloud cover.3
35
afegM M aasa& atsasi
Figure 3.2 Clear sky daylight.
3.3.2.2 Partly Cloudy Sky Condition
A partly cloudy sky condition occurs when a portion of the sky is
covered by clouds. It is one which has 30 - 70 per cent cloud cover;4 that makes
measuring daylight illumination unpredictable.
3.3.2.3 Cloudy Sky Condition
A cloudy sky condition occurs when a large part of the sky is cover by
sky. It is the one which has more than 70 per cent cloud cover.4
36
3.3.2.4 Overcast Sky Condition
An overcast sky condition is caused by large water particles diffusely
reflecting all wavelengths of sunlight equally in all directions; this results in a
white-colored sky. It is the one which has 100 per cent cloud cover where the
sun is not visible.4
>V S j |
v#
CLOUD COVER
£
Figure 3.3 Overcast sky condition.
37
REFERENCES:
1) The ALMANAC.
45th ED, 1992. Boston, Houghton Mifflin Company.
2) IES, RP-5.
Recommended Practice for the Calculation o f Davlighting. IESNA,
1978.
3) IES, RP-21.
Calculation ofDavlioht Availability. IESNA, 1983.
4) Kaufman, John, editor.
IES lighting Handbook. 4th ed. New York, Illumination Engineering
Society, 1964.
5) Liang, June.
Computer Modeling o f Cumulative Daylight Availability With an Urban
Site. Los Angeles, University of Southern California, 1993.
6) Lynes, J.A.
Principles o f Natural Lighting. London, Elsevier Publishing Company
LTD, 1968.
7) Schiler, Marc.
Simplified Design o f Building Lighting. New York, John Wiley & Sons,
1992.
8) Schiler, Marc, editor.
Simulating Day lighting With Architectural Models. Daylighting Network
of North America (DNNA).
9) Walsh, John W .t.
The Science o f Davlieht. London, Macdonald, 1961.
38
4. Methods of Measuring Daylight
Several methods have been established to measure the available
illumination level measured on a horizontal surface inside a building, which is
called a workplane. The function of the space, however, defines the height of
the workplane which is measured from the ground level of a space.
4.1 Exterior IHumination Methods
The first step in calculating the daylight availability in a certain site is to
determine the available total horizontal illumination of the site if there is no
obstruction in the surroundings of the site. The illumination level is called the
exterior illumination which consists the direct sunlight and diffuse light.
4.1.1 Gillette Model
The Gillette Model was developed at the National Bureau of Standard in
1983, with the support from the U.S. Department of Energy and the Nationsal
Fenestration Council.7 The principle parameters are:
1. Solar lacation ( altitude, azimuth, time)
2. Global radiation on a horizontal surface.
3. The ratio of diffuse to the total radiation as affected by the atmosphere
turbidity and moisture.
39
4.1.2 Dogniaux Model
The Dogniaux Model, which was developed in 1967 by the CIE
(Commision Internationale de Eclairage), is one of the first major prediction
models developed. The Dogniaux model has two techniques to calculate the
exterior illumination on a horizontal plane: a model for a clear sky, and a model
for overcast sky.7
It is more applicable for overcast sky than clear sky comparing to the
IES model. It is, however, useful for overcast climates common in Europe
where this prediction model was developed.
4.1.1 IES Model
The IES model, which is known as the lumen method as well, is based
on the luminance model studies by Richard Kittler, Moon and Spencer. It is
recommended by the Iluminating Engineering Society, and it is used for the
prediction of the direct and diffuse light for clear, partly cloudy and overcast
sky conditions; however, this method is recommended the most for clear sky
condition. It measures both exterior and interior illumination. This method is
discussed in details in 4.2.1.
4.2 Interior Illumination Methods
There are several methods to calculate the interior illumination, some of
these methods are manual calculations, graphic methods, computer calculations
o
and model measurements. The manual methods will be covered.
4.2.1 Lumen Method
The basic procedure to calculate the available illumination on a
horizontal plane are as follows:
1) The latitude and longitude of the site location.
2) The day of the year (Julian date).
3) The local time.
The next step is to find the related solar position to the site:
1) The solar altitude of the sun.
2) The solar azimuth of the sun.
mm
j U P
Figure 4.1 Lumen input method.
41
However, the daylight illumination calculated at a particular point in a
space is not only coming directly from the sun, but coming from the sky dome,
reflected from the surrounding buildings, and reflected from the ground;
therefore, all these factors should be taken into consideration. On the other
hand, there are some design factors like louvers, overhangs, glazing
materials,...etc. These factors should be included in the calculations. In this
method, we can only calculate three points in a single space, Max, Mid and
Min (Figure 4.1). Each reference point can be simply calculated for sidelighting
by following the coming steps:8
Step # 1
Find the Azimuth of the sun with respect to the window. From table A .l, we
can detemine the solar azimuth after defining the latitude of the site.
A ’ = A - Aw where:
A ’ =The azimuth of the sun with respect to the window.
A = The solar azimuth.
Aw= The window azimuth.
If ‘A’ is bigger than 90 degrees, that means the sun is not shining on
the window at that particular time, knowing the solar azimuth, altitude and the
sky condition, we can find the illuminance on a vertical surface, which is Ek w in
Klux (Kilo lux = 1000 lux) from table A.2.
42
From table “ A .3” , we can define the illuminance on a horizontal
surface, which is Ek g in Klux. Then, define the reflectance of the ground from
table “A.4 ” . After that, we find the illuminance from the ground on the
window using this formula:
E ^ = 0.5 ( E fcg ) pg where:
Egw = The illuminance from the ground on the window.
Ek g = The illuminance from the sky on the window.
pg = The reflectance of the ground.
Step # 2
Find the net glass area of the window where the sill height is 3 feet as a
minimum.
Step # 3
Find the net transmissivity of the window. Factors considered are the
mullions, glass transmissivity, dirt loss factor, and any other information
provided by the manufacturer. See table ( A.5).
Total x = xl + t2 + t3 + ............
Step # 4
Find the coefficient of utilization ( K & C ) values for both the sky and
the ground for a specified point ( Max, Mid, Min) from table “ A .6”. Then,
substitute all the numbers into the general equation twice, once for the direct
effect and once for the ground effect.
43
Ek = Ek w (fc) x Aw (ft2) x t x Ck x Kk
Eg = Ek g (fc) x Aw (ft2) x t x Cg x Kg
where:
Ek = The total illumination from the sky in footcandles.
Eg = The total illumination from the ground in footcandles.
Ekw = The illumination from the sky on the window in (fc).
Ekg = The illumination from the ground on the window in (fc).
Aw = The net glass area.
t = The net transmissivity.
Then, the sum of the two formulas is the illumination at the defined point.
Total illumination (fc) = Ek 4- Eg
4.2.2 Daylight Factor M ethod
The daylight factor (DF) method was first developed in England and
approved by the CIE. It can calculate any position in the room instead of only
three points in a space like what was discussed in the lumen method (Figure
4.2).
The daylight factor method is not a method which can be directly
calculated, but it is a percentage of an illuminance available on an exterior
horizontal surface; so, the daylight factor at a certain point (p) is defined as:
D F = ( E p / E exterjor horizontal ) * 1 0 0
44
D C
0 II
Building
Ground
Figure 4.2 Daylight factor method (Stein, 1986).
The calculated daylight factor is the sum of the following components:
1) The sky components (SC), which are the illuminance striking a given station
point received directly either from the sun or from the sky.
2) The external reflectance components (ERC), which are the reflected
illuminance from the external surfaces.
3) The internal reflectance components (IRC), which the illuminance striking a
station point received either directly or indirectly from the daylight that
interreflected around the room. The internal illuminance reflectance is received
from the interreflected daylight of the ground of the outside, of the ground of
the space, of the ceiling and of the interior walls (Figure 4.2).
An interior maintenance factor (MF) can be added to represent the
frequency of cleaning the interior surfaces of the space. The daylight factor is
expressed as:
45
DF = SC + ERC + (MF)(IRC)
This formula can be used when there is no glazing used for the opening.
A glazing factor (Cg) can be added to the equation which reduces the interior
illuminance.
Cg = (Tg / 0.85) (Dg) (Fg) where:
Tg = the glazing transmission
Dg = the dirt depreciation factor
Fg = the ratio of glazed area to aperture area
DF then becomes:
DF = [SC + ERC + (MF)(IRC)]Cg
Using the this method and the average exterior illuminance chart, the
absolute illuminance can be determined at any station point in the room. The
typical approach used for manual applications of DF method is not one of the
calculating absolute light levels but of working backward from weather
information and available illuminances so as to provide a desired daylighting
factor within a space so that minimum illuminance requirements are met over a
desired period of time.8
The following steps are taken to find the sidelighting necessary to
provide a minimum light:8
We will begin by trying to obtain a design level of 50 fc throughout the
space for at least 80% of the time between 9:00 A.M. and 5:00 P.M .
46
Step # 1
Looking at table B. 1, we see that at, for example, 34° north latitude,
1300 fc is available for at least 80% of the time.
Step # 2
By dividing our design level by the illuminance available on the exterior
surface, we obtain the required minimum daylight factor within a space.
DF = (50/1300) * 100 = 3.9%
Step # 3
Find the dirt correction factor for vertical glazing from table A.5. The
corrected daylight factoris:
new DF = DF/DCF
Step # 4
From table B.2, we can find how many times the room depth can exceed
the the height of the window. For example, if the strip window covers more
than 90% of the length of the window wall, and the room is longer than 33 feet,
the room depth cannot exceed 1.8 times the height of the window (1.8H).
Step # 5 and 6
There is no need to make adjustments if there is no obstructions outside
the window. However, if there are obstructions, adjustments should be taken
into consideration.
47
Step # 1
Find the window height and then find the room depth that provides the
minimum DF required for the space by multiplying the height of the window by
the number obtained from step # 4.
Although the daylight factor method is more flexible than the lumen
method under an overcast sky, the application of this method is still largly
dependent on pre-tested results. However, a good approximation of light level
can be determined using this method.
4.3 Physical Models
There are so many complex spaces, shapes and curved walls which can
not be calculated by using any of those mentioned calculation methods. There
are many situations where some qualitative questions can not be answered or
modeled by any method or computer program. Physical models are considered
as they are more accurate in terms of studying the qualitative and quantative
daylight more than any model because, simply, other calculation models are
based on many assumptions as mentioned in 4.1.1.
4.3.1 Objectives of Building Physical Models
1. Offering a “ safe technology” approach in a sensitive design area, without
using expensive equipment requiring on analysis of endless rows of seemingly
obscure numbers to come up with a meaningful answer to a simple question9.
48
2. Daylighting models are extremely accurate. The distribution of daylight
within the model space is exactly the same as it would occur in a full-size room,
when the model is built properly. Differences in luminance between models and
full-size structres are negligible, when measured.9
3. They, as well, answer vital questions about many aspects of the building
design in addition to daylighting, and that is the most important reason for
building the daylighting models. They answer questions about quantitative data
taken to detemine the adequacy of daylight for meeting visual needs.
“Qualitative data from visual observations and photographs can indicate
whether there is visual comfort and clear rendition o f the spatial characteristics
o f the room. Qualitative evaluation of models requires the use of photocells
and measuring equipment. Qualitative evaluation of a daylighting model
through the use of direct observation, still photography or video recording
allows for subjective appraisal of the apperance of the space.
4. The model is capable of dealing with more complex forms than are any
computer program.
4.3.2 Assessing the Purpose of Modeling Project
Two things should be considered, the budget for the model construction
and when each different scale of model is appropriate. For example, smale scale
models are used at an early stage of preliminary design and development; they
49
could be used, as well, to study more general site scaled questions such as solar
access, or reflection or obstruction of daylight. The appropriate scale for that is
1:200 or 1:100.
Mid and full scale models are used, however, for detailed refinement of
spatial components and used for the final documentation of critical daylighting
details that influence the documentation of critical photometric performance.
The appropriate scale for that is 1:10 to full scale mockups of a space.
The quality of the spatial effect and the quantities of daylight available
are extreme and should be accurately represented, since they change as the
reflectances change. Therefore, all the surface materials used in the model
should have a matte finish since is that the type of surface finish that is optimum
in the finished building. Materials which produce specular reflection, such as
glass, water or mirror surfaces, should be approximated. In addition, all
construction joints in the model should be taped with black electrical tape, or
any other truly opaque tape.
Shading devices, like roof overhangs and louvers, should be included in
order to obtain accurate illumination data, but glazing devices should not be
simulated, and the results should be multiplied by a glazing factor. It is
recommended to use a dirt depreciation factor whenever horizontal or exterior
reflectors are used because mirrors and any other reflectors may give distorted
50
results. At the same time, the illumination readings must be lowered by
multiplying the measured values by a glazing bar factor.
Model analysis must evaluate the effects of all site obstructions and
deciduos trees. The use of an adjustable table to track the sun to simulate annual
daylighting may distort measurements due to the unnatural position of the
neighboring buildings and trees.
4.3.3 Measuring the Results
There are some materials and equipment required for preparation:
1. The site should be beneath an artificial sky or on a real site similar to the
actual building site.
To simulate an artificial sky, which is used to simulate an overcast
condition, a mirror box is used. The design principles of the mirrored box are
based on an infinite reflection to the horizon and highly diffused luminous
ceiling to the box. It is most often composed of an array of closely spaced
fluorescent lamps behind a sheet of diffusing plexiglass. It provides a good
overcast illuminance distribution and allows the model to see the horizon as it
should be. The inner virtical surfaces of the box are mirrored. Small high-speed
fans are provided to ventilate the light fixtures (Figure 4.3).
Figure 4.3 The mirror box for simulating overcast sky.9
2 . The scale o f the model should be appropriate for the size o f the light
sensors; in addition, a grid on the model floor should be drawn to mark at
which point measurements are to be taken.
3. At least two luminance meters to be used in the measurements, one to
be placed inside the model, another one to be placed outside the model to
measure the illuminance available outside.
4. Labling the points, at which measurements are to be taken, helps to
facilitate communication between the meter mover and the data recorder.
5. After doing all the measurements, photograph the testing model
showing the position o f the photometric equipment for future reference.
52
4.3.4 Equipment Used for Measurements
There are some equipment used in measuring the illuminance level in a
space, and studying the qualitative light, as well.
4.3.4.1 Photometric Equipment
1) Illuminance Measurements: They are a full cosine corrected meter
which is usually used to measure the illuminance. The phtometer should have a
range from 1 - 1000 footcandles (Figure 4.4).
3
3
f!
Figure 4.4 Fully cosine collected meter allows extra light to strike side of diffuser to
compemsate for higher diffuser reflectace at lower angle.9
2) Luminance Measurements: Luminance meters measure the luminance
in foorLamberts of a very small portion of a surface or sky with the field or
view.
53
4.3.4.2 Computerized Multi-Sensor System
1) Remote Sensors: They are remote from the display and are desirable
alternative to the self-contained meter.
2) Multiple Sensors: They are composed of several sensors connected to
a single meter. They are used when model studies require measurements at
several model locations at once. The major problem here is that the sensors
have to be calibirated relatively one to another.
3) Microcomputer Systems: A microcomputer system is a briefcase-sized
system with multiple remote photometric sensors. It has a battery which is
operated and suitable for several hours of operation in the field. The analog
signal from each sensor is converted to a digital signal recognized by the
microcomputer using an analog-to-digiter converter connected to the
microcomputer by a cable.
4.3.4.3. Video and Photography
Using cameras and video tapes instead of pens and papers allows
designers to visualize and present the design in more realistic form, but
computer programs and various diagrams allow designers to examine or
evaluate the daylight distribution for a fixed period of time, and that means that
the dynamic changes of daylight are unexamined.
54
Figure 4.5 Daylighting model data acquisition system.9
Photography provides a permanent record o f daylighting conditions
inside the space. This technique provides an evaluation method for observation
o f the quality o f light and a comparison to other design options. W ide angle
lenses recommended for model photography are 21mm, 24mm , and 28mm
because their viewing angles are approximate to that o f the human eye. An ASA
400 daylight film is appropriate for photographing the tested model if different
types o f light sources are used.
A video camera can be functioning the same thing as the camera, but
with motion pictures. Supported computer programs are used with video
camera. For example, for IBM compatible machines, a video camera with
55
monitor, Computer Eye, Video Blaster, Super VIA, and softwares such as,
Foto Shop or Video for Windows, are the supported equipment needed for these
applications.
4.4 Evaluating the Results
Because daylighting models generate a very large amount of quantitative
data, it is desirable to present this data graphically. The two graphic formats
most widely used for this purpose are the Iso-Lux Contour Plan and the
Daylight Factor Graph.
Daylight Factor data from physical model studies, calculations, or
building surveys can be presented graphically in the form of contour of equal
daylight factor (DF) plotted over a building floor plan. This method allows
ready assessment of illuminance distribution throughout a room.
Another method is that the daylight factor levels are presented
graphically overlayed on a building section cut through the fenestration. The
daylight factor curve for each fenestration reveals much design information
above and beyond the individual illuminances used for the plot.
56
REFERENCES:
1) Bound, Joh.
Lighting Design in Buildings. England, Peter Peregrinus Ltd, 1973.
2) Gillette, Gary.
A Daylighting Model for Building Energy Simulation. Washington D.C.,
U.S. Department of Commerce, National Bureau of Standards Building
Science, Series 152, 1983.
3) Hopkinson, R.G. and Kay, J.D.
The Lighting o f Buildings. England, Frederick A. Prager, 1969.
4) Leifeste, A.A.
Predicting Daylighting With Models. Rice University, 1966.
5) Lynes, J.A.
Principles o f Natural Lighting. London, Elsevier Publishing Company
LTD, 1968.
6) Phillips, Derek.
Lighting in Architectural Design. New York, McGraw-Hill, 1964.
7) Robbins, Claude L.
Daylighting Design and Analysis. New York, Van Nostrand Reinhold
Co., 1986.
8) Schiler, Marc.
Simplified Design o f Building Lighting. New York, John Wiley & Sons,
1992.
9) Schiler, Marc, editor.
Simulating Daylighting With Architectural Models. DNNA, 1990.
10) Walsh, John W.T.
The Science o f Daylight. London, Macdonald, 1961.
57
5. Measuring the Illuminance in Atria Using Physical Models
In this chapter, the study intends to measure the daylight performance in
atria under clear sky conditions. It intends to measure the quantitative and
qualitative available light, as well, using Physical models. The measured light is
taken on the ground level of the atria.
There are various reasons for simulating daylighting with physical
models, these include:4
1) Learning about the lighting technique used in a remote existing
building.
2) Evaluating a given design or remodel proposal.
3) Choosing among design proposals.
4) Studying the behavior of a particular variable in parametric studies.
The aim of this research is to study the behavior of light inside atria to
have the output analysis available to be used by designers and architects in
predicting the available amount of light in atria upon a given length, width and
depth.
5.1 Description of Method
Section 4.2 explains all the important factors which should be taken into
consideration when building a physical model used for daylighting studies. All
58
those factors were firmly followed in order to attain accurate results. As a
matter of fact, the accuracy of the daylighting measurements using physical
models is similar to an original building if the two results are to be compared.
In addition, physical models can beat any other calculation model or computer
programs which were designed under several assumptions.
A model with a scale of l ” = l ’-0” is used to simulate the daylight
distribution in an atrium of 20’ Width, 20’ Length, and 40’ depth which results
in a ratio of 1:1:2 where the depth is double the length and the width. This
kind of atrium is used in hot and sunny climates to prevent the ground of the
atria of being overexposed by the direct sunlight which is undesirable.
The physical model represents an abstract atrium study; therefore, the
physical model is built of four foamcore walls with the same geometry
mentioned above. Since there are no windows used in this study, the reflectance
of the walls is lowered and averaged as much of the light is absorbed by the
openings. Thus, reflectance materials of 30 % are used for the walls and the
ground. A grid pattern of one foot by one foot is drawn on the ground floor of
the model to mark at which point measurements are to be taken.
One of the four panels is removable to facilitate the process of placing
the measuring devices. The technique of removable panels, in general, should
be used whenever simulating daylight with architectural models because that
enable the designer not only to photograph the model, but to study different
59
material reflectances, different width and length o f windows and skylights,
different shapes o f overhangs, louvers and light shelves.,.etc. However, the
back sides o f all the walls are covered with thick black construction paper to
avoid any light leakage through the wall panels.
To measure the illuminance in different hours and months o f the year, a
sundial diagram (solar gnomon) is used which allows the readings to be taken at
any time o f the day on the 21st o f each month; therefore, a tilting device was
required.
The model is fixed to a plywood base which contains a small b^xb”
piece o f plywood at the bottom o f the base. The small piece o f plywood is
attached to a tripod which facilitates orienting the model in all directions
(Figure 5.1).
Figure 5.1 Using a tripod to tilt the model in different orientations.
60
5.2 Devices Used for Testing
5.2.1 286 Compatible Computer
The DATALIT computer program1, which was developed at the
University of California at Los Angeles with the help of Atmospheric
Technology ( ATEC) and Southern California Edison (SCE), is used. The
program allows the user to input all the necessary dimensions for a space, like
the design of the room, windows and skylights, and the surface reflectances. In
addition to that, the geometry of the overhangs, lightshelves,...etc could be
input. The meters are directly connected to the computer, and the program
samples, records, calibrates and weighs the readings. The final output is in foot
candles (fc) for the reference points chosen(Figure 5.2).
5.2.2. LI-210S Photometric Sensors
The Licor LI-21 OS photometric sensors are designed to measure
illumination in terms of lux ( 1 foot-candle = 10.764 lux).
This is radiation as the human eye sees it; although characteristics of the
human eye vary from person to person. Standard luminosity coefficients for the
eye were defined by the Commission Internationale de Eclairage (C.I.E.).
The sensor may be handled or mounted easily at any angle. In its most
frequent application, the sensor is set on a level surface. Sensors should be
61
clean and treated as scientific instruments in order to maintain the accuracy of
their calibrations. In addition, the vertical edge of the diffuser should be clean
in order to approximate the cosine correction factor.
A sensor, which has a cosine response and follows Lambert’s Cosine
Law, allows measurements of flux densities through a surface plane. This
allows sensors to measure flux densities per unit area (m2).2 A sensor without
an accurate cosine correction can give a severe error under diffuse radiation
conditions.
The LI-21 O S photometric sensors have been calibrated against a standard
lamp. The uncertainty of the calibration is +5% or -5%. They should be
further calibrated against each other before taking any readings. To calibrate
them:
1) Place all LICOR light sensors together in a close packed group.
2) Place a sheet of paper over the sensors to diffuse light and eliminate
any point sources or uneven illumination.
3) Check the Input Module Box is turned on and all the wires are
connected.
4) Run the DATALIT program, which compares each sensor’s reading
to the average of all sensors, and determines the appropriate correction factor
for each one.
62
5.2.3 The Portable Analog Input Module
A Fowlkes Engineering Serial Analog Module (SAM ) accepts eight
analog inputs, and provides up to four latched digital outputs. It converts the
analog signals into digital signals. The module is connected to a serial port on
the computer with a single three-wire cable.
The SAM is small, light-weight, and powered by an internal battery. An
optional internal amplifier is available. It operates at 0-70°C operating
temperature, 15% - 90% Relative Humidity, and it is non condensing.3 The
SAM has four digital output bits that can be controlled by the computer using
the COM M AND word. The output bits are labeled 3 ,4 ,5 , and 6 on the terminal
strip.
Figure 5.2 The physical model next to the computer unit used for testing.
5.3 M easuring the Results
A . The model was tested under clear sky conditions in Los Angeles,
California, 34° N Latitude. The testing took place on the roof o f Watt Hall o f
63
the University of Southern California (USC) to avoid any obstructing objects
like trees and buildings.
B. Reference points were carefully selected on the ground floor of the
atrium because of the limited number of light sensors which could be attached
to the SAM. Therefore, seven Licors were located inside the atrium and one
was located completely outside the atrium to measure the total horizontal
illumination. The inside light sensors were located as follows (Figure 5.3):
1) East of the center point and one foot from the wall, (1,10) coordinate.
2) North -west comer and one foot from the wall, (1,19) coordinate.
3) South of the center point and one foot from the wall, (10,1) coordinate.
4) The center of the atrium, (10,10) coordinate.
5) North of the center point and one foot from the wall, (10,19) coordinate.
6) South-east comer and one foot from the wall, (19,1) coordinate.
7) East of the center point and one foot from the wall, (19,10) coordinate.
C. DATALIT (see 5.2.1) was used to read the illumination level from
each light sensor.
64
" 1 ’
9’
1 "
9 ’
Figure 5.3 The location of each reference point in the atrium.
D. The illumination level was measured every hour, on the hours from
9:00 a.m. - 3:00 p.m ., on the 21st of each month using the sundial diagram for
the same latitude (Figure 5.4), and using the tilting device.
m ar/sep t 21
noon
6am
34* NORTH LATITUDE
Figure 5.4 The sundial diagram.
0 O
2 5
0 O 0
1 4 7
3
o
i
65
5.4 Analysis
Preliminary data indicated that the primary variation of the daylight
factor (DF) for every reference point inside the atrium occurs due to the change
in time and month. However, the first overall illumination level seemed too
high. This was perhaps because of the materials used for the model, including
foamcore, which leaks light. The model was, therefore, corrected by covering
the exterior surfaces with black sheets and taping the joints and tested again.
Each reference point mentioned in 5.3.B is plotted in a graph; x-axis
shows the months, y-axis shows the hours, and the z-axis shows the daylight
factor which is calculated by measuring the total horizontal illumination and the
indoor illumination, which resulted from diffuse light from the sky and reflected
light from surrounding walls. ( See Appendix D for the complete collected data
for each reference point from 9:00 a.m .-3:00 p.m. on the 21st of each month).
Daylight Factor (DF) = (Indoor Illumination / Total Horizontal) * 100
It was found, after obtaining all the measurements from the physical
model, that the daylight factor ratio among all the reference points obtained
remains constant when changing the time and the month, except when the direct
sunlight hits the ground. That observation was interesting; so, designers and
architects can predict the amount of light that reaches the ground of an atrium if
they know the illumination level at, at least, one reference point. At the mean
time, it was found that the DF in summer is always higher than the DF in
66
winter and spring almost by the half, and that because of the high exterior
illumination level in summer.
For this atrium, with a ratio of 1:1:2, several behaviors were observed.
Some of the behaviors were expected and some of them have consistent ratios
which were beyond what was expected.
1) The DF in the center of the atrium is always higher than anywhere
else in the atrium (Figure 5.8).
2) The lowest DF we get is for all the reference points adjacent to the
north facing wall (Figure 5.7 and 5.10).
The following are consistent observation ratios:
3) The DF ratio is almost the same for any particular hour, and along
the center line from east to west; 2: 3: 2 (Figure 5.5, 5.8 and 5.11).
4) The DF ratio decreases gradually along the center line of the atrium
from north to south with a ratio of 4: 3: 2, especially at the peak hours from
10:00 a.m. - 14:00 p.m ( Figure 5.7, 5.8 and 5.9).
From the above mentioned observations, we can as architects,
designers, and landscape architects predict the amount of light in different spots
of the atrium. Upon that, we can determine the function of each spot; for
example, the highest illumination level is in the center of the atrium; therefore,
it is preferably used for plantings which will not hurt the illumination level in
other direction that much.
67
The north facing wall (south edge of atrium) receives the lowest
illumination, as was observed; therefore, it is recommended to be used as a
sitting area especially if the climate is hot.
The DF ratios between the east and west walls are about similar. The
same function for these walls at the ground level can be used. However,
interesting observations were found:
1) When comparing the illumination level along the east and west walls on the
ground level, it was found that at 9:00 A.M. in winter, the east side of the
atrium floor receives more light than the west side. This is counter intuitive.
Most of the light received at that particular time is reflected light bouncing from
the upper portion of the opposite wall. The same observation was found for the
west side of the atrium at 3:00 P.M .in winter (Figure 5.12a).
2) When comparing the illumination level along the north and the south walls
on the ground level, it was found that at noon in winter, the south side of the
atrium floor receives more light than the north side. Most of the light received
at that time is reflected light bouncing from the opposite wall (Figure 5.12b).
However, in summer at noon, the atrium’s floor receives a great deal of direct
sunlight in half of the portion of the atrium’s ground (Figure 5.12c).
68
DAYLIGHT FACTOR (DF)
PHYSICAL MODEL
REFERENCE PO IN T # 1 (1,10). 20 X 20 X 40
Figure 5.5 Reference point # 1 in the atrium (west edge).
DAYLIGHT FACTOR (DF)
REFERENCE PO IN T # 2(1,19). 20 X 20 X 40
PHYSICAL MODEL
o
Figure 5.6 Reference point # 2 in the atrium (north west corner).
DAYLIGHT FACTOR (DF)
REFERENCE PO IN T # 3(10,1). 20 X 20 X 40
PHYSICAL MODEL
Figure 5.7 Reference point # 3 in the atrium (south edge).
DAYLIGHT FACTOR (DF)
PHYSICAL MODEL REFERENCE PO IN T # 4(10,10) 20 X 20 X 40
Figure 5.8 Reference point # 4 in the atrium (middle).
DAYLIGHT FACTOR (DF)
REFERENCE PO IN T # 5(10,19) 20 X 20 X 40
PHYSICAL MODEL
\ 0 \ Y \ V
f \ \ w n v ; \ \ w
Figure 5.9 Reference point # 5 in the atrium (north edge).
DAYLIGHT FACTOR (DF)
v . V i
REFERENCE PO IN T # 6(19,1) 20 X 20 X 40
PHYSICAL MODEL
4 -
Figure 5.10 Reference point # 6 in the atrium (south east corner).
DAYLIGHT FACTOR (DF)
REFERENCE PO IN T # 7(19,10) 20 X 20 X 40
PHYSICAL MODEL
..
Figure 5.11 Reference point # 7 in the atrium (east edge).
DECEMBER 21 AT 9:00
DECEMBER 21 AT 12:00
JUNE 21 AT 12:00
Figure 5.12 The illumination inside the atrium at particular hours.
76
REFERENCES:
1) LI-COR Instruction Manual.
LI-COR Ltd, Lincoln, Nebraska.
2) Milne, Murray.
DATALIT computer software. University of California, Los Angeles,
1986.
31 SAM Manual.
Portable Analog Input Module, Fowlkes Engineering Bozeman M T.,
1984.
4) Schiler, Marc, editor.
Simulating Day lighting With Architectural Models. DNNA, 1990.
77
6. Validation of the “ LIGHTSUM” Program Using Models
This is an extension to chapter 5 in terms of the results and the analysis
obtained from the physical model. This chapter intends to validate a computer
program called “ LIGHTSUM”.
6.1 Background
The LIGHTSUM computer program is written by a former graduate
student at University of Southern California. It calculates the available
illuminance inside atria using IES, Gillette and Dogniaux sky models, and form
factors for reflective surfaces.
The computer program, with output in table formats and three
dimensional graphics, is developed to do the following:
1. Calculate the solar altitude and azimuth angles for a given site, at a given
date and time.
2. Read a TMY (Typical Meteorological Year ) weather files to provide record
weather data for a specific site.
3. Calculate the direct, diffuse and total horizontal radiation at an open site or
atrium.
4. Calculate the exterior illuminance from the direct sun and diffuse sky, using
the solar radiation data, atmospheric turbidity, air moisture and other weather
data.
78
5. Calculate the total illuminance available over a defined period of time on a
workplane of specified height.
6.2 Collecting Data
To validate the “LIGHTSUM” computer program, all the input data
have to be analogous to and under the same conditions that the physical model
was tested. Since the physical model was tested under clear sky condition, the
input data have to be for the same condition. Therefore, there was a need to
create a weather file for Los Angeles, California, for the entire year to read
only clear sky condition data. The Typical Meteorological Year ( TMY) format
was used ( see Appendix C ), and data was collected from different computer
programs like, DOE2, SOLARIS, and CLIMATE CONSULTANT. The
following data were collected for the entire year, from 9:00 a.m. to 3:00 p.m .:
1. The solar altitude angle for 21st of each month from 9:00 a.m .-3:00 p.m .;
The data were collected from SOLARIS computer program.
2. The direct normal radiation. The heighest value of each month was picked as
the brightest sunny day and used for the 21st of that month. The data were
collected from CLIMATE CONSULTANT computer program.
3. The total Horizontal radiation. The same as the direct normal was picked.
The data were collected from CLIMATE CONSULTANT as well.
79
4. The extraterrestrial solar radiation data were collected from DOE2.
However, all the values obtained from DOE2 have the same readings for all
hours; therefore, all the values were subsequently multiplied by the sine of the
altitude angle for that hour.
The sky ratio of each hour on the 21st of each month is calculated by
LIGHTSUM. It was noticed that all the sky ratios from 9:00-15:00 are below
30 % which indicates a clear sky condition ( See tables 6.1-6.12).
The same atrium geometry used in the physical model was applied to the
computer program to calculate the interior illumination of the atrium for the
same reference points used in the physical model ( Figure 5.1).
6.3 Analysis
The data collected from LIGHTSUM for both IES and Gillette
recommended models were calculated in Klux; so, to compare the output data to
it in the physical model, all the data were converted to footcandles and then to
DF to facilitate the comparison. All the output data, as well, were plotted in
graphs; each graph represents a reference point, where the x-axis shows the
months, the y-axis shows the hours, the z-axis shows the daylight factor. The
geometry of the atria were plotted, as well, to compare it to the physical model
( See Appendix E for the complete collected data for IES and Gillette models).
80
TIME EXTRATER.
RADIATION
( KJ/M2 )
DIRECT
NORMAL
(KJ/M2)
TOTAL
HORIZ.
(KJ/M2 )
ALTITUDE
( DEGREE)
SKY
RATIO
(%)
9:00 1569 1904 901 20.62 27
10:00 2166 2689 1481 28.36 14
11:00 2461 3001 1919 33.53 14
12:00 2578 3133 2149 35.36 16
13:00 2461 3133 2148 33.53 19
14:00 2116 3009 1923 28.36 26
15:00 1569 2715 1493 20.62 36
Table 6.1 Data collected for January 2 St.
TIME EXTRATER.
RADIATION
(KJ/M2)
DIRECT
NORMAL
(KJ/M2 )
TOTAL
HORIZ.
(KJ/M2)
ALTITUDE
( DEGREE)
SKY
RATIO
(%)
9:00 2046 2099 1172 27.47 17
10:00 2616 2799 1796 36.14 10
11:00 2975 3061 2252 42.11 9
12:00 3097 3196 2488 44.27 10
13:00 2975 3176 2480 42.11 14
14:00 2616 3000 2229 36.14 21
15:00 2046 2647 1769 27.47 31
Table 6.2 Data collected for Febrauary 21st.
TIME EXTRATER.
RADIATION
(KJ/M2)
DIRECT
NORMAL
(KJ/M2 )
TOTAL
HORIZ.
(KJ/M2)
ALTITUDE
( DEGREE)
SKY
RATIO
(%)
9:00 2522 2300 1507 35.36 12
10:00 3093 2832 2162 45.21 7
11:00 3453 3090 2626 52.38 7
12:00 3574 3189 2862 55.10 9
13:00 3452 3136 2838 52.38 12
14:00 3092 3057 2612 45.21 17
15:00 2522 2832 2162 35.36 24
Table 6.3 Data collected for M arch 21st.
81
TIME EXTRATER.
RADIATION
(KJ/M2)
DIRECT
NORMAL
(KJ/M2)
TOTAL
HORIZ.
(KJ/M2 )
ALTITUDE
( DEGREE)
SKY
RATIO
<»>
9:00 2887 2584 2001 43.20 12
10:00 3429 3014 2656 54.38 8
11:00 3769 3135 3101 63.32 10
12:00 3885 3167 3320 67.08 12
13:00 3769 3128 3269 63.32 15
14:00 3429 3098 3062 54.38 18
15:00 2887 2754 2558 43.20 26
Table 6.4 Data collected for April 21st.
TIME EXTRATER.
RADIATION
(KJ/M2)
DIRECT
NORMAL
(KJ/M2 )
TOTAL
HORIZ.
(KJ/M2 )
ALTITUDE
( DEGREE)
SKY
RATIO
(%)
9:00 3017 2617 2314 47.91 16
10:00 3481 2803 2869 58.91 15
11:00 3831 3059 3285 70.46 12
12:00 3938 3082 3488 75.64 14
13:00 3831 3041 3432 70.46 16
14:00 3481 3025 3241 58.91 19
15:00 3017 2962 2844 47.91 23
Table 6.5 Data collected for May 21st.
TIME EXTRATER.
RADIATION
(KJ/M2 )
DIRECT
NORMAL
(KJ/M2 )
TOTAL
HORIZ.
(KJ/M2 )
ALTITUDE
( DEGREE)
SKY
RATIO
(%)
9:00 3008 1928 2033 49.47 28
10:00 3484 2592 2759 61.66 17
11:00 3783 3032 3371 72.88 14
12:00 3885 3049 3557 78.95 16
13:00 3783 3029 3531 72.88 18
14:00 3484 3021 3357 61.66 21
15:00 3008 2977 2993 49.47 24
Table 6.6 Data collected for June 21st.
82
TIME EXTRATER.
RADIATION
(KJ/M2 )
DIRECT
NORMAL
(KJ/M2 )
TOTAL
HORIZ.
(KJ/M2 )
ALTITUDE
( DEGREE)
SKY
RATIO
<%)
9:00 2932 2731 2354 48.06 14
10:00 3415 2984 2950 60.06 12
11:00 3719 3049 3342 70.69 14
12:00 3823 3068 3531 75.94 16
13:00 3719 3055 3513 70.69 18
14:00 3415 3046 3337 60.06 21
15:00 2932 2997 2966 48.06 25
Table 6.7 Data collected for July 21st.
TIME EXTRATER.
RADIATION
(KJ/M2)
DIRECT
NORMAL
(KJ/M2 )
TOTAL
HORIZ.
(KJ/M2)
ALTITUDE
( DEGREE)
SKY
RATIO
(%)
9:00 2769 2652 2238 43.31 19
10:00 3286 2945 2855 54.50 16
11:00 3611 3040 3264 63.47 17
12:00 3722 3064 3461 67.25 18
13:00 3611 3058 3453 63.47 21
14:00 3286 3044 3268 54.50 24
15:00 2769 2986 2881 43.31 29
Table 6.8 Data collected for August 21st.
TIME EXTRATER.
RADIATION
(KJ/M2)
DIRECT
NORMAL
(KJ/M2 )
TOTAL
HORIZ.
(KJ/M2 )
ALTITUDE
( DEGREE)
SKY
RATIO
(%)
9:00 2442 2465 1919 35.50 25
10:00 2993 2846 2573 45.37 21
11:00 3339 3009 3016 52.57 21
12:00 3457 3062 3234 55.30 22
13:00 3339 3048 3225 52.57 25
14:00 2993 3014 3019 45.37 29
15:00 2442 2887 2595 35.50 30
Table 6.9 Data collected for September 21st.
83
TIME EXTRATER.
RADIATION
( KJ/M2)
DIRECT
NORMAL
(KJ/M2)
TOTAL
HORIZ.
(KJ/M2 )
ALTITUDE
( DEGREE)
SKY
RATIO
{%)
9:00 1981 2107 1331 27.80 28
10:00 2540 2692 1980 36.50 21
11:00 2891 2982 2444 42.60 19
12:00 3011 3105 2680 44.80 20
13:00 2891 3084 2670 42.60 23
14:00 2540 2985 2442 36.50 29
15:00 1981 2723 1992 27.80 30
Table 6.10 Data collected for October 21st.
TIME EXTRATER.
RADIATION
(KJ/M2)
DIRECT
NORMAL
(KJ/M2 )
TOTAL
HORIZ.
(KJ/M2 )
ALTITUDE
( DEGREE)
SKY
RATIO
(%)
9:00 1542 1834 1001 21.00 29
10:00 2085 2608 1616 28.80 24
11:00 2427 2972 2083 34.00 22
12:00 2543 3108 2318 35.90 23
13:00 2427 3104 2316 34.00 27
14:00 2085 2982 2088 28.80 29
15:00 1542 2682 1646 21.00 29
Table 6.11 Data collected for November 21st.
TIME EXTRATER.
RADIATION
(KJ/M2 )
DIRECT
NORMAL
(KJ/M2 )
TOTAL
HORIZ.
(KJ/M2 )
ALTITUDE
( DEGREE)
SKY
RATIO
(%)
9:00 1377 1649 0679 18.40 25
10:00 1913 2440 1217 25.90 14
11:00 2249 2841 1631 30.80 12
12:00 2364 2884 1796 32.60 15
13:00 2249 2848 1777 30.80 19
14:00 1913 2683 1569 25.90 27
15:00 1377 2242 1161 18.40 29
Table 6.12 Data collected for December 21st.
8 4
6.4 Summary
Even though the physical model agrees with the computer program in
terms of the shape of the ilumination level distributed inside the atria, the
physical model, however, does not agree with the computer program in two
major facts:
1. The daylight factor calculated for each reference point seems significantly
higher than the DF measured from the physical model.
2. The LIGHTSUM does the inverse of what is shown on the graphs from the
physical model, high daylight factors in winter and low daylight factors in
summer and spring for both IES and Gillette models. The LIGHTSUM shows
very low exterior horizontal illumination in winter and that causes the high
daylight factor. However, the daylight factor in summer and spring is twice as
high as in the physical model.
Therefore, the physical model tests do not validate the computer
program.
85
fttfrg te N & E POINT « 1 (1,10). 20 X 30 X «p|
IES MODEL
E g n g g g c g EoinT 4 1 g,io>: 207 2oV *ol
QILLETTE MODEL
PHYSICAL MODEL PREFERENCE POINT *1(1,10). 20 X g T g )
Figure 6.1 Reference point #1 for IES, Gillette and physical models.
8 6
PREFERENCE POIWT » 2(1,1 » |. 2 0 X 2 0 X «Oj
Figure 6.2 Reference point # 2 for IES, Gillette and physical models.
87
g S g j g g K W g g « an o,i). 20 T g T g
[REFERENCE ROIKS « 3 10,1), 20 X 20 X H O )
PHYSICAL MODEL REFERENCE POINT* 3110,11. 2C X 20X ^C|
Figure 6.3 Reference point # 3 for IES, Gillette and physical models.
8 8
P H Y S IC A L M O D E L IftE ^ flg m S F P O lM T » « (i o ,t q 2 0 X 2 0 V « o l
hbiuY 4 *(10 , 1 g 20 x 2 0 W75j
PHYSICAL MODEL IteFERENcbE froiNf » «( 1 o,i o) 20 « 20 W «o|
Figure 6.4 Reference point # 4 for IES, Gillette and physical models.
89
PREFERENCE POINT * »(10,1«) ZO X ao X 4Q|
PHYSICAL MODEL
PREFERENCE POINT » 8(10,11) 20 X 20 X
Figure 6.5 Reference point # 5 for IES, Gillette and physical models.
90
PREFERENCE POINT # S(19,1) 20 X 20 X 40|
GILLETTE MODEL *------------------------------1 ----------------------
Figure 6.6 Reference point # 6 for IES, Gillette and physical models.
91
IES MODEL
REFERENCE POIKH # 7(1 »,10» 20 X 20 X 4Q|
REFERENCE PONT # 7|1*.10( 20 X SO X 40)
GILLETTE MODEL
PHYSICAL MODEL
Iftfcf f c R i^ C e p o i n t » 7 j i a ,i o ) g o K j p y * o |
Figure 6.7 Reference point # 1 for IES, Gillette and physical models.
92
JUNE 21 AT KOO
IES MODEL
JUNE 21 AT KOO
GILLETTE M ODEL/
PHYSICAL MODEL
Figure 6.8 June 21 at 9:00 for the IES, Gillette, and physical models.
93
DECEMBER 21 AT K M
IES MODEL
GILLETTE MODEL/
D ECEM BER 21 AT 9:00
PH YSICAL M O D E L
Figure 6.9 December 21 at 9:00 for the IES, Gillette, physical model.
94
DECEMBER 21 AT 12:00
IES MODEL
DECEMBER 21 AT 12:00
GILLETTE MODEL/
/"
"'I
PHYSICAL MODEL
DECEMBER 21 AT 1 2 0 0
Figure 6.10 December 21 at 12:00 for the IES, Gillette, and physical models.
95
REFERENCES:
1) Liang, June.
Computer Modeling o f Cumulative Daylight Availability Within an Urban
Site. Los Angeles, University of Southern California, 1993.
2) Milne, Murray.
Climate Consultant software. University of California, Los Angeles, 1991.
3) Schiler, Marc.
Solaris, v.2.1. Computer software. University of Southern California,
1988.
4) University of California, Berkeley, Department of Energy,
DOE-2 Manual and computer so ftware.
96
7. Quantitative and Qualitative Illumination in
Spaces Adjacent to Atria
In this chapter, the study intends to measure the daylight performance in
the spaces adjacent to atria under clear sky conditions. The study intends to
measure the quantitative and qualitative available light in adjacent spaces in all
orientations using physical models.
The aim of this study is to provide insight on the relationship between
light and form. For example, in some cases light is less desirable and heat gain
is extremely undesirable. Therefore, the form of that space is different from
when the light is needed.
In spaces adjacent to atria, the study of the behavior of light is more
interesting than when there is sidelighting opened directly to the outside because
several variables play major factors in how the light behaves. There are direct
light, reflected light from the ground and the walls of the atrium, and the
ceiling of the space.
7.1 Description of Method
As was discussed in chapter 4.2, all the necessary factors in building
physical models were followed strictly to attain accurate results because when a
physical model is built properly, it provides results as it is in an actual building.
97
The same scale of the physical model used in chapter 5 was used in this
case, scale of 1” = l ’-O” . The atrium has the following geometry:
Width = 20’
Length = 20’
Height = 40’
The reflectance of the ground = 30 %
The net reflectance of the walls = 50 %
Adjacent spaces were attached to one side of the atrium with the
following geometry for each floor:
Width = 20’
Length = 20’
Height = 10’
The reflectance of the ground = 30 %
The reflectance of the walls — 50 %
The reflectance of the ceiling = 70 %
The atrium is considered as it is a four floor building. By rotating the
model in different orientations, we’ll be able to measure the available light in
all floors and all orientations on 21st of each month at the hours 9:00a.m.,
12:00 p.m ., and 3:00 p.m.
Since one side of the atrium was modeled with adjacent spaces, the other
three sides of the atrium should act as they are affecting the light in the built
98
spaces. Therefore, specular surfaces were modeled on these walls simulating the
fenestrations, and they were pasted on construction papers as most of the light
goes through the fenestrations will be reflected and absorbed within the
respective adjacent spaces (Figure 7.1).
,
Figure 7.1 Modeling specular surfaces on the opposite walls of the modeled adjacent
spaces.
Expecting that the amount of light in the first and the second floors will
be a bit low, a decision had to be made regarding the glazing area. Therefore, it
99
was safer to follow the Title-24 Energy Code. “The window area o f the
standard building is the greater o f (1) or (2): (1) the window area o f the
proposed building, or 40 % o f the gross exterior wall area o f the standard
building, whichever is less; or (2) 6 feet times the display perimeter. ” So, a
glazing area of 40 % for all four floors was used.
The model was built of foamcore panels and all the exterior walls are
covered by black construction paper to prevent any leak of light; all the joints
are taped, as well. The model was tested in a dark space using a light source to
correct any light leak. To facilitate placing the light sensors inside the adjacent
spaces, on of the atrium’s panels is removable. A grid pattern is drawn on the
ground of each floor to mark at which point the measurements are to be taken.
The measurements of light inside the adjacent spaces were taken at the
workplane height level (3 feet). To study the light in the entire space,
measurements were taken in different locations of each space ( Figure 7.2).
Because of the limited number of light sensors available, the
measurements for each space at a particular time had to be taken three times;
one time for each row. One sensor was totally outside the model to measure the
total horizontal illuminance which is used in calculating the daylight factor for
each reference point.
ATRIUM
Figure 7.2 Placing the light sensors inside the adjacent spaces to atria.
The same technique as is mentioned in chapter 5.1 is used for this study,
by tilting the model to simulate different solar times using the sundial diagram.
At the same time, a 286 compatible computer, LI-210S photometric sensors,
and a portable analog module were used to take the readings.
7.2 M easuring the Results
A. The model was tested under clear sky conditions in Los Angeles,
California, 34° N Latitude. The testing took place on the roof of Watt Hall of
the University of Southern California ( USC ) to avoid any obstructing objects.
1 0 1
B. Eighteen reference points were selected at the workplane height level
( 3 fe e t) and they were located as follows ( Figure 7.2):
1) Two rows of six sensors each at the sides of each space with three feet
distance between every two, and with one foot from the walls.
2) One row of six sensors at the center of each space and along the depth with
three feet distance between each two sensors.
C. A DATALIT computer program is used to measure the illumination level
from each sensor ( See 5.3.C ).
D. The illumination level was measured at the hours 9:00 a.m ., 12:00 p.m .,
and 3:00 p.m. on the 21st of each month using the sundial diagram for the same
latitude, and using the tilting device mentioned in chapter 5.
E. The adjacent spaces were photographed by using a 28 mm camera, and ASA
400 daylight film. The main objective of photographing the model is to provide
a permanent record of day lighting conditions inside the model; this technique
provides an evaluation method for observation of the quality of light to other
design options.
7.3 Analysis
All the output data is plotted in graphs showing the geometry of each
space; the x-axis and the y-axis show the geometry ( width and length ), the z-
axis shows the daylight factor in that space at a particular time of the year.
1 0 2
As expected, it was found that the DF closer to the fenestration is higher
than the points further from the fenestrations. However, the points at the rear
wall of each space receive more light than the points five feet from the same
wall. Those points get reflected light from the comer walls. This has not been
discussed in the general literature. Most of the daylight measuring methods
indicated that the measured points at the rear of a space receive the lowest DF.
That is because the measured points are not taken very close to the rear wall of
the space (five feet from the rear wall).
7.4 Sum m ary
After obtaining all the measurements from the physical model and after a
visual observation, the following was concluded:
A. South Facing
1. In summer, because of the higher exterior illumination, and because
of the higher altitude angle, the first and second floors, which were the biggest
concern, receive both good quality and quantity of light for most functions
without any need for artificial light ( The DF ranges in the first floor from 4 %
to 2 % at the back wall of the space at noon) (Figure 7.3). That amount of light
is sufficient for task work like reading. For the third and fourth floors, the
amount of light was absolutely enough (Figure 7.8); as a matter of fact, those
spaces do not receive direct sunlight in the summer except for the first two feet
103
from the sidelighting which is desirable in controlling heat in high temperature
climates. So, for all floors, a good quality and quantity of light is obtained in
summer at noon. However, in the first and the second floors, the amount of
light at the rear half of each floor at 9:00 a.m. and 3:00 p.m. requires artificial
lights (Figure 7.5).
Figure 7.3 The first floor for the south facing wall in June 21 at noon.
2. In winter and spring, the four floors receive sufficient DF at noon so
that there is no need to turn the light on (Figures 7.9 and 7.10). On the other
hand, at 9:00 a.m. and 3:00 p.m ., the DF for the first and second floors is still
not enough to light the entire space naturally. The first third of each space gets
enough natural light, but the rest of the space requires artificial lights (Figures
7.6 and 7.7).
104
B. North Facing
1. In summer, it was found that the fouth and third floors receive
sufficient illumination because most of the light received is reflected from south
facing wall at noon, from the east facing wall at 9:00 a.m ., and from the west
facing wall at 3:00 p.m. However, in the first floor, the light is reflected from
the ground of the atrium in addition to the surrounding walls (Figure 7.4); it
was found that the light received in the first floor at noon is about the same as it
is in the first floor in the south facing wall. The first third of the first and
second floors receive enough light at noon and at 9:00 a.m.
Figure 7.4 The first floor for the north facing wall in June 21 at noon.
105
2. In spring, it was found that the first and the second floors receive almost the
same amount of light in the upper two floors in the front half at noon and that
agrees with what was concluded from in section 5.4 (See figure 5.9).
Moreover, they receive almost the same illumination level as the lower two
floors in the south facing facade at 9:00 a.m. and 3: p.m .; however, the
available amount of light is still not sufficient in the rear half of those two
floors (Figure 7.15). In winter, the first and second floors do not receive
sufficient light at noon and at 9:00 a.m. (Figures 7.13 and 7.16).
C. East and W est
The two facades are combined because they act exactly the same at
noon, and completely the opposite at 9:00 a.m. and 3:00 p.m. At the first floor
for west facing wall, the space receives more illumination level at 9:00 than the
first floor for the east facing wall and that agrees with the conclusions from
section 5.3 (See figure 5.9); that occurs for the first, second and third floors
only (Figures 7.17 - 7.22).
The same thing occurs, as well, at the first floor for the east facing wall
at 3:00 p.m. where high illumination levels received.
As a final conclusion, it was found that the north facing facade in an
atrium receives more illumination level than any other case, not only that, but
similar for the east and west facig facades, where a lot of reflected light
106
received in different ways and different times of the days. The facing walls, as
well, protect the other walls feom the direct sunlight which causes glare and
high energy consumption. Thus atria are good examples in terms of quality and
quantity of light as mentioned in section 1.3.
107
SOUTH JUNE £> •
SOUTH 3rd, JUNE & 9
SOUTH 2nd. JUNE & 9
SOUTH 1st. JUNE @ •
Figure 7.5 South facing wall in the atrium; June 21 at 9:00 A.M.
108
SOUTH, MARCH @ 9
SOUTH 3rd. MARCH ® 9
SOUTH. 2nd. MARCH @ 9
SOUTH 1st. MARCH @ i 9
Figure 7.6 South facing wall in the atrium; March 21 at 9:00 A.M.
109
SOOTH 4tft. DECEMBER @ 9
SOUTH 3rd. DECEMBER 6 9
SOUTH 2nd. DECEMBER & 9
SOUTH 1 H DECEMBER ® 9
Figure 7.7 South facing wall in the atrium; December 21 at 9:00 A.M.
110
SOUTH 4tfv JUNE 0 1 2
SOUTH 3rd, JUNE & 12
SOUTH 2nd, JUNE ® 12
SOUTH 1 *t JUNE & 12
Figure 7.8 South facing wall in the atrium; June 21 at noon.
S O U T H S MARCH & 12
SOUTH * d . MARCH @ 12
SOUTH 2nd. MARCH @ 12
SOUTH 1st. MARCH @ 12
Figure 7.9 South facing wall in the atrium; March 21 at noon.
112
SOUTH DECEMBER & 12
SOUTH 3rd. DECEMBER © 12
SOUTH 2nd. DECEMBER © 12
SOUTH 1 H DECEMBER © 12
Figure 7.10 South facing wall in the atrium; December 21 at noon.
113
NORTH 4th, JUNE (g > >
NORTH a>d. JUNE <& 9
NORTH 2nd. JUNE <® 9
NORTH 1 H JUNE & 9
Figure 7.11 North facing wall in the atrium; June 21 at 9:00 A.M.
114
NORTH 4th, MARCH @ 9
7 ^ N
NORTH 3rd. MARCH @ •
NORTH, 2nd, MARCH @ 9
NORTH 1 s t MARCH @ »
Figure 7.12 North facing wall in the atrium; March 21 at 9:00 A.M.
115
NORTH «h, DECEMBER & 9
NORTH 2nd. DECEMBER & 9
NORTH 1 St. DECEMBER ® 9
f
Figure 7.13 North facing wall in the atrium; December 21 at 9:00 A.M.
116
NORTH. 4th, JUNE & 12
NORTH 3»d. JUNE fl> 12
NORTH 1 s t JUNE @ 12
Figure 7.14 North facing wall in the atrium; June 21 at noon.
117
NORTH MARCH & 12
NORTH. 3rd. MARCH 0 12
Figure 7.15 North facing wall in the atrium; March 21 at noon.
118
NORTH, 40 % , DECEMBER & 12
NORTH, 3rd. DECEMBER @ 12
NORTH. 2nd. DECEMBER & 12
1
£
NORTH, t a t DECEMBER @ 12
£
Figure 7.16 North facing wall in the atrium; December 21 at noon.
119
EAST, JUNE @ »
Figure 7.17 East facing wall in the atrium; June 21 at 9:00 A.M.
120
EAST, 4m, MARCH @ 9
Figure 7.18 East facing wall in the atrium; March 21 at 9:00 A.M.
121
Figure 7.19 East facing wall in the atrium; December 21 at 9:00 A.M.
122
Figure 7.20 East facing wall in the atrium; June 21 at noon.
123
EAST, 4th. MARCH < g > 12
EAST. 1st. MARCH © 12
Figure 7.21 East facing wall in the atrium; March 21 at noon.
124
EAST. * h , DECEMBER @ 12
EAST. 3rd. DECEMBER @ 12
EAST. 2nd. DECEMBER @ 12
EAST. 1 s t DECEMBER @ 1 2
Figure 7.22 East facing wall in the atrium; December 21 at noon.
125
WEST, 3rd, JUNE < 5 > 12
Figure 7.23 West facing wall in the atrium; June 21 at noon.
126
WEST, mh, MARCH @ 12
WEST, 3rd. MARCH 0 12
WEST. 2nd. MARCH @ 12
WEST. 1st. MARCH 0 12
Figure 7.24 West facing wall in the atrium; March 21 at noon.
127
Figure 7.25 West facing wall in the atrium; December 21 at noon.
128
8. Conclusions
From the studies in chapters 5 and 7, it was found that an atrium is a
good solution in sunny and hot climates because it provides a good quality of
light which is mostly either diffused or reflected or both, and most of the
windows do not give view of the direct sun and consequently that does not
produce disability glare which can be observed by shielding the sun with one’s
hand.
As mentioned in section 1.3.1, an atrium provides a cool air by
behaving as a shading device especially in high temperature climates, high
humidity, and high sunshine.
An atrium provides privacy to dwellings because it is free from being
overlooked by neighbors, and it is sheltered from the wind. It shuts off from the
public noise, as well. Therefore, an atrium provides a good quality of privacy
in a single family dwelling.
1) Graphing the daylight factor in the spaces adjacent to atrium, shown
in chapter 7, shows that some spaces do not get a sufficient illumination level to
function properly and part of these spaces need artificial lights. From an
architectural perspective, there is a strong relationship between light and form
in a space; therefore, the adjacent spaces could be formed upon the available
functional light in each floor ( Figures 8.1 and 8.2).
129
This allows us to arrange the function in the space in the entire building
without using any artificial light which saves a lot of energy. At the same time,
an architectural perspective is highly considered to relate the form of a building
to the behavior of light.
Wi
Figure 8.1 Applying the DF on the building.
F u n ctio n a l DF
Limit
2nd
•tlh
3rJ
2 n d
A T R T R IM
1st
Figure 8.2 The building after it is form ed upon the available light.
130
2) To improve the quantity of light in the first and second floors, the
total glazing area could be increased. At the same time, the total glazing area in
the third and fourth floors should be decreased. However, the total glazing area
for all floors should remain the same. The total glazing area in testing the model
mentioned in chapter 7 is 40 % of the total area of the wall (Figure 8.3). The
glazing area could be changed to the following (Figure 8.4):
1) The first floor 60 %
2) The second floor 50 %
3) The third floor 30 %
4) The fourth floor 20 %
That recommended atrium still keeps the same overall glazing area as the
study case used in chapter 7. The idea behind that is that the function of the
cooling and heating systems will remain the same for the entire building. The
glazing area in for the forth and third floors is small and that will not allow
enough light to reach the rear of the space if the sidelighting is centered in the
middle of the wall. Therefore, sidelightings should be raised so that the light
reflects from the ceiling of the space and bounces more light to the rear of the
space.
1 3 1
Figure 8.3 40% glazing area.
is.
Figure 8.4 Protrated glazing area.
3) Another important factor to improve the illumination level in adjacent
spaces is changing the reflectance of the walls. The reflectance of the atrium’s
walls could be raised to a higher reflectance and consequently the amount of
light in the adjacent spaces will increase; wall refletances of 50-70% are
desirable. Increasing the reflectance of the walls in the adjacent spaces will
increase the illumination level. However, incresing the reflectance of the
atrium’s walls will increase the luminance, which may subsequently increase
glare which is definitely undesirable. Therefore, the reflectance of the walls of
the atrium should be carefully chosen.
4) Another way of increasing the quantity of light is using light
reflectors to supply more light to the bottom two floors. The reflectors could be
any high reflectance and specular material; they should be tilted toward the
areas which require more light ( Figure 8.5).
132
The depth of the reflectors should be carefully chosen so that they do not
block the light coming to the other sides. As a matter of fact, using reflectors is
practical for not only providing and supporting the bottom floors with more
light, but protecting the upper floors from the direct sunlight. A good example
for using light reflectors is the Tennessee Valley Authority building (T.V.A.).
4 t h
3rd
Figure 8.5 Using reflectors to improve the illumination level.
5) Unlike all other measurement methods for interior spaces, the
physical model showed that the points immediately adjacent to the rear wall of
the space receive more illumination than the points five feet from the rerar wall
which is the traditional measurement station. This is because of the light
reflected from the rear wall which has a reflectivity of 50%. The lumen method
133
calculates a minimum point five feet from the rear wall and that agrees with the
measured points from the physical model as they are the lowest points, but as
we get closer to the rear wall the illumination level actually gets higher again
(Figure 8.6 and 8.7).
DF
Figure 8.6 Daylight factor using the lumen method.
DF
Figure 8.7 Daylight factor in the physical model.
134
6) From figures 7.5-7.25, it was concluded that the third and the fourth
floors receive sufficient illumination level in all orientations, but not in the first
and the second floors. Therefore, an atrium’s geometry of 1: 1: 1 provides good
quality and quantity of light. If the same atrium’s geometry (1: 1: 2) is used,
the first floor could be used as an entrance to the building, and the second floor
could be used for functions where rerading tasks is not required.
135
9. Future Work
1) Using the same physical model used for testing in chapter 7, the east -
west direction of the atrium could be extended to double the distance of the
north-south direction to come up with an atrium’s geometry of 1:2:2. Then,
measure the illumination level in each floor and in each orientation and compare
it with the output data for the atrium’s geometry of 1:1:2 analyzed in chapter 7
(Figure 9.1).
2) Extending the atrium in the north-south direction by doubling the
distance of the north-south direction of the atrium to come up with an atrium’s
geometry of 2:1:2 (Figure 9.2). Then, measure the amount of light arrives to
each floor in each orientation and compare it with the measurements from
chapter 7 and the measurements from case (1) (Figure 9.1).
so • S O ’
N
20 ’
+
20 ’ 4 - 0 ’
Figure 9.1 Extending in east-west direction. Figure 9.2 Extending north-south.
136
3) Using different reflectance materials for the walls of the atrium and
the walls of the adjacent spaces should be considered as a future work because it
is expected that the higher the reflectivity of the materials, the higher the
illumination level. It will be important, however, to test for glare.
4) The LIGHTSUM computer program which was written by a former
graduate student at University of Southern California ( USC ) is somewhat
useful to predict light in atria. As it was noticed that most of the results from
the measurements taken inside the atrium ( chapter 5 ) are too much related to
the measurements obtained from the adjacent spaces. Therefore, the reflectance
algorithm shuld be corrected. To verify whether the algorithm was in fault or
not, running a very low atrium wall is needed.
137
APPENDIX A Daylight Calculation Using Lumen Method
Dale
Solar Time*
AM : 6 7 a 9 10 11 NoOrt
PM: 6 5 A 3 2 1
J u n e 21 12
24 3 7 5 0 6 3 7 5 8 3
ALTITUDE M ar.-S ep t. 21 — 13 26 3 6 4 9 57 8 0
D ec. 21 — — 12 21 2 9 3 5 37
J u n e 21 111 104 99 9 2 84 6 7 0
AZIMUTH M a r.-S ep t. 21 8 3 74 64 49 2 6 0
D ec. 21 — 54 44 32 17 0
J u n e 21 13 25 37 50 62 74 7 9
ALTITUDE M ar.-S ep t. 21 — 12 25 36 4 6 53 56
D ec. 21 — — 9 18 26 31 3 3
J u n e 21 11 0 103 95 90 78 58 0
AZIMUTH M a r.-S ep t. 21 82 72 61 4 6 26 0
Dec. 21 — — 54 43 3 0 16 0
Ju n e 21 14 2 6 37 4 9 61 71 75
ALTITUDE M a r.-S ep t. 21 — 12 2 3 34 4 3 50 52
D ec. 21 — — 7 16 23 27 28
J u n e 21 109 101 9 0 8 3 70 4 6 0
AZIMUTH M ar.-S ep t. 21 81 71 5 6 4 3 2 4 0
Dec. 21 — — 54 43 3 0 16 0
J u n e 21 16 26 3 6 4 9 6 0 6 6 71
ALTITUDE M a r.-S ep t. 21 — 11 2 2 32 4 0 4 6 4 8
Dec. 21 — — 4 13 19 2 3 2 5
J u n e 21 10 6 9 9 89 7 8 6 3 39 0
AZIMUTH M ar.-S ep t. 21 8 0 69 5 6 41 22 0
D ec. 21 — — 53 4 2 2 9 15 0
J u n e 21 17 27 37 48 57 6 5 67
ALTITUDE M ar.-S ep t. 21 — 10 20 30 3 7 4 2 44
D ec. 21 — — 2 10 15 2 0 21
J u n e 21 107 97 86 74 5 8 34 0
AZIMUTH M ar.-S ep t. 21 79 67 54 3 9 21 0
D ec. 21
—
— 52 41 28 14 0
4B°N
Ju n e 21 17 27 37 47 56 6 3 65
ALTITUDE M ar.-S ep t. 21 — 10 20 29 3 6 4 0 4 2
D ec. 21 — — 1 8 14 17 19
J u n e 21 10 6 95 8 5 72 5 5 31 0
AZIMUTH M a r.-S ep t. 21 79 67 53 3 8 2 0 0
D ec. 21 — — 52 41 28 14 0
A. 1 Solar Altitude and Azimuth.
(Source: Schiler, Marc. Simplified Design of Building Lighting).
HOMZOMttL FULL SKVI
Z '
I *
Is
i
>
» w s o 40 » 1 0 1 0 0
S O L M A i m H M M O M U
A. OVERCAST SKY
HOMZONTM. JFtAL SKTJ _
P
is
V
«i
I# 40 JO 30 7 0
sous* altitude m degrees
B. CLEAR SKY
x:
S'
1 5
I s
&
i
0 0 ( 0 to 40 so 10 2 D 0 1 0
H O A S O ^T M . ( f u u . SKY)
i
S 'p ,
13
<
i
I
I
60 « 1 0 0 40 3 0 SO 1 0 2 0 30
SOLAR ALTffUOE W DEGREES
C. CL EAR SAT- DIRECT SUN COMPONENT
SOLAR ALTITUDE (N OEGAEES
D. PARTLY CLOUDY SKY
*1 V &
*1
&
i
60
D ffE C T NORMAL
90
40
90
O
M 0 40 10 JO
E. PARTLY CLOUDY- DIRECT SUN COMPONENT
SOLAR ALT7TUDE FN DRCRSES
A.2 Illuminance of Vertical Surfaces.
(Source: Schiler, Marc. Simplified Design of Building Lighting).
139
Latitude (de
grees north)
Component
December 21 Match and September 21 June 21
BAM
4PM
10 AM
2PM
Noon
BAM
4 PM
10 AM
2PM
Noon
BAM
4PM
10 AM
2PM
Noon
Clear Dayf
3 0 Direct 9 42 55 34 72 87 52 86 99
Diffuse 8 12 13 11 14 15 13 15 16
Total 17 54 68 45 66 102 66 101 115
34 Direct 5 3 5 48 32 68 82 52 8 6 96
Diffuse 7 11 12 11 14 15 13 15 16
Total 2 4 6 60 43 62 97 65 101 114
38 Direct 3 29 41 29 64 77 53 8 4 96
Diffuse 6 10 12 11 14 16 13 15 16
Total 9 3 9 53 40 7 8 92 66 99 112
4 2 Direct 1 2 2 33 27 59 71 53 83 94
Diffuse 5 10 11 10 13 14 13 15 16
Total 6 32 44 37 72 86 66 98 110
48 Direct 0 16 25 24 54 65 53 80 91
Diffuse 4 9 10 10 13 14 13 15 1 6
Total 4 25 35 34 67 79 66 95 107
50 Direct 0 10 18 21 49 59 52 7 8 87
Diffuse 0 8 9 10 12 13 13 15 15
Total 0 16 27 31 61 72 65 93 1 02
Partly Cloudy Dayf
30 Direct 0 13 20 9 33 4 4 19 44 55
Diffuse 9 22 27 2 0 34 3 9 27 40 45
Total 9 35 47 2 9 67 83 46 84 100
34 Direct 0 9 16 8 30 40 20 44 54
Diffuse 7 20 25 19 33 38 27 40 45
Tdtal 7 29 41 27 63 78 47 84 99
38 Direct 0 6 12 7 27 36 20 43 52
Diffuse 6 17 22 18 31 36 28 39 44
Total 6 23 34 25 58 72 48 82 96
4 2 Direct 0 4 8 6 24 32 20 4 2 50
Difhise 4 15 19 17 29 34 28 39 43
Total 4 19 27 23 53 66 48 81 93
46 Direct 0 2 5 4 20 28 20 40 48
Diffuse 2 12 16 16 27 32 28 38 42
Total 2 14 21 20 47 60 48 78 90
50 Direct 0 1 2 3 17 24 19 38 45
Diffuse 0 10 13 15 25 29 27 37 41
Total 0 11 15 18 42 53 46 7 5 86
Overcast Day§
30 Direct 0 0 0 0 0 0 0 0 0
Diffuse 4 11 13 9 16 18 13 19 21
Total 4 11 13 9 16 18 13 19 21
34 Direct 0 0 0 0 0 0 0 0 0
Diffuse 4 9 12 9 15 18 13 19 21
Total 4 9 12 9 15 18 13 19 21
38 Direct 0 0 0 0 0 0 0 0 0
Diffuse 3 8 10 9 15 17 13 19 21
Total 3 8 10 9 15 17 13 19 21
42 Direct 0 0 0 0 0 0 0 0 0
Diffuse 2 7 9 8 14 16 13 18 20
Total 2 7 9 8 14 16 13 18 20
46 Direct 0 0 0 0 0 0 0 0 0
Diffuse 1 6 8 8 13 15 13 18 20
Total 1 6 8 8 13 15 13 18 20
50 Direct 0 0 0 0 0 0 0 0 0
Diffuse 0 5 6 7 12 14 13 17 19
Total 0 5 6 7 12 14 13 17 19
t Atmospheric Extinction Coefficient = 080. § Typical nonpredpltative minimum.
t Atmospheric Extinction Coefficient » 021. Atmospheric extinction coefficient Is the reciprocal of the optical air m ass times the natural
logarithm of the ratio of the extraterrestrial direct normal solar illuminance to the sea level direct normal solar IIluminance. Optical air m ass is the
ratio of the s a a level path length through the atmosphere toward the sun to the sea level path toward the zenith.
Vote: Muminanoe in kiioiux (multiply by 100 for foot candles}. Mora exact multiplier is 9 G L 9 .
A.3 Exterior Horizontal Illuminance.
(Source: Schiler, Marc. Simplified Design of Building Lighting).
140
M ATERIAL REFLECTANCE
Grass 06
Slate 08
Asphalt 07-15
Earth 10
Gravel 13-15
Concrete 20-40
Marble 45
White paint 60-75
Snow 65-75
A.4 Ground Reflectances.
(Source: Schiler, Marc. Simplified Design of Building Lighting).
Locations
Glazing Orientation
Vertical Sloped Horizontal
Clean areas 0.9 0.8 0.7
Industrial areas 0.8 0.7 0.6
Very dirty areas 0.7 0.6 0.5
A.5 Light loss factor for dirt accumulation.
(Source: Schiler, Marc. Simplified Design of Building Lighting).
1 4 1
A. luminance frorn an overcast sky, without window controls
C K
Room Length 6.1 M (20 FT) 9.1 M (30 FT) 1 25 M (40 FT) C eing Height 2.4 M (8 FT) 3 M (10 FI)
3.7 M (12
FT)
4.3 M (14 FT)
W al Reflectance
(per cent}
70 30 70 30 70 30
Wal Reflectance
(percent)
70 30 70 30 70 30 70 30
Room Room
Width Width
M FT M FT
6.1 20 .0276 .0251 .0191 .0173 .0143 .0137 6.1 20 .125 .129 .121 .123 .111 .0991 .0973
MAX 9.1 30 .0272 .0246 .0168 .0172 .0137 .0131 MAX 9.1 30 .122 .131 .122 .121 .111 .0945 .0973
12.2 40 .0269 .0246 .0162 .0171 .0133 .0130 152 40 .145 .133 .131 .126 .111 .111 .0973 .0962
6.1 20 .0159 .0117 .0101 .0087 .0061 .0071 6.1 20 .0908 .0982 .107 .115 .111 .105 .122
MID 9.1 30 4)058 0050 .0054 .0040 .0034 .0033 MIO 9.1 30 .156 .102 .0939 .113 .111 .111 .121 .134
12.2 40 .0039 0027 .0030 .0023 .0022 .0019 12.2 40 .106 .0946 .123 .107 .111 .111 .136 .127
6.1 20 .0087 .0053 .0083 .0043 .0050 .0037 6.1 20 .0906 .102 .0951 .114 .111 .111 .116 .134
MIN 9.1 30 .0032 .0019 J0029 0017 .0020 .0014 MIN 9.1 30 .0924 .119 .101 .114 .111 .125 .126
12.2 40 :0019 .0009 .0016 .0009 .0012 .0008 12.2 40 .111 .0926 .125 .109 .111 .133 .130
B. luminance from a dear sky without window controls
C K
Room Room
Width Width
M FT M FT
6.1 20 .0206 .0173 .0143 4)123 .0110 .0098 6.1 20 .145 .155 .129 .162 .111 .111 .101 .0682
MAX 9.1 30 .0203 .0173 D137 .0120 .0098 .0092 MAX 9.1 30 .141 .149 .125 .130 .111 .111 .0954 .101
12.2 40 .0200 .0168 .0131 .0119 4)096 .0091 12.2 40 .157 .157 .135 .134 .111 .111 .0964 J0991
6.1 20 .0153 .0104 4)100 .0079 4)063 .0067 6.1 20 .110 .128 .116 .126 .111 .111 .103 .106
MID 9.1 30 .0082 .0054 .0062 .0043 .0046 .0037 MID 9.1 30 .106 .125 .110 .129 .111 .111 .112 .120
12.2 40 .0052 .0032 .0040 4)028 4)029 .0023 12.2 40 .117 .118 .122 .118 .111 .111 .123 .122
6.1 20 .0106 .0060 .0079 4)049 4)067 4)043 &1 20 .105 .129 .112 .130 .111 .111 .111 .116
MIN 9.1 30 .0054 .0028 .0047 .0023 4)032 .0021 MIN 9.1 30 4)994 .144 .107 .126 .111 .111 .107 .124
12.2 40 .0031 .0014 .0027 .0013 .0021 4)012 12.2 40 .119 .116 .130 .118 .111 .111 .120 .118
C. luminance from a uniform ground without window controls
C K
Room Room
Width Width
M FT M FT
6.1 20 .0147 .0112 .0102 .0088 4)061 4)071 6.1 20 .124 .206 .140 .135 .111 .111 .0909 .0659
MAX 9.1 30 .0141 .0112 .0098 .0066 4)077 .0070 MAX 9.1 30 .182 .188 .140 .143 ,111 .111 .0918 .0676
12.2 40 .0137 .0112 .0093 .0086 .0072 .0069 1 22 40 .124 .182 .140 .142 .111 .111 .0936 .0679
6.1 20 .0128 .0090 4)094 .0071 4)073 4)060 6.1 20 .123 .145 .122 .129 .111 .111 .100 .0945
MID 9.1 30 .0083 .0057 .0062 .0046 4)050 .0041 MID 9.1 30 .0966 .104 .107 .112 .111 .111 .110 .106
12.2 40 .0055 .0037 4)044 .0033 4)042 .0026 12.2 40 .0790 .0786 .0999 .106 .111 .111 .118 .116
6.1 20 .0106 .0071 4)082 .0054 .0067 .0044 6.1 20 .0994 .108 .110 .114 .111 .111 .107 .104
MIN 9.1 30 .0051 .0026 •4)041 .0023 4X133 .0021 MW 9-1 30 .0816 .0822 .0984 .105 .111 .111 .121 .116
12.2 40 .0029 .0018 .0026 .0012 .0022 4)011 12.2 40 4)700 .0656 .0946 .0966 .111 .111 .125 .132
D. Iluminance front the “uniform sky” without diffuse window shades
C K
Room Room
Width Width
M FT M FT
6.1 20 .0247 .0217 .0174 .0152 .0128 .0120 6.1 20 .145 .154 .123 .128 .111 .111 4)991 .0964
MAX 9.1 30 .0241 .0214 .0166 .0151 4)120 .0116 MAX 9.1 30 .141 .151 .126 .128 .111 .111 4)945 .0964
12.2 40 .0237 .0212 .0161 .0150 .0118 .0113 12 2 40 .159 .157 .137 .127 .111 .111 .0973 .0964
6.1 20 .0169 .0122 .0110 .0092 .0089 .0077 6.1 20 .101 .118 .115 .125 .111 .111 .101 .110
MID 9.1 30 .0078 .0060 .0067 4)046 .0044 .0041 M ID 9.1 30 .0952 .113 .105 .122 .111 .111 .110 .122
1 2 2 40 4)053 4)033 .0039 .0026 .0029 .0024 1 2 2 40 .111 .105 .124 .107 .111 .111 .130 .124
6.1 20 .0106 .0066 .0080 .0052 .0063 .0047 6.1 20 .0974 .111 .107 .121 .111 .111 .112 .119
MIN 9.1 30 4)047 .0026 .0042 .0023 .0029 .0020 M IN 9.1 30 .0956 .125 .103 .117 .111 .111 .115 .125
122 40 .0027 .0013 .0022 4)012 .0018 .0011 122 40 .111 .105 .125 .111 .111 .111 .133 .124
A.6 Coefficient of Utilization (C & K).
(Source: Schiler, Marc. Simplified Design of Building Lighting).
142
Fc
400
3 0 0
>200
>100
1 000
9 5 0
9 0 0
8 5 0
8 0 0
7 5 0
70 0
65 0
60 0
5 5 0
500
4 50
400
3 80
3 6 0
34 0
32 0
30 0
280
26 0
24 0
220
200
190
180
170
160
150
140
130
TOIX B:
P e rc e n ta g e o f h o u rs b e tw e e n 9:00 a n d 17:00-
for w h ic h le v e ls o f illu m in a n c e will be
av ailab le o r e x c e e d e d .
15.000
14.000
13.000
1 2 .0 0 0
± 1 1 ,0 0 0
10,000
9 .5 0 0
9 .0 0 0
8 .5 0 0
8.000
7 .5 0 0
7 ,0 0 0
6.5 0 0
F or p e rio d s o th e r th a n
9:00-17:00 s e e
T a b le 13.8
6,000
5 ,5 0 0
+ 5 ,0 0 0
4,500
4,000
- 3 ,8 0 0
3 ,6 0 0
- 3 ,4 0 0
3 .2 0 0
3 ,0 0 0
- 2.800
2 .6 0 0
2 ,4 0 0
2,200
2,000
C urves indicate m in im u m illum inance
available w ithin a sp ecified percen tag e
of daytim e w orking h o u rs, on a horizontal
plane o u td o o rs w h en th e su n is obscured.
-- 1,800
This is so m e tim e s referred to as th e
R eference v alue of external illum inance
-- 1,600
1.400
30 40 50
L atitu d e (°N o r S)
1 External illuminance available for percentage of workday.
(Source: Schiler, Marc. Simplified Design of Building Lighting, 1992)
143
Minimum daylight factor (%)
% W id th of
w in d o w
10.0
9.0
8.0
7.0
6.0
5.0
4.5
4.0
3.5
3.0
2.5
R o o m le n g th
- - - - 2 10.0 m . (3 3 ft.)
4 .5 -7 m . (1 5 -2 3 ft.)
C eiling h eig h t: 2.7 0 -4 .5 0 m . (9-15 ft.)
90% W d
60% Wd
30% Wd
2.0
1.8
1.6
1.4
1.0
0.9
0.8
0.7
0.6
0.5
0 .4
0.3
0.2
2 H 3H 4H 5H
Room depth —►
Table B.2 Allowable room depth for minimum daylight factor.
(Source: Schiler, Marc. Simplified Design of Building Lighting)
144
APPENDIX C
The record length of the TMY format is 132 characters.
Column Contents
1-5 WBAN station number.
6-15 Solar time at end of hourly solar observation.
6-7 Year of observation (00-99 = 1900-1999)
8-9 Month of observation ( 01-12)
10-11 Day (01-31)
12-15 End of the hour of observation 0001-2400 ( hours and
minutes).
16-19 Local standard time in hours and minutes corresponding to the
solar time given above.
20-23 Extraterrestrial radiation KJ/m2 based on solar constant =
1377 J/m2.
24-28 Direct normal radiation KJ/m . Column 24 is a model flag;
columns 25-28 contain the data.
29-33 Diffuse radiation KJ/m2.
34-38 Net radiation.
39-43 Tilt radiation.
44-48 Observed radiation.
49-53 Engineering corrected radiation.
54-58 Standard year corrected radiation in KJ/m2. Column 24 is a model
flag; columns 55-58 contain the data.
59-68 Additional radiation data.
69-70 Minutes of sunshine for local standard hour most closely matching
the solar hour.
145
Column Content
71-72 Time of surface observation ( hour) 00-23. This is the local
standard hour of the TD 1440 observation closest to the mid-point
of the hour for which solar data was taken.
73-76 Ceiling height in meters times ten.
77-81 Sky condition.
82-85 Visibility in hundreds of meters ( tenth of kilometers ).
86-93 Weather flag-- used to set the rain and snow flags for the weather
file. These flags are never used by the program.
94-98 Atmospheric pressure reduced to sea level in tenth of millibars
( 08000 to 10999).
99-103 Station atmospheric pressure in tenth of millibars.
104-107 Dry-bulb temperature in tenth of °C ( -700 - 0600).
108-111 Dew point temperature in tenth of °C.
112-114 Wind direction in degrees.
115-118 Wind speed in tenth of m/s (0000-1500 ).
119-120 Total sky cover ( tenth) ( 00-10).
121-122 Total opaque sky cover ( tenth).
123 Snow cover flag; 0 = none, 1= some.
124-132 Blank.
146
APPENDIX D
RP # U TIME=> 9:00 10:00 11:00 12:00 13:00 14:00 15:00
1 (1,10) Klux 2.34 2.93 3.71 3.95 3.88 3.34 2.99
fc 217 272 345 367 360 310 278
DF % 4 4 5 6 6 6 6
2 (1,19) 2.6 3.13 3.67 3.72 3.88 3.64 3.47
242 291 341 346 360 338 322
5 5 5 5 6 6 7
3 (10,1) Klux 2.9 3.57 4.37 4.75 4.62 3.76 3.14
fc 269 332 406 441 429 349 292
DF % 5 5 6 7 7 6 7
4 (10.10) 3.00 3.58 4.35 4.68 4.68 3.83 3.24
279 333 404 435 435 356 301
5 5 6 7 7 6 7
5 (10.19) Klux 2.59 3.08 3.52 3.52 3.57 3.2 2.84
fc 241 286 327 327 332 297 264
DF % 5 5 5 5 5 5 6
6 (19,1) 2.07 2.38 2.81 3.00 3.00 2.38 1.83
192 221 261 279 279 221 170
4 4 4 4 4 4 4
7 (19,10) Klux 3.33 3.80 4.38 4.74 4.81 3.89 3.01
fc 309 353 407 440 447 361 280
DF % 6 6 6 7 7 7 6
Total Horizontal 5249 6061 6601 6538 6379 5488 4438
D .l Data collected from t tie physical model for J ranuary & November 21st.
RP# U TIME=> 9:00 10:00 11:00 12:00 13:00 14:00 15:00
1 (1,10) Klux 2.53 3.50 5.01 5.81 5.33 4.27 3.50
fc 235 325 465 540 495 379 325
DF % 4 5 6 7 7 6 6
2(1.19) 2.91 3.72 4.69 5.09 5.15 4.83 4.20
270 346 436 473 478 449 390
5 5 6 6 7 7 7
3 (10,1) Klux 3.14 4.00 5.36 6.53 6.29 4.80 3.51
fc 292 372 498 607 584 446 326
DF % 5 5 7 8 8 7 6
4 (10.10) 3.29 4.35 5.71 6.88 6.64 5.15 3.81
306 404 530 639 617 478 354
5 6 7 8 8 7 7
5 (10.19) Klux 3.01 3.93 4.54 4.90 4.83 4.31 3.46
fc 280 365 422 455 449 400 321
DF % 5 5 6 6 6 6 6
6(19,1) 2.23 2.67 3.35 4.07 4.13 3.12 2.06
207 248 311 378 384 290 191
4 4 4 5 5 5 4
7 (19.10) Klux 3.68 4.55 5.59 6.72 6.93 5.31 3.54
fc 342 423 519 624 644 493 329
DF % 6 6 7 8 9 8 6
Total Horizontal 5886 6776 7397 7572 7349 6442 5249
D.2 Data collected from the physical model for February & October 21st.
147
RP#U TIME=> 9:00 10:00 11:00 12:00 13:00 14:00 15:00
1 (1.10)
Klux 3.01 4.38 7.69 10.44 7.80 5.97 4.47
fc 280 407 714 970 725 555 415
DF % 4 5 9 1 1 9 7 7
2 (1.19) 3.52 4.93 7.76 10.14 7.52 7.29 5.71
327 458 721 942 699 677 530
5 6 9 1 1 8 9 9
3 (10,1) Klux 3.64 4.98 6.92 9.41 8.62 6.38 4.29
fc 338 463 643 874 801 593 399
DF % 5 6 8 10 10 8 6
4(10.10) 4.10 5.72 8.09 12.17 10.66 7.64 4.97
381 531 752 1131 990 710 462
6 7 9 13 12 10 8
5 (10.19) Klux 3.90 5.69 7.16 9.48 7.98 6.96 4.83
fc 362 529 665 881 741 647 449
DF % 5 7 8 10 9 9 7
6 (19,1) 2.60 3.35 4.22 5.67 5.67 4.19 2.41
242 311 392 527 527 389 224
4 4 5 6 6 5 4
7 (19.10) Klux 4.53 6.04 7.57 10.75 11.25 8.20 4.32
fc 421 561 703 999 1045 762 401
DF % 6 7 8 12 13 10 7
Total Horizontal 6729 7619 8351 8685 8256 7444 6140
D.3 Data collected from the physical model for March & September 21st.
TIME=> 9:00 10:00 11:00 12:00 13:00 14:00 15:00
1 (1.10) Klux 3.55 5.43 11.65 13.37 10.73 8.23 5.89
fc 330 504 1082 1242 997 765 547
DF % 4 6 12 13 11 9 8
2(1.19) 4.25 6.73 144.9 146.1 12.78 10.93 7.84
395 625 13463 13575 1187 1015 728
5 8 146 143 13 12 1 1
3 (10,1) Klux 4.50 6.24 8.64 10.10 10.10 8.13 5.48
fc 418 580 803 938 938 755 509
DF % 6 7 9 10 10 9 7
4 (10.10) 5.20 7.69 11.66 15.25 15.43 11.56 6.71
483 714 1083 1417 1433 1074 623
7 9 12 15 16 13 9
5 (10.19) Klux 5.03 8.14 13.21 113.6 112.4 12.74 6.76
fc 467 756 1227 10550 10444 1184 628
DF % 6 9 13 111 113 14 9
6 (19,1) 3.15 4.17 5.23 6.06 6.36 4.88 2.80
293 387 486 563 591 453 260
4 5 5 6 6 5 4
7 (19,10) Klux 5.73 8.00 10.12 12.87 15.71 12.16 5.37
fc 532 743 940 1196 1459 1130 499
DF % 7 9 10 13 16 14 7
Total Horizontal 7365 8303 9210 9496 9210 8303 6904
D.4 Data collected from the physical model for April & August 21st.
148
RPtf U TIME=> 9:00 10:00 11:00 12:00 13:00 14:00 15:00
1 (1.10) Klux 3.75 6.94 96.42 95.92 11.35 9.76 7.91
fc 348 645 8957 8911 1054 907 735
DF % 5 7 94 90 1 1 10 10
2 (1,19) 4.60 8.55 147.8 149.3 14.96 12.62 10.14
427 794 13732 13867 1390 1172 942
6 9 144 140 14 13 13
3 (10,1) Klux 4.93 7.88 9.80 9.98 10.06 10.16 7.64
fc 458 732 910 927 935 944 710
DF % 6 8 10 9 10 1 1 10
4(10.10) 5.72 10.23 14.03 99.07 98.20 15.83 9.67
531 950 1303 9204 9123 1471 898
7 1 1 14 93 94 16 12
5 (10.19) Klux 5.54 10.53 15.32 116.2 115.9 15.74 9.29
fc 515 978 1423 10799 10764 1462 863
DF % 7 1 1 15 109 111 16 12
6 (19.1) 3.49 5.09 5.78 5.83 6.07 5.81 3.44
324 473 537 542 564 540 320
4 5 6 5 6 6 4
7 (19.10) Klux 6.39 9.83 11.53 13.29 12.78 121.9 7.15
fc 594 913 1071 1235 1187 11327 664
DF % 8 10 1 1 12 12 126 9
Total Horizontal 7635 8860 9544 9910 9671 8971 7444
D.5 Data collected from the physical model for May & July 21st.
RP#U TIME=> 9:00 10:00 11:00 12:00 13:00 14:00 15:00
1 (1,10) Klux 4.11 8.50 99.54 97.89 11.30 10.09 8.53
fc 382 790 9247 9094 1050 937 792
DF % 5 9 95 91 1 1 10 10
2 (1.19) 5.09 10.03 146.9 143.5 14.41 12.74 10.34
473 932 13643 13329 1339 1184 961
6 10 141 133 13 13 13
3 (10,1) Klux 5.57 9.86 11.02 10.90 11.52 11.88 9.46
fc 517 916 1024 1013 1070 1104 879
DF % 7 10 1 1 10 11 12 1 1
4 (10,10) 6.52 12.30 15.01 100.3 99.78 16.64 11.29
605 1143 1394 9319 9270 1546 1049
8 13 14 93 93 17 14
5 (10.19) Klux 6.21 11.86 15.59 112.6 112.2 15.34 9.91
fc 577 1102 1448 10462 10426 1425 921
DF % 7 12 15 104 105 16 12
6 (19,1) 3.94 5.96 6.12 5.91 7.42 8.56 4.20
366 554 569 549 689 795 390
5 6 6 5 7 9 5
7 (19.10) Klux 7.15 11.19 12.02 13.53 121.7 123.4 8.63
fc 664 1040 1117 1257 11307 11467 802
DF % 8 11 12 13 114 126 10
Total Horizontal 7842 9099 9703 10037 9942 9099 7651
D.6 Data collected from the physical model for June 21st.
149
RP#U TIME=> 9:00 10:00 11:00 12:00 13:00 14:00 15:00
1 (1,10) Klux 2.27 2.74 3.37 3.50 3.39 3.09 2.80
fc 211 255 313 325 315 287 260
DF % 4 4 5 5 5 6 6
2 (1,19) 2.48 2.87 3.36 3.40 3.46 3.36 3.19
230 267 312 316 321 312 296
5 5 5 5 5 6 7
3 ( 10,1) Klux 2.83 3.33 4.05 4.29 4.07 3.51 2.96
fc 263 309 376 399 378 326 275
DF % 5 5 6 7 6 6 7
4 (10.10) 2.88 3.35 3.98 4.10 4.05 3.52 3.00
268 311 370 381 376 327 279
5 5 6 6 6 6 7
5 (10.19) Klux 2.45 2.78 3.18 3.14 3.14 2.93 2.60
fc 228 258 295 292 292 272 242
DF % 5 5 5 5 5 5 6
6 (19,1) 2.00 2.23 2.58 2.74 2.62 2.19 1.74
186 207 240 255 243 203 162
4 4 4 4 4 4 4
7 (19.10) Klux 3.18 3.54 4.00 4.18 4.10 3.51 2.81
fc 295 329 372 388 381 326 261
DF % 6 6 6 6 6 6 7
Total Horizontal 4963 5679 6204 6108 5870 5138 4009
D.7 Data collected from the physical model for December 21st.
150
APPENDIX E Data collected from LIGHTSUM
RP# TIME 9:00 10:00 11:00 12:00 13:00 14:00 15:00
1(1.101 Klux 11.02 12.72 13.15 12.6 15.73 17.41 5.17
fc 1024 1182 1222 1171 1461 1617 480
DF % 29 24 22 20 26 33 25
2(1,19) 4.71 4.78 4.43 3.81 6.67 8.86 3.68
438 444 412 354 620 823 342
% 12 9 7 6 11 17 18
3(10.1) Klux 16.7 17.74 16.45 13.68 16.45 17.74 5.17
fc 1551 1648 1528 1271 1528 1648 480
DF % 43 34 27 21 27 34 25
4(10,10) 20.74 21.86 20 16.3 20 21.86 6.2
1927 2031 1858 1514 1858 2031 576
% 54 42 33 25 33 42 30
5(10,19) Klux 11.05 10.32 7.99 4.88 7.99 10.32 4.11
fc 1027 959 742 453 742 959 382
DF % 29 20 13 8 13 20 20
6(19,1) 14.57 15.32 14.03 11.47 11.78 11.24 3.67
1354 1423 1303 1066 1094 1044 341
% 38 29 23 18 19 22 18
7(19.10) Klux 16.71 17.41 15.73 12.6 13.15 12.72 4.1
fc 1552 1617 1461 1171 1222 1182 381
DF % 43 33 26 20 22 24 20
Tntal horizontal
38.47 52.14 61.07 64.17 61.07 52.14 20.92
Table E .la IES Model January 21.
1(1,10) 7.51 9.66 10.4 10.21 12.65 13.32 11.31
698 897 966 949 1175 1237 1051
% 29 19 17 16 21 26 54
2(1.19) Klux 3.06 3.37 3.4 3.21 5.66 7.18 6.98
fc 284 313 316 298 526 667 648
DF % 12 9 7 6 11 16 22
3(10,1) 11.54 13.67 13.06 11.07 13.21 13.56 11.31
1072 1270 1213 1028 1227 1260 1051
% 45 36 27 21 26 31 35
4(10.10) Klux 14.36 16.89 15.89 13.18 16.01 16.6 13.91
fc 1334 1569 1476 1224 1487 1542 1292
DF % 56 44 33 25 31 38 44
5(10.19) 7.53 7.74 6.25 4.07 6.72 8.29 7.92
700 719 581 378 624 770 736
% 29 20 13 8 13 19 25
6(19,1) Klux 10.05 11.78 11.12 9.3 9.58 8.87 6.96
fc 934 1094 1033 864 890 824 647
DF % 39 31 23 18 19 20 22
7(19.10) 11.54 13.4 12.48 10.22 10.68 10 7.88
1072 1245 1159 949 992 929 732
% 45 35 26 19 21 23 25
Total H orizontal
25.54 38.40 48.06 52.49 51.00 43.69 31.87
Table E. lb Gillette Model January 21.
151
RP# TIME 9:00 10:00 11:00 12:00 13:00 14:00 15:00
1(1.10) Klux 10.97 12.17 12.35 11.66 15.2 17.45 7.55
fc 1019 1131 1147 1083 1412 1621 701
DF % 22 19 17 15 20 27 24
2(1,19) 4.81 4.69 4.22 3.53 6.7 9.28 5.37
447 436 392 328 622 862 499
% 10 7 6 5 9 14 17
3(10,1) Klux 17.56 17.65 15.81 12.66 15.81 17.65 7.5
fc 1631 1640 1469 1176 1469 1640 697
DF % 35 27 21 16 21 27 24
4(10.10) 21.95 21.84 19.28 15.09 19.28 21.84 9.07
2039 2029 1791 1402 1791 2029 843
% 44 34 26 19 26 34 29
5(10.19) Klux 12.17 10.74 7.98 4.52 7.98 10.74 6
fc 1131 998 741 420 741 998 557
DF % 24 17 1 1 6 1 1 17 19
6(19,1) 15.38 15.29 13.51 10.61 11.03 10.7 5.04
1429 1420 1255 986 1025 994 468
% 31 24 18 14 15 16 16
7(19.10) Klux 17.73 17.45 15.2 11.66 12.35 12.17 5.66
fc 1647 1621 1412 1083 1147 1131 526
DF % 35 27 20 15 17 19 18
Total H orizontal 50.19 64.94 74.43 77.77 74.43 64.94 31.67
Table E.2a IES model, February 21.
1(1,10) 8.04 9.51 9.93 9.61 12.66 14.09 12.9
747 883 922 893 1176 1309 1198
% 22 19 17 15 20 26 31
2(1,19) Klux 3.31 3.4 3.17 2.85 5.74 7.82 8.19
fc 307 316 294 265 533 726 761
DF % 9 7 5 4 9 14 20
3(10,1) 13.14 14.01 12.83 10.44 13.16 14.24 12.79
1221 1302 1192 970 1223 1323 1188
% 37 28 22 16 21 26 31
4(10.10) Klux 16.47 17.39 15.67 12.45 16.02 17.53 15.82
fc 1530 1616 1456 1157 1488 1629 1470
DF % 46 35 26 19 26 32 38
5(10.19) 8.97 8.33 6.28 3.66 6.8 9 9.27
833 774 583 340 632 836 861
% 25 17 1 1 6 11 16 22
6(19,1) Klux 11.49 12.11 10.94 8.75 9.25 8.9 7.42
fc 1067 1125 1016 813 859 827 689
DF % 32 24 18 14 15 16 18
7(19,10) 13.28 13.85 12.32 9.61 10.35 10.08 8.49
1234 1287 1145 893 962 936 789
% 37 28 21 15 17 18 20
Total H rizontal
35.80 50.02 59.56 64.01 62.63 55.03 41.77
Table E.2b Gillette Model, February 21.
152
RP # TIME 9:00 10:00 11:00 12:00 13:00 14:00 15:00
1(1,10) Klux 9.71 10.54 10.54 9.76 13.54 16.18 17.16
fc 902 979 979 907 1258 1503 1594
DF % 15 13 12 11 15 21 27
2(1,19) 4.58 4.33 3.79 3.05 6.4 9.23 11.06
425 402 352 283 595 857 1027
% 7 6 4 3 7 12
0 0
3(10,1) Klux 16.78 16.17 13.96 10.59 13.96 16.17 16.78
fc 1559 1502 1297 984 1297 1502 1559
DF % 27 21 16 12 16 21 27
4(10.10) 21.11 20.13 17.1 12.6 17.1 20.13 21.11
1961 1870 1589 1171 1589 1870 1961
% 34 26 19 14 19 26 34
5(10,19) Klux 12.49 10.58 7.54 3.88 7.54 10.58 12.49
fc 1160 983 700 360 700 983 1160
DF % 20 14 9 4 9 14 20
6(19,1) 14.79 14.09 11.99 8.89 9.38 9.19 8.31
1374 1309 1114 826 871 854 772
% 24 18 14 10 1 1 12 13
7(19.10) Klux 17.17 16.18 13.55 9.76 10.54 10.55 9.71
fc 1595 1503 1259 907 979 980 902
DF % 27 21 15 1 1 12 14 15
Total Horizontal 62.91 78.11 87.81 91.14 87.81 78.11 62.91
Table E.3a IES Model, March 21.
1(1,10) 7.38 8.33 8.59 8.23 11.68 13.7 13.67
686 774 798 765 1085 1273 1270
% 16 13 12 11 15 20 25
2(1,19) Klux 3.24 3.12 2.58 2.52 5.7 8.09 9.13
fc 301 290 240 234 530 752 848
DF % 7 5 4 3 8 12 17
3(10,1) 13.14 13.09 11.52 8.93 12.03 13.7 13.38
1221 1216 1070 830 1118 1273 1243
% 28 21 16 12 16 20 25
4(10.10) Klux 16.6 16.36 14.14 10.64 14.69 16.96 16.69
fc 1542 1520 1314 988 1365 1576 1551
DF % 35 26 20 14 19 25 31
5(10,19) 10 8.36 6.03 3.22 6.68 9.24 10.27
896 777 560 299 621 858 954
% 20 13 8 4 9 14 19
6(19,1) Klux 11.56 11.38 9.86 7.49 8.18 8.07 7.13
fc 1074 1057 916 696 760 750 662
DF % 24 18 14 10 11 12 13
7(19.10) 13.46 13.1 11.16 8.23 9.18 9.21 8.25
1250 1217 1037 765 853 856 766
% 28 21 15 1 1 12 14 15
Total Horizontal 47.61 62.07 72.21 77.03 75.83 67.72 53.76
Table E.3b Gillette Model, March 21.
153
RP# TIME 9:00 10:00 11:00 12:00 13:00 14:00 15:00
111.10) Klux 7.42 7.99 7.87 7.07 10.85 13.62 15
fc 689 742 731 657 1008 1265 1394
DF % 10 9 8 7 1 1 15 20
2(1,19) 4.05 3.72 92.3 94.96 5.75 8.62 10.64
376 346 8575 8822 534 801 988
% 5 4 94 94 6 10 14
3(10,1) Klux 14.37 13.37 11.02 7.63 11.02 13.37 14.37
fc 1335 1242 1024 709 1024 1242 1335
DF % 19 15 1 1 8 1 1 15 19
4(10.10) 18.26 16.78 13.57 9.07 13.57 16.78 18.26
1696 1559 1261 843 1261 1559 1696
% 25 19 14 9 14 19 25
5(10,19) Klux 11.89 9.75 6.66 95.55 6.66 9.75 11.89
fc 1105 906 619 8877 619 906 1105
DF % 16 1 1 7 94 7 1 1 16
6(19,1) 12.8 11.77 9.54 6.44 6.95 6.87 6.21
1189 1093 886 598 646 638 577
% 17 13 10 6 7 8 8
7(19.10) Klux 15 13.62 10.85 7.07 7.87 7.99 7.42
fc 1394 1265 1008 657 731 742 689
DF % 20 15 1 1 7 8 9 10
Total Horizontal 74.01 88.85 98.29 101.5 98.29 88.85 74.01
Table E.4a IES model, April 21.
1(1,10) 5.91 6.55 6.93 6.68 10.04 12.25 12.71
549 608 644 621 933 1138 1181
% 10 9 8 7 11 15 19
2(1,19) Klux 3.15 2.93 79.01 80.87 5.72 8.13 9.42
fc 293 272 7340 7513 531 755 875
DF 5 4 93 89 6 10 14
3(10.1) % 11.66 11.15 9.62 7.16 10.18 12.05 12.26
1083 1036 894 665 946 1119 1139
20 15 1 1 8 1 1 15 18
4(10.10) m ux 14.84 14.02 11.83 8.47 12.43 14.95 15.3
fc 1379 1302 1099 787 1155 1389 1421
DF 25 19 14 9 14 19 23
5(10.19) % 9.61 8.05 5.9 81.43 6.56 9.15 10.48
893 748 548 7565 609 850 974
16 11 7 90 7 1 1 16
6(19,1) m ux 10.38 9.8 8.34 6.09 6.71 6.73 6.24
fc 964 910 775 566 623 625 580
DF 17 13 10 7 8 8 9
7(19.10) % 12.18 11.36 9.48 6.68 7.56 7.74 7.27
1132 1055 881 621 702 719 675
20 15 1 1 7 9 10 11
Total Horizontal % 59.69 74.01 85.37 90.60 88.55 80.23 66.30
Table E.4b Gi lette Model, April 21,
154
RP# TIME 9:00 10:00 11:00 12:00 13:00 14:00 15:00
1(1,10) Klux 5.44 5.88 99.47 4.94 8.57 11.28 12.78
fc 505 546 9241 459 796 1048 1187
DF % 7 6 97 5 8 12 16
2(1,19) 3.55 3.2 96.41 98.92 5.14 7.9 9.92
330 297 8956 9190 478 734 922
% 4 3 94 94 5 8 12
3(10,1) Klux 12 10.87 8.54 5.3 8.55 10.87 12
fc 1115 1010 793 492 794 1010 1115
DF % 15 12 8 5 8 12 15
4(10.10) 15.38 13.74 10.58 6.28 10.6 13.74 15.38
1429 1276 983 583 985 1276 1429
% 19 15 10 6 10 15 19
5(10.19) Klux 10.98 8.84 5.84 99.34 5.86 8.84 10.98
fc 1020 821 543 9229 544 821 1020
DF % 14 9 6 94 6 9 14
6(19,1) 10.81 9.67 7.48 4.5 5 4.97 4.44
1004 898 695 418 465 462 412
% 14 10 7 4 5 5 6
7(19.10) Klux 12.78 11.28 8.56 4.94 99.48 5.89 5.45
fc 1187 1048 795 459 9242 547 506
DF % 16 12 8 5 97 6 7
Total Horizontal 79.59 93.68 102.6 105.7 102.6 93.68 79.59
Table E.5a IES Model, May 21.
1(1,10) 7.38 8.33 8.59 8.23 11.68 13.7 13.67
686 774 798 765 1085 1273 1270
% 16 13 12 11 15 20 25
2(1.19) Klux 3.24 3.12 2.58 2.52 5.7 8.09 9.13
fc 301 290 240 234 530 752 848
DF % 7 5 4 3 8 12 17
3(10,1) 13.14 13.09 11.52 8.93 12.03 13.7 13.38
1221 1216 1070 830 1118 1273 1243
% 28 21 16 12 16 20 25
4(10,10) Klux 16.6 16.36 14.14 10.64 14.69 16.96 16.69
fc 1542 1520 1314 988 1365 1576 1551
DF % 35 26 20 14 19 25 31
5(10.19) 10 8.36 6.03 3.22 6.68 9.24 10.27
896 777 560 299 621 858 954
% 20 13 8 4 9 14 19
6(19,1) Klux 11.56 11.38 9.86 7.49 8.18 8.07 7.13
fc 1074 1057 916 696 760 750 662
DF % 24 18 14 10 11 12 13
7(19.10) 13.46 13.1 11.16 8.23 9.18 9.21 8.25
1250 1217 1037 765 853 856 766
% 28 21 15 1 1 12 14 15
Total Horizontal 67.57 83.01 91.78 96.60 94.43 86.30 72.53
Table E.5b Gi lette Model, May 21.
155
RP# TIME 9:00 10:00 11:00 12:00 13:00 14:00 15:00
Kiao) Klux 4.63 5.03 99.4 101.76 7.62 10.28 11.79
fc 430 467 9234 9454 708 955 1095
DF % 6 5 96 96 7 11 15
2(1,19) 3.33 2.99 97.01 99.44 4.86 7.55 9.55
309 278 9012 9238 451 701 887
% 4 3 94 94 5 8 12
3(10.1) Klux 10.96 9.8 7.52 4.36 7.53 9.8 10.96
fc 1018 910 699 405 700 910 1018
DF % 14 10 7 4 7 10 14
4(10.10) 14.11 12.44 103.91 102.83 103.9 12.44 14.11
1311 1156 9653 9553 9653 1156 1311
% 17 13 101 97 101 13 17
5(10.19) Klux 10.53 8.41 100.05 99.79 100.0 8.41 10.53
fc 978 781 9295 9270 9296 781 978
DF % 13 9 97 94 97 9 13
6(19,1) 9.93 8.77 6.62 3.72 4.22 4.2 3.71
922 815 615 346 392 390 345
% 12 9 6 3 4 4 5
7(19.10) Klux 11.79 10.28 7.61 101.76 99.42 5.03 4.64
fc 1095 955 707 9454 9236 467 431
DF % 15 1 1 7 96 96 5 6
Total Horizontal 81.02 94.69 103.4 106.3 103.4 94.69 81.02
Table E.6a IES Model, June 21.
1(1,10) 4.82 5.14 84.4 85.85 8.03 10.17 10.98
448 478 7841 7975 746 945 1020
% 7 6 90 87 8 1 1 15
2(1,19) Klux 3.77 3.4 82.3 83.8 5.63 7.86 9.14
fc 350 316 7646 7785 523 730 849
DF % 6 4 88 85 6 9 12
3(10.1) 9.3 9.02 7.37 5.12 7.95 9.8 10.37
864 838 685 476 739 910 963
% 14 U 8 5 8 11 14
4(10.10) Klux 11.73 11.31 88.32 86.93 86.45 12.15 13
fc 1090 1051 8205 8076 8031 1129 1208
DF % 17 13 94 88 90 14 17
5(10.19) 8.99 7.89 84.94 84.21 83.07 8.7 10.05
835 733 7891 7823 7717 808 934
% 13 9 90 86 86 10 13
6(19,1) Klux 8.44 8.09 6.53 4.47 5.11 5.23 4.8
fc 784 752 607 415 475 486 446
DF % 12 10 7 5 5 6 6
7(19.10) 9.88 9.41 7.44 85.85 82.55 6.05 5.67
918 874 691 7975 7669 562 527
% 15 1 1 8 87 86 7 8
Total Horizontal 67.78 84.05 93.87 98.36 96.38 88.54 75.28
Table E.6b Gi lette Model, June 21,
156
RP # TIME 9:00 10:00 11:00 12:00 13:00 14:00 15:00
1(1,10) Klux 5.77 98.79 101.21 8.44 11.12 12.61 8.12
fc 536 9178 9402 784 1033 1171 754
DF % 6 97 96 8 12 16 18
2(1,19) 3.17 95.82 98.3 5.08 7.82 9.83 7.01
294 8902 9132 472 726 913 651
% 3 94 94 5 8 12 16
3(10,1) Klux 10.71 8.4 5.19 8.41 10.71 11.84 7.76
fc 995 780 482 781 995 1100 721
DF % 1 1 8 5 8 1 1 15 17
4(10.10) 13.54 10.4 102.51 10.42 13.54 15.17 9.5
1258 966 9523 968 1258 1409 883
% 15 10 98 10 15 19 21
5(10.19) Klux 8.75 5.78 98.71 5.79 8.75 10.88 7.68
fc 813 537 9170 538 813 1011 713
DF % 9 6 94 6 9 14 17
6(19.1) 9.53 7.35 4.41 4.91 4.88 4.35 4.47
885 683 410 456 453 404 415
% 10 7 4 5 5 5 10
7(19.10) Klux 11.13 8.43 101.21 98.81 5.78 5.35 5.12
fc 1034 783 9402 9179 537 497 476
DF % 12 8 96 97 6 7 11
Total Horizontal 79.25 93.2 102.1 105.1 102.1 93.2 79.25
Table E.7a IES Model, July 21.
1(1.10) 5.36 83.88 85.4 8.65 10.8 11.55 1 1
498 7792 7934 804 1003 1073 1022
% 7 91 88 9 12 16 20
2(1,19) Klux 3.13 81.3 82.87 5.78 8.05 9.32 9.29
fc 291 7553 7699 537 748 866 863
DF % 4 88 85 6 9 13 17
3(10,1) 9.51 8.06 5.76 8.63 10.48 10.98 10.35
883 749 535 802 974 1020 962
% 12 9 6 9 12 15 18
4(10,10) Klux 11.96 9.88 86.68 10.51 12.98 13.74 13
fc 1111 918 8053 976 1206 1276 1208
DF % 15 1 1 89 1 1 15 19 23
5(10.19) 7.86 5.86 83.33 6.51 8.94 10.28 10.2
730 544 7741 605 831 955 948
% 10 6 86 7 10 14 18
6(19,1) Klux 8.47 7.1 4.99 5.64 5.74 5.28 4.71
fc 787 660 464 524 533 491 438
DF % 10 8 5 6 7 7 8
7(19,10) 9.86 8.08 85.41 82.04 6.62 6.2 5.58
916 751 7935 7622 615 576 518
% 12 9 88 86 8 8 10
Total Horizontal 66.87 81.79 92.49 97.05 95.1 87.17 73.74
Table E.7b Gillette Model, Ju
iy 2 i.
157
RP# TIME 9:00 10:00 11:00 12:00 13:00 14:00 15:00
la.ioi Klux 7.87 7.74 6.95 10.69 13.43 14.79 7.56
fc 731 719 646 993 1248 1374 702
DF % 9 8 7 1 1 15 20 20
2(1.191 3.68 91.28 93.9 5.68 8.51 10.52 6.3
342 8480 8723 528 791 977 585
% 4 94 93 6 10 14 17
3(10,1) Klux 13.18 10.85 7.51 10.85 13.18 14.17 7.27
fc 1224 1008 698 1008 1224 1316 675
DF % 15 1 1 7 1 1 15 19 19
4(10.10) 16.53 13.36 8.92 13.36 16.53 18 8.89
1536 1241 829 1241 1536 1672 826
% 19 14 9 14 19 25 24
5(10.19) Klux 9.63 6.58 94.49 6.58 9.63 11.75 6.93
fc 895 611 8778 611 895 1092 644
DF % 1 1 7 94 7 1 1 16 18
6(19,1) 11.6 9.4 6.33 6.84 6.77 6.12 4.29
1078 873 588 635 629 569 399
% 13 10 6 7 8 8 11
7(19.10) Klux 13.43 10.69 6.95 7.75 7.87 7.31 4.89
fc 1248 993 646 720 731 679 454
DF % 15 1 1 7 8 9 10 13
Total Horizontal 73.35 87.99 97.29 100.5 97.29 89.99 73.35
Table E.8a IES Model, August 21.
1(1.10) 7.34 7.7 7.43 10.6 12.59 12.95 11.28
682 715 690 985 1170 1203 1048
% 9 9 8 12 15 19 22
2(1,19) Klux 3.85 75.87 77.48 6.49 8.7 9.77 9.21
fc 358 7048 7198 603 808 908 856
DF % 5 85 83 7 10 14 18
3(10,1) 11.66 10.24 7.88 10.73 12.41 12.52 10.76
1083 951 732 997 1153 1163 1000
% 15 12 8 12 15 18 21
4(10.10) Klux 14.52 12.48 9.26 13 15.26 15.54 13.37
fc 1349 1159 860 1208 1418 1444 1242
DF % 19 14 10 14 18 22 26
5(10.19) 8.77 6.75 78.11 7.37 9.75 10.85 10.14
815 627 7256 685 906 1008 942
% 1 1 8 84 8 12 16 20
6(19,1) Klux 10.3 8.94 6.78 7.4 7.39 6.73 5.54
fc 957 831 630 687 687 625 515
DF % 13 10 7 8 9 10 11
7(19.10) 11.87 10.11 7.43 8.29 8.43 7.78 6.45
1103 939 690 770 783 723 599
% 15 1 1 8 9 10 1 1 13
Total Horizontal 62.28 77.98 88.83 93.47 91.41 83.10 69.20
Table E. 8b Gi lette Model, August 21.
158
RP* TIME 9:00 10:00 11:00 12:00 13:00 14:00 15:00
1(1,10) Klux 10.38 10.37 9.6 13.34 15.94 9.43 6.03
fc 964 963 892 1239 1481 876 560
DF % 13 12 1 1 15 21 15 23
2(1.19) 4.28 3.74 3.02 6.32 9.11 6.99 4.77
398 347 281 587 846 649 443
% 6 4 3 7 12 11 18
3(10,1) Klux 15.93 13.75 10.41 13.75 15.93 9.29 5.88
fc 1480 1277 967 1277 1480 863 546
DF % 21 16 12 16 21 15 23
4(10.10) 19.82 16.83 12.4 16.83 19.82 11.28 7.14
1841 1564 1152 1564 1841 1048 663
% 26 19 14 19 26 18 27
5(10.19) Klux 10.44 7.44 3.83 7.44 10.44 7.77 5.27
fc 970 691 356 691 970 722 490
DF % 13 9 4 9 13 12 20
6(19.1) 13.88 11.81 8.74 9.23 9.05 5.99 3.71
1289 1097 812 857 841 556 345
% 18 14 10 11 12 10 14
7(19.10) Klux 15.94 13.34 9.6 10.37 10.38 6.77 4.2
fc 1481 1239 892 963 964 629 390
DF % 21 15 11 12 13 11 16
Total Horizontal 62.39 77.36 86.92 90.20 86.92 77.36 62.39
Table E.9a IES Model, September 21.
1(1,10) 9.28 9.8 9.55 12.47 13.97 13.5 10.31
862 910 887 1158 1298 1254 958
% 14 12 1 1 15 19 23 25
2(1,19) Klux 4.5 4.5 4.31 7.06 9 9.58 8.02
fc 418 418 400 656 836 890 745
DF % 7 6 5 9 12 16 19
3(10,1) 13.54 12.42 10.17 12.77 13.97 13.26 10.02
1258 1154 945 1186 1298 1232 931
% 20 16 12 16 19 22 24
4(10,10) Klux 16.7 15.05 11.99 15.4 17.06 16.29 12.26
fc 1551 1398 1114 1431 1585 1513 1139
DF % 24 19 14 19 23 27 29
5(10,19) 9.33 7.52 5.11 8.1 10.16 10.7 8.87
867 699 475 752 944 994 824
% 14 9 6 10 14 18 21
6(19,1) Klux 11.86 10.77 8.71 9.21 8.96 7.9 6
fc 1102 1001 809 856 832 734 557
DF % 17 14 10 1 1 12 13 14
7(19,10) 13.55 12.11 9.55 10.27 10.12 9.01 6.83
1259 1125 887 954 940 837 635
% 20 15 1 1 13 14 15 16
Total Horizontal 51.82 68.31 79.35 84.05 81.96 73.46 59.58
Table E.9b Gillette Model, September 21.
159
RP# TIME 9:00 10:00 11:00 12:00 13:00 14:00 15:00
1(1,10) Klux 12.1 12.28 11.61 15.09 17.28 7.37 3.57
fc 1124 1141 1079 1402 1605 685 332
DF % 19 17 15 21 27 24 23
2(1,19) 4.66 4.2 3.53 6.64 9.17 5.25 2.81
433 390 328 617 852 488 261
% 7 6 5 9 14 17 18
3(10.1) Klux 17.49 15.7 12.61 15.7 17.49 7.33 3.53
fc 1625 1459 1171 1459 1625 681 328
DF % 28 22 17 22 28 24 23
4(10.10) 21.64 19.14 15.02 19.14 21.64 8.85 4.22
2010 1778 1395 1778 2010 822 392
% 34 26 20 26 34 29 27
5(10.19) Klux 10.62 7.91 4.51 7.91 10.62 5.86 3.11
fc 987 735 419 735 987 544 289
DF % 17 1 1 6 1 1 17 19 20
6(19,1) 15.15 13.42 10.57 10.98 10.64 4.95 2.48
1407 1247 982 1020 988 460 230
% 24 18 14 15 17 16 16
7(19.10) Klux 17.29 15.09 11.61 12.29 12.1 5.56 2.77
fc 1606 1402 1079 1142 1124 517 257
DF % 27 21 15 17 19 18 18
Total Horizontal 49.07 63.58 72.93 76.15 72.93 63.58 49.07
Table E.lOa IES Model, October 21.
1(1.10) 9.8 10.47 10.24 12.9 13.91 12.47 8.16
910 973 951 1198 1292 1158 758
% 19 17 15 20 24 28 28
2(1,19) Klux 4.11 4.1 3.87 6.47 8.32 8.26 6.08
fc 382 381 360 601 773 767 565
DF % 8 7 6 10 14 19 21
3(10,1) 13.9 13.14 11.01 13.35 14.04 12.38 8.02
1291 1221 1023 1240 1304 1150 745
% 26 21 16 20 24 28 27
4(10.10) Klux 17.13 15.94 13.05 16.14 17.12 15.18 9.76
fc 1591 1481 1212 1499 1590 1410 907
DF % 33 25 19 25 30 34 33
5(10.19) 8.68 7.06 4.73 7.56 9.49 9.29 6.76
806 656 439 702 882 863 628
% 17 1 1 7 12 16 21 23
6(19.1) Klux 12.07 11.28 9.33 9.7 9.7 7.62 5.09
fc 1121 1048 867 901 901 708 473
DF % 23 18 14 15 17 17 17
7(19.10) 13.74 12.66 10.24 10.95 10.81 8.66 5.76
1276 1176 951 1017 1004 805 535
% 26 20 15 17 19 19 20
Total Horizontal 36.80 52.46 62.94 67.43 65.59 57.54 44.45
Table E. 10b Gillette Model, October 21.
160
K P # TIME 9:00 10:00 11:00 12:00 13:00 14:00 15:00
1(1,10) Klux 12.64 13.08 12.55 15.63 7.6 5.04 1.69
fc 1174 1215 1166 1452 706 468 157
DF % 25 22 20 26 15 25 19
2(1,19) 4.76 4.41 3.81 6.63 4.95 3.59 1.42
442 410 354 616 460 334 132
% 9 7 6 11 10 17 16
3(10,1) Klux 17.61 16.35 13.62 16.35 7.69 5.04 1.68
fc 1636 1519 1265 1519 714 468 156
DF % 34 27 22 27 15 25 18
4(10.10) 21.68 19.88 16.23 19.88 9.22 6.04 1.96
2014 1847 1508 1847 857 561 182
% 42 33 26 33 18 29 21
5(10.19) Klux 10.23 7.94 4.87 7.94 5.59 4.01 1.56
fc 950 738 452 738 519 373 145
DF % 20 13 8 13 1 1 20 17
6(19.1) 15.2 13.94 11.42 11.73 5.64 3.59 1.37
1412 1295 1061 1090 524 334 127
% 30 23 18 19 11 17 15
7(19.10) Klux 17.27 15.64 12.55 13.09 6.28 4.01 1.51
fc 1604 1453 1166 1216 583 373 140
DF % 34 26 20 22 12 20 17
Total Horizontal 20.55 51.41 60.26 63.32 60.26 51.41 20.55
Table E. 1 la IES Model, November 21.
1(1,10) 9.63 10.58 10.47 12.62 12.94 10.66 5.59
895 983 973 1172 1202 990 519
% 24 21 19 24 28 31 25
2(1.19) Klux 3.89 4.04 3.91 6.14 7.39 6.93 4.29
fc 361 375 363 570 687 644 399
DF % 10 8 7 12 16 20 19
3(10.1) 13.22 13.03 11.27 13.12 13.15 10.66 5.55
1228 1210 1047 1219 1222 990 516
% 33 26 21 25 29 31 24
4(10.10) Klux 16.23 15.77 13.36 15.82 16 12.99 6.62
fc 1508 1465 1241 1470 1486 1207 615
DF % 40 31 24 30 35 38 29
5(10.19) 7.88 6.74 4.8 7.2 8.47 7.82 4.75
732 626 446 669 787 726 441
% 19 13 9 13 18 23 21
6(19,1) Klux 11.44 11.16 9.54 9.73 8.91 6.93 3.97
fc 1063 1037 886 904 828 644 369
DF % 28 22 17 18 19 20 17
7(19.10) 12.97 12.49 10.47 10.82 10.01 7.82 4.43
1205 1160 973 1005 930 726 412
% 32 25 19 20 22 23 19
Total Horizontal 26.03 40.46 50.49 54.93 53.34 46.07 34.62
Table E. 1 lb Gillette Model, November 21.
161
RP* TIME 9:00 10:00 11:00 12:00 13:00 14:00 15:00
1(1,10) Klux 12.64 13.2 12.73 15.64 17.01 4.14 1.21
fc 1174 1226 1183 1453 1580 385 112
DF % 27 24 22 28 36 24 17
2(1.19) 4.75 4.45 3.88 6.56 8.55 2.99 1.06
441 413 360 609 794 278 98
% 10 8 7 12 18 17 15
3(10.1) Klux 17.38 16.38 13.82 16.38 17.38 4.15 1.2
fc 1615 1522 1284 1522 1615 386 111
DF % 37 29 24 29 37 24 17
4(10.10) 21.37 19.9 16.46 19.9 21.37 4.95 1.38
1985 1849 1529 1849 1985 460 128
% 45 36 28 36 45 29 19
5(10.19) Klux 9.97 7.88 4.95 7.88 9.97 3.34 1.16
fc 926 732 460 732 926 310 108
DF % 21 14 8 14 21 19 16
6(19,1) 14.99 13.96 11.59 11.84 11.19 3.04 1.04
1393 1297 1077 1100 1040 282 97
% 32 25 20 21 24 18 14
7(19.10) Klux 17.01 15.64 12.73 13.21 12.64 3.39 1.14
fc 1580 1453 1183 1227 1174 315 106
DF % 36 28 22 24 27 20 16
Total Horizontal 33.97 47.00 55.61 58.59 55.61 47.00 33.97
Table E.12a IES Model, December 21.
1(1,10) 9.38 10.17 9.98 12.18 12.49 9.75 3.64
871 945 927 1132 1160 906 338
% 29 24 22 28 34 38 25
2(1.19) Klux 3.16 3.13 2.95 5.22 6.54 5.93 2.79
fc 294 291 274 485 608 551 259
DF % 10 8 6 12 18 23 19
3(10,1) 13.15 12.74 10.84 12.75 12.75 9.77 3.62
1222 1184 1007 1184 1184 908 336
% 40 31 24 29 34 38 25
4(10.10) Klux 16.23 15.51 12.93 15.47 15.62 12 4.32
fc 1508 1441 1201 1437 1451 1115 401
DF % 49 37 28 35 42 46 29
5(10.19) 7.26 5.86 3.79 6.24 7.58 6.75 3.09
674 544 352 580 704 627 287
% 22 14 8 14 20 26 21
6(19,1) Klux 11.3 10.82 9.08 9.26 8.38 6.11 2.62
1050 1005 844 860 779 568 243
DF % 34 26 20 21 23 24 18
7(19.10) 12.85 12.14 9.98 10.32 9.44 6.93 2.92
1194 1128 927 959 877 644 271
% 39 29 22 23 25 27 20
Total Horizontal 20.21 32.80 41.53 45.62 44.02 37.04 25.83
Table E. 12b Gillette Model, December 21.
162
APPENDIX F:
Latitude and Longitude of World Cities
(and tlmn corresponding to 12:00 noon, eastern standard tima)
lot. Lena* lot. Long.
City . . . . Dmo City . . . . Tim
Aberdeen, Scotland 57 9 n 2 9 w 5:00 pjn.
Adelaide, Australia 34 5 5 s 138 36 e 2 3 0 a.m .1
Algiers 35 5 0 n 3 0 • 6:00 p.m.
Amsterdam 52 22 n 4 53 e 6:00 p.m.
Ankara, Turkey 35 S 5n 32 5 5 # 7:00 p jn.
Asuncion, Paraguay 25 15 s 57 40 w 1.D0 p.m.
A thens 37 5 8 n 23 43 • 730 p.m.
Auckland, New 36 5 2 s 174 45 e 5:00 a jn .1
Zealand
midnight1 Bangkok, Thailand 13 4 5 n 100 30 e
Barcelona 41 23 n 2 9 e 6.-00 p.m.
Beldm, Brazil 1 2 8 s 48 29 w 2.-00 p.m.
Belfast, Northern 54 37 n 5 56 w 5:00 p.m.
Ireland
Belgrade, Yugoslavia 44 52 n 20 32 e 6.-00 p.m.
Berlin 52 30 n 13 25 e 6:00 p.m.
Birmingham, England 52 25 n 1 55 w 5:00 p.m.
Bogota, Colombia 4 3 2 n 74 15w 1230 noon
Bombay 19 0 n 72 48 e 10:30 p.m.
Bordeaux, France 44 SOn 0 31 w 6:00 p.m.
Bremen, W. Germany 53 5 n 8 49 e 630 p.m.
Brisbane, Australia 27 2 9 s 153 8 e 3:00 a-m.1
Bristol, England 51 28 n 2 35 w 530 p.m.
Brussels 50 52 n 4 22 e 6:00 p.m.
B ucharest 44 25 n 26 7 e 730 pjn.
Budapest 47 30 n 19 5 e 6:00 p.m.
Buenos Aires 34 35 s 58 22 w 230 p.m.
Cairo 30 2 n 31 21 e 730 pzn.
Calcutta 22 34 n 88 24 e 10:30 p.m.
Canton, Chine 23 7 n 113 15 e 130 a.m .’
Cape Town, South 33 55 s 18 22 e 7:00 p.m.
Africa
Caracas, Venezuela 10 28 n 67 2w 130 p.m.
Cayenne, French 4 49 n 52 18 w 130 p.m.
Guiana
Chihuahua, Mexico 28 37 n 106 5 w 1130 a.m.
Chongqing, China 29 46 n 106 34 e 130 a.m .1
Copenhagen 55 40 n 12 34 e 6:00 p.m.
C6rdoba. Argentina 31 2 8 s 64 lOw 2:00 p.m.
Dakar, Senegal 14 40 n 17 28 w 530 p.m.
Darwin, Australia 12 2 8 s 130 51 e 2:30 a.m .'
Djibouti 11 30 n 43 3 e 8:00 p.m.
Dublin 53 20 n 6 15w 5:00 p.m.
Durban, South Africa 29 5 3 s 30 53 e 7:00 p.m.
Edinburgh, Scotland 55 55 n 3 lOw 5:00 p.m.
Frankfurt 50 7 n 8 41 e 6:00 p.m.
Georgetown, Guyana 6 45 n 58 15w 1:15 p.m.
Glasgow, Scotland 55 50 n 4 15 w 5:00 p.m.
Guatemala City, 14 37 n 90 31 w 11:00 a.m.
Guatemala
Guayaquil, Ecuador 2 10 s 79 56 w 12:00 noon
Hamburg 53 33 n 10 2 e 630 p.m.
Hammerfest, Norway 70 38 n 23 38 e 6:00 p.m.
Havana 23 8 n 82 23 w 12:00 noon
Helsinki, Finland 60 10 n 25 0 e 7:00 p.m.
H obart Tasmania 42 52 s 147 19 e 3:00 a.m .'
Iquique, Chile 20 10 s 70 7w 130 p.m.
Irkutsk, U.S.S.R. 52 30 n 104 20 e 1:00 a.m.
Ja k arta, Indonesia 6 16 s 106 48 e 0:30 a.m .1
Johannesburg, South 26 12 s 28 4 e 7:00 p.m.
Africa
Kingston, Jam aica 17 59 n 76 49 w 12:00 noon
Kinshasa, Zaire 4 18 s 15 17 e 6:00 p.m.
La Paz, Bolivia 16 27 s 68 22 w 1:00 p.m.
Leeds, England 53 45 n 1 30 w 5:00 p.m.
Leningrad
Lima, Peru
59 56 n 30 18 • 8:00 p.m.
12 0 s 77 2 w £ 00 noon
Lisbon 38 44 n 9 9 w 5:00 p.m.
Liverpool England 53 25 n 3 Ow 5:00 p.m.
London 51 32 n 0 5w 5:00 p.m.
Lyons, Franco
Madrid
45 45 n 4 50 e 6:00 p.m.
40 26 n 3 42 w 6:00 p.m.
M anchester, England 53 30 n 2 15w 5:00 p.m.
Manila 14 35 n 120 57 e 1:00 a.m.
Marseilles, R enee 43 20 n 5 20 e 6:00 p.m.
M azatlin, Mexico 23 12 n 106 2Sw 10:00 a.m.
Mecca, Saudi Arabia 21 29 n 39 45 e 8:00 p.m.
Melbourne 37 47 s 144 58 e 3:00 a.m.
Mexico City 19 26 n 99 7 w 11:00 a.m,
Milan, Italy 45 27 n 9 10 e 6:00 p.m.
Montevideo, Uruguay 34 5 3 s 56 lOw £0 0 p.m.
M oscow 55 45 n 37 36 e 8:00 p.m.
Munich, Germany 48 8 n 11 35 e 6:00 p.m.
Nagasaki, Japan 32 48 n 129 57 e 2:00 a.m.
Nagoya, Japan
Nairobi, Kenya
35 7 n 136 56 e £0 0 a.m.'
1 25 s 36 55 e 8:00 p.m.
Nanjing (Nanking), 32 3 n 118 53 e 1:00 a.m.
China
Naples, Italy 40 50 n 14 15 e 6:00 p.m.
N ewcastle -on-Tyne, 54 58 n 1 37 w 5:00 p.m.
Eng.
Odessa, U.S.S.R. 46 27 n 30 48 e 9:00 p.m.
Osaka, Japan 34 32 n 135 30 e 2:00 a.m.
Oslo 59 57 n 10 42 e 6:00 p.m.
Panama City, Panama 8 58 n 79 32 w 12:00 noon
Paramaribo, Surinam 5 45 n 55 15w 1:30 p.m.
Paris 48 48 n 2 20 e 6:00 p.m.
Peking 39 55 n 116 25 e 1:00 a.m.
Perth, Australia 31 57 s 115 52 e 1:00 a.m.
Plymouth, England 50 25 n 4 5w 5:00 p.m.
Port Moresby, Papua 9 25 S 147 8 e 3:00 a.m.
New Guinea
Prague 50 5 n 14 26 e 6:00 p.m.
Reykjavik, Iceland 64 4 n 21 58 w 4:00 p.m.
Rio de Janeiro 22 57 s 43 12w 2:00 p.m.
Rome 41 54 n 12 27 e 6:00 p.m.
Salvador, Brazil 12 56 s 38 27 w 2:00 p.m.
Santiago, Chile 33 28 s 70 45w 1:00 p.m.
Sao Paulo, Brazil 23 31 s 46 31 w 2:00 p.m.
Shanghai, China 31 10 n 121 28 e 1:00 a.m.
Singapore 1 14 n 103 55 e 0:30 a.m.
Sofia, Bulgaria 42 40 n 23 20 e 7:00 p.m.
Stockholm 59 17 n 18 3 e 6:00 p.m.
Sydney, Australia 34 0 s 151 0 e 3:00 a.m.
Tananarive, 18 50 s 47 33 e 8:00 p.m.
M adagascar
Teheran, Iran 35 45 n 51 45 e .8:30 p.m.
Tokyo 35 40 n 139 45 e 2:00 a.m.
Tripoli, Libya 32 57 n 13 12 e 7:00 p.m.
Venice 45 26 n 12 20 e 6:00 p.m.
Veracruz, Mexico 19 10 n 96 10w 11:00 a.m.
Vienna 48 14 n 16 20 e 6.00 p.m.
Vladivostok, U.S.S.R. 43 10 n 132 0 e 3.00 a.m.
W arsaw 52 14 n 21 0 e 6:00 p.m.
Wellington, New 41 17 s 174 47 e 5:00 a.m.
Zealand
Yangon. Myanmar 16 50 n 96 0 e 11:30 p.m.
Ziirich 47 21 n 8 31 e 6:00 p.m.
1. O n th e follow ing day.
163
APPENDIX G: Glossary of Abbreviations:
A The solar illumination.
A’ The azimuth of the sun with respect to the window.
Aw
The window azimuth.
CIE Commission Internationale de Eclairage.
DF Daylight Factor.
Edh
Direct horizontal solar illuminance.
E - dn
Direct normal solar illuminance.
Edv
Direct vertical radiation.
Eg
The total illumination from the ground in footcandles.
F
The illumination from the ground on the window.
Et
The total illumination from the sky in footcandles.
Ekg
The illumination from the ground on the window.
Ekw
The illumination from the sky on the window in footcandles.
En et
Net illumination.
fc Footcandles.
IES Illumination Engineering Society.
lx Lux.
MF Maintenance Factor.
NBS National Bureau of Standards.
NOAA National Oceanic and Atmospheric Administration.
RP Reference Point.
SAD Seasonal Affective Disorder.
TMY Typical Meteorological Year.
a Solar altitude angle.
T the net transmissivity.
Pg
The reflectance of the ground.
165
BIBLIOGRAPHY:
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DavliQht and its Spectrum. New York, Elsevier Publishing Company
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Knowles, Ralph L.
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Creator Al-Turki, Ibrahim M. I. (author)

Core Title Qualitative and quantitative natural light in atria and adjacent spaces

Degree Master of Building Science

Degree Program Building Science

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

Tag engineering, architectural,OAI-PMH Harvest

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Advisor Schiler, Marc (committee chair), Knowles, Ralph Lewis (committee member), Noble, Douglas (committee member)

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