A MODELING METHODOLOGY FOR ENERGY

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90. 135. Source:(ASHRAE, 1989). The angle of incidence, Q, for any surface is the angle between the direction of the sun rays and the line normal to the surface.

A MODELING METHODOLOGY FOR ENERGY-CONSERVING SITE DESIGN

DISSERTATION

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University

By Balqies I. Sadoun

The Ohio State University

1992

Dissertation Committee:

proved by

Jean-Michel Guldmann Steven I . Gordon Kenneth S . Lee

Adviser Department of City and Regional Planning

TO MY PARENTS

ii

ACKNOWLEDGEMENT I would like to express my sincere appreciation and thanks to Professor Jean-Michel Guldmann, who served as my academic advisor and chairman of my dissertation exam committee, for his valuable advice throughout my graduate studies and during the course of this dissertation research. Special thanks are due to Professors Steven I. Gordon and Kenneth S. Lee, who served diligently as members of my dissertation committee. Their suggestions and comments have been a valuable contribution to this dissertation. I also would like to thank the technical staff of Academic Computing Services at The Ohio State University, and in particular Joseph Damico, for their help. I would like to thank my parents, and my family for their continued support and dedicated love and concern. Finally, my deep appreciation and thanks are due to my beloved husband for his emotional support, understanding, and encouragement throughout my graduate studies.

iii

VITA 1978..................... B.S. in Civil Engineering, Ain Shams University, Cairo, Egypt. 1978-1979............... Design Engineer, Irbid, Bureau, Jordan.

Consulting

1981..................... M.S in Civil Engineering, Ecole Nationale Des Travaux Publiques d 'E t a t . 1981-1988............... Instructor, Yarmouk University and Jordan University of Science and Technology, Irbid, Jordan.

FIELDS OF STUDY

Major Field:

City and Regional Planning.

Studies in : Energy, Environmental, Transportation Planning and Economics.

PUBLICATIONS AND CONFERENCE PRESENTATION

[1]

Balqies Sadoun Obaidat, " A Methodology for Defining The Solar Access in Site Planning", Proceedings of the 1992 Modeling and Simulation Conference, Pittsburgh, PA, May 1992 (in press).

[2]

Balqies Sadoun Obaidat, 11 A Modeling Methodology for Energy-Conserving Site Design", Paper Presentation at The 34th Annual Conference of the Association of Collegiate Schools of Planning, Columbus, Ohio, October 1992.

[3]

Balqies Sadoun Obaidat," An Experiment to Choose the Optimal Solar Access Site Design in Planning", Proceedings of the 1992 International Simulation Technology Conference, SimTec'92, pp.621-625, Houston, TX, N o v . 1992.

v

TABLE OF CONTENTS

D E D I C A T I O N ............................................ ACKNOWLEDGEMENT

.....................................

V I T A ................................................... PUBLICATIONS AND CONFERENCE PRESENTATIONS

PAGE ii iii iv

.........

v

LIST OF T A B L E S ........................................

ix

LIST OF FIGURES

xi

.....................................

CHAPTERS I.

II.

PAGE

INTRODUCTION ..................................... 1.1 The Importance of Planning for Energy Conservation .......................... 1.2 The P r o b l e m ........................... 1.3 Organization of the Dissertation . . . LITERATURE REVIEW AND BACKGROUND ............... ........................ Part I: Solar Impacts ....................... 2.1 Solar Radiation 2.2 Solar A n g l e s ........................... 2.3 Solar Energy Systems .................. 2.4 The Simulation of Building Heat Transfer and Applications ........... 2.5 Solar Rights and Shadow Analysis . . . Part 2: Wind I m p a c t s .......................... 2.6 Wind G e n e r a t i o n ...................... 2.7 Wind Pressure and Air Infiltration . . 2.8 Relative Importance of Air Infiltration Heat L o s s ............................. 2.9 Infiltration Models .................. 2.10 The Effect of Wind on The Energy Consumption in Buildings ............. 2.10.1 Air Infiltration ............. 2.10.2 Surface Heat Transmission . . vi

1 2 3 4 6 7 7 12 16 18 21 34 36 36 39 46 49 49 52

2.10.3

The Efficiency of Mechanical S y s t e m s ...................... 2.10.4 Enclosure of the Outdoors . . 2.11. Reduction Factors for Wind Velocity at the Leeward of a B a r r i e r .......... 2.12. Calculating Infiltration Heat Losses 2.12.1 Sensible Heat L o s s ........... 2.12.2 Latent Heat L o s s ............. 2.13 The Estimation of Air Infiltration V o l u m e ............................... 2.13.1 Crack Length Method ........ 2.13.2 Air Change Method ........... 2.14 V e n t i l a t i o n ......................... III. MODELING METHODOLOGY ............................. Part One: A Methodology for Solar Impact Assessment on An Urban S i t e ....................... 3.1 Shadow Analysis and Solar Energy Calculations .......................... 3.1.1 Data I n p u t s ................... 3.1.2 Preliminary Calculations ... 3.1.3 Wall Shadow Area Calculation . 3.1.4 Window Shadow Area Calculation 3.1.5 Energy Gain Calculation . . . . Part Two: A Methodology for Wind Impact Assessment on an Urban S i t e ........... ... 3.2 Wind Infiltration Analysis and Energy Losses Calculations ................. 3.2.1 Wind Protection Reduction Factor 3.2.2 Air Infiltration Calculations . 3.2.3 Building Tightness ........... 3.2.4 Outdoor Design Temperature . . 3.2.5 Description of the Methodology IV. A P P L I C A T I O N S ..................................... 4.1 Data I n p u t s .......................... 4.1.1 Building Characteristics . . . 4.1.2 Climatological D a t a .......... 4.1.3 Alternative Site Designs . . . 4.2 Design S t r a t e g y ..................... 4.3 Results and A n a l y s i s .................. 4.3.1 The Case of Contrasted Designs 4.3.2 Improved Site 5 ............... 4.3.3 Marginal Analysis ............. 4.3.4 S u m m a r y ........................

vii

55 57 57 61 61 62 63 63 64 65 66 67 67 67 75 79 84 85 86 86 87 92 92 94 96 109 109 109 110 110 114 115 115 139 139 158

V. CONCLUSIONS AND R E C O M M E N D A T I O N S ................. 5.1 C o n c l u s i o n s ......................... 5.2 R e c o m m e n d a t i o n s .....................

160 160 162

A P P E N D I C E S ............................................ A. Sample of Site D a t a ....................... B. Solar Impact Calculations Computer Program . C. Wind Impact Calculations Computer Programs .

164 164 168 176

R E F E R E N C E S ............................................

183

viii

LIST OF TABLES

TABLES 2.1

PAGE Extraterrestrial Solar Radiation Intensity and Related D a t a ..........................

8

............

15

2.2

Surface Orientations and Azimuths

2.3

Reduction in Velocity With Distance Behind Different Types of Barriers of Height H . . .

58

Wind Velocity Reduction Factors for a Vertical Plate .................................

87

Air Change Rates as a Function in Air Tightness and Outdoor Design Temperature . . .

93

Air Change Rates as a Function in Air Tightness and Outdoor Design Temperature . . .

93

Monthly Temperature and Wind Speed Characteristics ...............................

Ill

Monthly Direct and Global Radiation Characteristics ...............................

112

3.1

3.2

3.3

4.1

4.2

4.3

Wind Direction F r e q u e n c i e s ................ 113

4.4

The Annual Solar Energy Gains on Site 1

...

117

4.5

The Annual Wind Energy Losses on Site 1

...

118

4.6

The Monthly Solar Energy Gains on Site 1 . . .

120

4.7

The Monthly Wind Energy Losses on Site 1 . . .

121

4.8

The Annual Solar Energy Gains on Site 2

...

123

4.9

The Annual Wind Energy Losses on Site 2

...

124

ix

4.10

The Monthly Solar Energy Gains on Site 2 .

126

4.11

The Monthly Wind Energy Losses on Site 2

127

4.12

The Annual Solar Energy Gains

on Site 3

129

4.13

The Annual Wind Energy Losses

on site 3

130

4.14

The Monthly Solar Energy Gains on Site 3

131

4.15

The Monthly Wind Energy Losses on Site 3

133

4.16

The Annual Solar Energy Gains

on Site 4

135

4.17

The Annual Wind Energy Losses

on site 4

136

4.18

The Monthly Solar Energy Gains on Site 4

137

4.19

The Monthly Wind Energy Losses on Site 4

138

4.20

The Annual Solar Energy Gains

on Site 5

141

4.21

The Annual Wind Energy Losses

on Site 5

142

4.22

The Annual Solar Energy Gains

on Site 6

145

4.23

The Annual Wind Energy Losses

on Site 6

146

4.24

The Annual Solar Energy Gains

on Site 7

148

4.25

The Annual Wind Energy Losses

on Site 7

149

4.26

The Annual Solar Energy Gains

on Site 8

152

4.27

The Annual Wind Energy Losses

on Site 8

153

4.28

The Annual Solar Energy Gain on Site 9

4.29

The Annual Wind Energy Losses on Site 9

4.30

Summary of Annual Site Energy Gains

A.l

Grid Data for Site 5 ....................

165

A.2

Sample Window Data .......................

166

A.3

Buildings Dimensions

.

...................

.

155 156

.

157

167

LIST OF FIGURES

FIGURES 2.1

PAGE

The Ea r t h 's Motion Around the Sun ASHRAE (1989)

11

Solar Angles For Vertical And Horizontal Surfaces ASHRAE (1989) ........................

13

Schematic of the Key Elements of the Passive Solar Research Program ......................

20

2.4

The Solar E n v e l o p e .............................

23

2.5

Templates of The Building Shadow Patterns

. .

23

2.6

Critical Solar Skyspace Translated into a Solar Access z o n e .............................

25

2.7

Specific Skyspace Configurations

27

2.8

Solar Skyspace Dependent Upon a Variety of F a c t o r s .....................................

28

Computer Generated Surface Representing Maximum Allowable Height of Obstruction, for Solar Access Protection ..........................

29

The Area in a Barrier to be Out of Obstruction, in Order to Protect the Solar Access of the C o l l e c t o r ......................................

30

2.11

Shadow Percent Contour Plan

..................

32

2.12

Solar E a s e m e n t s ...............................

35

2.13

Pressure Distribution on Surface of Test House in Wind T u n n e l ..........................

38

2.2

2.3

2.9

2.10

xi

..............

2.14

Idealized Pressure-Difference Distribution Across the Walls of a B u i l d i n g ................

38

Average Wind Speed at Shelter Belts of ........... Different Degrees of Permeability

43

2.16

Sample Schematic of Air Flow Around Buildings

51

2.17

Characteristics of Air Flow Across a Building Near a Recessed Window Casement................

51

Effect of Air Velocity on Surface Heat Transmission ...................................

56

Air Flow Patterns Around Four Barriers of Various Shapes .................................

59

2.15

2.18

2.19

3.1

Solar Energy and Shadow Interactions Calculations F l o w c h a r t ...................................... 68

3.2

Wall Shadow Calculations Flowchart ..........

69

3.3

Window Shadow Calculations Flowchart ........

70

3.4

The Definition of: (a) The Building, and (b) The W i n d o w .................................... 72,73

3.5

Defining the Walls That Face the Sun and the Walls That Create S h a d o w s ....................

78

3.6

Wall and Window Shadow C a l c u l a t i o n s ........

81

3.7

Shadow Height Calculations ...................

82

3.8

Wind Infiltration Calculations Flowcharts

3.9

The Reduction in Velocity With Distance Behind the Building Barrier ..................

91

Defining the Wind Corridors (Ci), and the Building Barrier ( B i ) ........................

98

Wind Speed Calculation on a C o r r i d o r ........

100

3.10

3.11 3.12

. .

88,89

Building Velocity Calculation and Its Components for Calculating Air Infiltration ............. 103

xii

3.13

Standard Effective Temperature and The ASHRAE (1989) Comfort Zones ..........................

107

4.1

Plan of Site 1 ..................................

116

4.2

Plan of Site 2 ..................................

122

4.3

Plan of Site 3 ..................................

128

4.4

Plan of Site 4 ..................................

134

4.5

Plan of Site 5 ..................................

140

4.6

Plan of Site 6 ..................................

144

4.7

Plan of Site 7 ..................................

147

4.8

Plan of Site 8 ..................................

151

4.9

Plan of Site 9 ..................................

154

xiii

CHAPTER I INTRODUCTION

Energy conservation is a form of energy production which can be measured in terms of ease of recovery,

pay back and

environmental protection. According to Hays (1977), A dollar invested in energy conservation can make more net energy available than a dollar invested in developing new energy sources. Also, Yergin (1979) states that Conservation may well be the cheapest, safest, most productive, energy alternative readily available in large amounts. By comparison, conservation is a quality energy source.

Past climatic

generations

have

conditions and

successfully

created

suitable

utilized

micro-

energy-conserving

habitats. They were able to direct the wind, to protect access to

sunlight

simple

ways.

prices

has

and

to retain

Presently, led

to

a suitable

the continuous

a

renewed

moisture increase

appreciation

content of of

in

energy energy

conservation through climatic design, and a renewed focus on quantifying its potential.

1

2 1.1 The Importance of Planning for Energy Conservation Site planning for energy conservation is a comprehensive process, consisting of four major parts: •

The

architectural and

unit

design:

energy

conserving

structures are well defined and analyzed to create the optimal

unit.

The

energy

conserving

structures

are

designed to work as a solar collector and wind shelter in

winter,

and

to

protect

from

solar

overheat

by

different means in summer. •

The

transportation network: its role is important in the

orientation of buildings in the site, and in increasing solar

accessibility

by

using

roads

as

base

of

unit

orientation and as buffer zones. •

The landscaping enhance

the

of

site:

it

energy-conserving

Manipulating parameters

the

colors, in

the

can

be

qualities

heights landscape

and adds

designed of

the

various to

the

to

site. other

energy-

conserving ability of a site. •

Finally, climatic

the

most

design.

important It

of

offers

all

factors

is

an

opportunity

micro for

significant energy savings. What

is meant by climatic design?

It means using the

weather at a site to save energy. In winter, more sun and less shade and wind are needed through a window. summer,

Meanwhile,

in

less sun and more wind and shade are needed through

that same window.

Thus, less sun in summer and less wind in

3 winter

may

different

be

constitute

locations

goals

have

at

some

different

sites.

needs,

However, and

site

design/planning depends on the prevailing climatic conditions. No unique rule works for all climates.

1.2 The Problem An

important

element

in micro-climatic design

is the

siting of buildings on a site. A building's siting is a major factor

to

efficiently

achieve

benefits

from

energy

conservation. The importance of this factor is related to its role in (1) allowing the sun into a window and (2) obstructing wind flows away from it. A building on a site can be oriented to protect other buildings and to cast shadows on them. The interaction between

the buildings'

siting

produce important energy savings. Then,

and

climate

can

what is needed is a

quantitative measure to define the value of this interaction under

various

climatic

conditions

and

for

various

site

designs/layouts. A comprehensive analysis of climatic interactions with buildings location on a site is necessary. All buildings on a site act as a unit and play a role in affecting the

energy

budget of the site. All previous works in the area of climate interaction with site planning are primarily descriptive and qualitative, with no quantitative measurements. The need for quantitative

measures

to

help

in

planning

for

energy

conservation has led us to work toward better defining this

4 problem

and developing

a

numerical

simulation model

which

calculates the total energy gain of a site, considering the interactions between the buildings siting and the prevailing climatic

conditions.

interactions

with

This

the

model

entire

considers

site

and

all

all

its

climatic buildings

simultaneously, and may constitute a practical tool to be used by planners and architects in quantifying the natural energy available at a site. Moreover, it should help them in choosing the best energy-conserving site design when several design proposals are should

help

available for a given site.

planners

in

quantifying

climatic factor separately allow

for

considers

more the

effective seasonal

the

Using the model effects

of

each

(wind and sun), and this should improvements. changes

in

The

climate

model

also

(summer

and

winter), so as to achieve a more realistic understanding of climatic effects and energy gains.

1.3 Organization of the Dissertation This dissertation comprises five chapters, including the Introduction. Chapter II, which presents a literature review and some technical background, consists of two parts:

Solar

Impacts and Wind Impacts, the most important climatic factors in generating

energy

losses or gains

on a site.

The

sun-

related section provides an overview of the nature of solar radiations,

solar

angles

calculations,

and

solar

systems.

Previous studies related to the simulation of heat transfers

in solar buildings, to solar rights, and to shadow analysis, are reviewed. The wind-related section presents an overview of wind generation, force, and pressure distribution, and the literature review focuses on air infiltration and ventilation, energy

losses

effects,

modeling,

which

both

and

on

constitute

the the

analysis basis

of for

windbreak the

wind

simulation methodology. Chapter III presents two computerized submodels. The first one analyzes solar and shadowing effects on an urban site, and calculates the solar energy gain on the entire site. The second one analyzes wind interactions with buildings on an urban site, and calculates the induced energy losses.

Chapter IV presents the results of the applications

of the integrated model to choose a "best" energy-conserving site

design

qualities.

and

to

improve

a

site's

energy

conserving

Chapter V presents the main conclusions of this

research and recommendations for future work. Some data inputs and the listings of the two simulation submodels are presented in the Appendices.

CHAPTER II LITERATURE REVIEW AND BACKGROUND

This chapter presents the background material necessary to

develop

the

numerical

simulation

models

discussed

in

chapter III. The physics of heat transfer and air flows are described. The chapter is divided into two sections. The first one discusses solar issues,

and the second one wind issues.

The first section provides a brief background on the nature of solar radiation and its geometry,

including solar angles

relationships (needed to calculate incident solar energy from the

available

climatic

equations). Previous rights

development

data,

studies are

on

using

some

astronomical

shadow analysis

reviewed,

so

as

to

and

solar

provide

a

comparative basis to assess the contribution of our proposed modeling approach. The second section discusses wind flows and their

effects

on

structures

from

a

stress

distribution

viewpoint, including the importance of wind in inducing energy losses.

A

presented,

review

of

previous

again to provide

wind

a basis

approach.

6

simulation

models

is

for assessment of our

7 PART ONE:

SOLAR IMPACTS

Solar energy utilization represents a critical factor in energy-conserving

site

design.

The

sun

is

a

safe,

long-

lasting, and free source of energy. It can be very useful for winter heating,

but very harmful

for summer

cooling.

comes the importance of solar energy utilization,

Here

if energy

conservation is the goal. Direct use of solar energy in space and water heating, drying, and other applications is easily achievable in lightly populated areas. Meanwhile, this is much more

difficult

in heavily populated

maximum energy needs) , due to

areas

(downtowns with

the blocking

of

sun rays.

Sunlight is necessary to operate a solar collector, but it has to cross through neighboring properties and is easy to block. If

we

consider

resources,

we

using

solar

should protect

energy

to

solar access.

conserve

energy

The process

of

solar access design needs a thorough analysis of solar data. Solar angles and their relationships with solar intensity over time must be considered.

2.1

Solar Radiation The solar radiation intensity on a surface normal to the

direction of the solar rays, measured at the boundaries of the earth

atmosphere,

and

at

the

(92.9*106m) , is defined as the 1989).

mean solar

earth-sun constant,

distance

I.c (ASHRAE

Its value is 434.29 Btu/hr.ft2 (Hickey et al.

1981).

The earth's orbit around the sun is slightly elliptical, which

8 causes

variations

in the

extraterrestrial

solar

intensity

value. The extraterrestrial solar intensity I„ varies from a maximum of 449.6 Btu /hr.ft2 on January 3, when the earth is closest to the sun, to

a minimum of 419.9 Btu/hr.ft2 on July

6, when the earth-sun distance reaches its maximum. The earth's orbital velocity varies throughout the year, and the apparent solar time,

as determined by a sun dial,

differs from the mean time as determined by the uniform rate running clock. time"

This variation,

is

called the

"Equation of

(see Table 2.1).

Table 2.1: Extraterrestrial Solar Radiation Intensity and Related Data For the Twenty-First Day of Each Month. Base year 1964 (ASHRAE, 1989).

Month

Io (Btu/hr.ft2)

Equation of Time (Minutes)

Declination (Degrees

January

488.8

-11.2

-20.00

February

444.2

-13.9

-10.8

March

437.7

- 7.5

-00.00

April

429.9

+ 1.1

+11.60

May

423.6

+ 3.3

+20.00

June

420.2

- 1.4

+23.45

July

420.3

- 6.2

+20.60

August

424.1

- 2.4

+12.30

September

430.7

+ 7.5

+15.40

October

437.3

+15.4

-10.50

November

445.3

+13.8

-19.80

December

449.1

+ 1.6

-23.45

Source (ASHRAE, 1989)

The Sun's position in t h e sky is determined by the local solar time, which is equal to the addition of the equation of time to the local civil time. Local civil time is equal to the addition or the subtraction of the longitude correction from the local standard time. The longitude correction is 4 min per degree

difference

between

the

local

longitude

and

the

longitude of the standard time meridian for that locality. In the

United

States

and

Canada,

these

values

are

60°

for

Atlantic Standard Time ST; 75° for Eastern ST; 90° for Central ST; 105° for Mountain ST; 120° for Pacific ST; 135° for Yukon ST;

and

relation

150° Alaska-Hawaii between

the

ST.

Apparent

Equation Solar

(2.1)

Time,

presents the

and

the

Local

Standard Time:

AST = LST + ET + 4* (LSM - LON)

(2.1)

where AST = Apparent Solar Time LST = Local Standard Time ET = equation of time

(minutes)

LSM = Local Standard Time Meridian

(degrees)

LON = Local longitude (degrees) 4 = minutes of time required for 1.0° rotation of the earth.

The

earth

equatorial plane

is tilted

at

23.45° from the orbital plane at solstice time

an

angle

of

(June 21 and

10 December 21) . The solar declination angle 6 between the earthsun line and the equatorial plane varies over the year,

as

shown in Figure 2.1 and Table 2.1. This variation creates the seasons and the differences in the lengths of their day and night periods. The declination angle is expressed as:

6 = 23.5 * sin (2 * n * (d-81)/365)

(2.2)

where 6 = solar declination in degrees. d = day number (the 1st of January = day No.l). 7T = pi number (180° in radians).

When the sun rays pass through the atmosphere, they are reflected,

scattered

absorption

and

and

absorbed

diffusion

is

by

gas

dependent

molecules. upon

This

atmospheric

composition and the length of the atmospheric path traversed by the sun's rays. The ozone in the upper atmosphere absorbs most of the ultraviolet solar radiation, radiation

in

the

short-wave

portion

of

while part of the the

spectrum

is

scattered by air molecules to form the blue color of the sky. The short-wave radiation, which is scattered by dust and air

molecules,

reaches

the

earth

in

the

form

of

diffuse

radiation, Id. It is difficult to measure because it comes from every part of the sky, and its density changes with the dust and moisture content of the atmosphere and throughout the day. On a covered day (when the clouds completely cover the sun),

11

MARCH 21

TROPIC OF CANCER 23.5° N LAT 959 MILLION MILES EQUATORIAL PL A N E ^ ___ _

DECLINATION ANGLES V 898 MILLION MILES TROPIC O F CAPRICORN 2 3 .5 S L A T ^ -----------------SEPTEM BER 21

ORBITAL PLANE (PLANE O F THE ECLIPTIC)

Figure 2.1: The Earth's Motion Around the Sun (ASHRAE, 1989) P . 27.3.

12 diffuse radiation accounts for all solar radiation reaching the earth. The total short wave irradiance,

It/ reaching the

earth surface is the sum of the direct solar radiation ID, the diffuse sky radiation Id, and the reflected solar radiation from the surrounding environment lr. The irradiance of the direct component on any surface is equal to the product of the direct normal radiation IDN, and the

cosine

between

the

of

the

incidence

incoming solar

angle

rays

6,

and

which

a line

is the normal

angle to

the

surface. Thus, the total irradiance can be expressed as:

It = Idn * COS 6 +

Id + Ir

(2.3)

In the following, we present a method to compute all the factors on the right side of equation (2.3) . [A more detailed approach to calculate It is proposed by Perez et al.

(1986),

wherein they separate the diffuse sky radiation into three different components].

2.2

Solar Angles The sun's position in the sky is defined by two angles:

the solar altitude (3 above the horizontal plane, and the solar azimuth 9 measured from the

South

(see Figure 2.2).

These

angles depend on the local latitude L, the solar declination 6, and the Apparent Solar Time expressed as the hour angle H, where H

(in degrees) is computed as:

13

\

EA RTH -SU N LINE VERTICAL SU R F A C E TILED S U R F A C E ..S s T I L T A N G L E

SOLAR A LTITU D E

| £ _ HORIZONTAI ^ — SU RFACE> S O LA R AZIMUTH

x . / ^ *P | Ot A, NORM ALTO ^ — VERTICAL SU R F A C E

Figure 2.2: Solar Angles For Vertical And Horizontal Surfaces (ASHRAE, 1989) P.27.3.

14 H = 0.25 * (number of minutes from the local solar noon)

The equations that represent the relationships between the three above angles and the solar azimuth and altitude are:

sin j8 = cos L * cos 6 * cos H + sin L * sin 6

(2.4)

cos $ = (sin /3* sin L - sin 6)/(cos /8 * cos L)

(2.5)

Figure

2.2

shows

the

solar position

angles,

and

the

incident angles for vertical, tilted and horizontal surfaces. The

line OQ

represents the

North-South direction,

sun's

rays

direction,

NOS

the

and EOW the East-West direction. The

line OV is perpendicular to the horizontal plane in which the solar azimuth angle HOS ($), and the surface azimuth angle POS (G) are located. The surface solar azimuth angle angle HOP, and

(a) is the

is defined by:

a = $ - €

(2.6)

The solar azimuth angles are negative in the morning and positive in the afternoon. The absolute value of a is used in equation (2.7) and (2.7b). When a is greater than 90°, or less than 270°, then the surface we are considering is completely in the shade.

Table 2.2 provides values in degrees for the

surface azimuth for different surface orientations.

15 Table 2.2 : Surface Orientations and Azimuths, Measured from the South.

Orientation

N

NE

E

SE

S

SW

W

NW

Surface Az imuth

180

-135

-90

-45

0

45

90

135

Source:(ASHRAE,

1989).

The angle of incidence, Q, for any surface is the angle between the direction of the sun rays and the line normal to the surface.

For the horizontal surface the incidence angle

0„ is equal to the angle QOV; and for the vertical surface, the

incidence

angle

Qv is

the

angle

QOP.

For

any

tilted

surface the incident angle 6 is related to the surface tilt 2, the

altitude /3, and the surface solar azimuth angle a,

with:

cos 6 = cos p *cos a * sin 2 + sin /3* cos 2

(2.7)

where 2 = tilt angle of the surface from the horizontal plane.

When the surface is horizontal, 2 = 0 ° ,

and:

cos 6 h = sin ft

(2.7a)

When the surface is vertical, 2 = 90° , and: cos 0V = cos p * cos a

(2.7b)

16 2.3

Solar Energy Systems The economical feasibility of solar energy utilization

depends on the solar energy system used and the prevailing climatic conditions of the site. There are two types of solar systems (Mazria, 1979):

The

passive

solar

passive and active.

system.

It

is

simply

integrated

to

the

architecture of the building, with few additional features and no

excessive costs.

glazing

windows,

This

system

thermal

is characterized by

storage,

sky-lights

south

etc...

The

building in this system works as a collector, the walls and the floor as energy storage, and the movement of the

indoor

air as the distribution system. In this system, a minimum of technology is used and natural means of energy storage and distribution are enhanced, using the local materials available at

the

site

of

construction.

This

system

is

always

economically feasible, and it covers most of the energy needs in mild climatic conditions. The advantages of this system are the

very

low

initial

maintenance costs, problem

of

this

capital

and

annual

operating

and

as well as its environmental safety. The

system

lies

in the

difficulty

of

thermal

control, as a result of its simplicity.

The active solar system. increases

the

initial

It involves high technology, which

costs

of

construction.

Some

of

its

applications are feasible depending on the prevailing climatic

17 conditions,

and

energy

prices

and

availability.

Earlier

studies by Bell (1976, 1978), have shown that active systems were

not

feasible

due

to

many

uncertainties,

but

recent

increases in pollution emissions and energy prices have made active solar systems much more feasible. Solar water heating is proven to be feasible in many countries of the world, and it

is

highly

industrialized

in

some

of

these

countries.

Another successful application is the solar oven to generate electricity in remote areas where no other energy source is available. The advantages of active systems are their better control

of

temperature

fluctuations

(and

comfort), and again environmental safety.

thus

much

more

The disadvantages

are the high initial costs. Combination of passive and active systems,

together with the usage of insulation, heat pumps,

and heat recovery systems, may offer the optimal approach for energy conservation. Earlier habitats accounted for the ambient weather, and had high ceilings, wind towers, and wind catchers to improve their microclimates. pollution,

With

increases

in

energy

prices

and

architects and engineers started to analyze the

heat transfer properties of buildings

(Emery et al.,

1981),

and to recommend energy conservation practices in their new designs. These new practices were widely accepted because of their efficiency in reducing energy bills. The first technical features

in buildings that they recommended to change were

those that yielded good results with a minimal

investment,

18 such as the use of insulation in the walls and roofs, and the use of louvers or blinds over the windows.

The second phase

included changes requiring more expenses but with less effect in reducing energy consumption, such as adding a third glass to a double glazed window. The third phase of changes,

such

as adding a plastic cover (film) over the window to increase energy savings, had very little effect.

2.4

The Simulation of Building Heat Transfer and Applications to Passive Solar Heating of Housing In the 1 9 8 0 's different simulation models were designed

to analyze the thermal behavior of buildings. The small and simple models for a detailed but limited analysis of a single structural However,

component,

were

good

and

inexpensive

to

use.

these models are of little benefit for the design

process and do not lead to a major change in the structure of a

habitat.

structure structures

The and

large designed

with

a

programs for

variety

programs are not practical

the of

are

complicated

simulation structural

(due to the

of

in

multi-room

changes.

lack of

their

These

experimen­

tation data) . Moreover, they are time consuming in their data preparation. Examples of these simulation models include ESP (Clark, 1982), PASOLE (Me Farland, 1978), BLAST 1977),

TRANSYS

(Klien et al.,

1977),

DEROB

(U.S. Army,

(Arumi,

1979),

SERI-RES (Palmiter, Wheeling & Judkoff, 1982). Research in passive solar applications has focused mainly on the performance evaluation of buildings.

The knowledge

19 gained through the understanding of the thermal behavior of existing structures, was used to predict the performance and to improve the thermal qualities of future structures. This research has emphasized: •

The development of mathematical models that characterize heat flows and thermal behaviors of structures.



The validation

of

these models

after

comparison with

test results. •

The usage of these models to investigate the effects of both

design

parameters

and

weather

factors

on

the

performance. Figure 2.3 illustrates the progression of passive solar research

(Balcomb,

experimental buildings,

1984).

results

This

obtained

in

research test

and special experiments.

with known physical principles

modules,

with

monitored

Combining these results

(heat transfer), analytical

models where then developed and validated. locality,

starts

For a particular

solar performance can be predicted by using such

models and local weather data. These models can also be used for

sensitivity analysis,

methods,

and

to

clarify

to develop simplified prediction the

relationship

between

energy

conservation and passive solar energy utilization. The results of this research were rapidly and effectively translated into design

tools

evaluation

for

models

passive as

following drawbacks:

solar

predictive

heating. or

design

Using tools

thermal has

the

20

TEST ROOMS

S P E C IA L EXPERIM ENTS

S i O E - B Y - SID E C O M P A R IS O N S

M OOEL VALIDATION

W E A T H E R /S O L A R DATA ANALYTICAL M O D ELIN G

PERFORM ANCE EV A LU A T IO N S

H O U R -B Y -H O U R A N A L Y SIS

SE N S IT IV IT Y A N A L Y S IS

S IM P L IF IE D M E T H O D S P U B L IC A T IO N S . T E C H N IC A L P A P E R S D E S IG N H A N D B O O K

B A L A N C IN G C O N S E R V A T IO N ANO S O L A R

Figure 2.3: Schematic of the Key Elements of the Passive Solar Research Program (Balcomb/1 9 8 4 ) .P.57.

21 •

Much time is needed for defining, entering, and checking input data, as well as for checking the results.



Need for high computing power and long running time.



Need

for

extensive

distribution

flow

characteristics

information,

to

predict

and pressure the

air

flow

patterns to be used in the model. •

The models are formulated as research tools and not for public or professional uses.



The

models

are

evaluative

of

a

given,

designed

structure, and are not design tools. Different models, been

devoted

to

of all sizes and capabilities,

passive

solar

heating

analysis,

have

wherein

different passive solar systems have been tested and analyzed. Examples include the complex simulation model UWENSL et al.,

(Emery

1981), and the simple model of Van Weiringen & Viens

(1981).

2.5 Solar Rights and Shadow Analysis Solar access to buildings is an important constraint in the modern design of buildings.

More and more demands

for

solar neighborhoods call for site planning for solar access. Architects

and

protecting

solar

planners access

have for

always

been

collectors,

concerned

starting with

with the

concept of protected skyspaces. Knowles (1974,

1978) was one of the first to introduce

the Solar Envelope concept, defined as "the largest volumetric

22 container over a land parcel that allows solar access to all adjacent neighbors within useful time constraints". The solar envelope is a prism, with the land are tilted planes,

as the base, and its sides

defined by the solar constraints of the

neighbors, and the body of the building (see Figure 2.4). The solar envelope is a three dimensional geometrical shape which is hard to visualize and to use in specific design cases or in sloped terrain. The problem of this method is to define the intersection of the planes with the land and each other, and the true tilt angles of the planes.

Once the solar envelope

is defined, it offers a good tool to help in design. Moreover, it handles both the variations in the sun position in the sky and the building orientation at the same time. Erley and Jaffe (1979) have developed shadow templates or volumes at critical times and dates in the year to define solar

access.

They

determine

the

shadow

patterns,

on

a

horizontal plane, generated by any volume on the site, during the critical times and dates in the year, so as to avoid the shadowing of other buildings,

as shown in Figure 2.5. They

determined the patterns by assuming any critical point in the obstruction as a pole of a given height; next they calculated the shadow length on the ground at three times

in the day

(morning, noon, and evening, where maximum shadows occurs in different directions), and for critical days in the season. Finally,

the shadow projections at

the critical

times

and

dates where used to clear any obstruction. Erley and Jaffe

23

Figure 2.4: The Solar Envelope (Etzion,1988) P . 149

BLOG. "CSHADED BY BLDG. “A" TO SOUTHWEST

Figure 2.5: Templates of The Building Shadow Patterns & Jaffe, 1979) P . 82.

(Erley

(1979), proposed

in their planning 12

degrees

of

approach

altitude

as

for solar

access,

the minimum

have

angle

to

consider when calculating the heat gain exposure in winter. They believe that the sun at this altitude will have 45 to 50 degrees azimuth for most latitudes at Mid-Winter, especially in the northern latitudes (see Figure 2.6). The sun is in this position between 8:00 A.M.

and 4:00 P.M. at most latitudes,

and the energy collected during this time represents 80% of the total energy collection over the heating period. Having the sun striking a fixed collector obliquely, with a very big incident

angle,

results

in

a small

amount

of

energy

gain

(Erley & Jaffe 1979, and Berdahl et al.1978) . A South-oriented collector will receive 90% of the available radiation between 9:00 A.M. and 3:00 P.M. on December 21, and if oriented 35° to the South-East or the South-West it can be 90% as efficient as a South-oriented collector

(Barnaby et al.,

1977).

This

method considers full solar access, a n d requires strong zoning restrictions. Another method Robert and Thayer

to define solar

(1979).

access

is

proposed by

They define the " Skyspace"

of a

collector as the volume of sky to be free of barrier, as shown in Figure 2.6. Moreover, they define the surface made by the bottom of the collector and the minimum sun path in the sky (December 21), as the bottom surface of the sky space, and the surface between the top of the collector and the maximum sun path in the sky (June 21), as the top surface of the sky

25

3 p.m. J u n e 21

/9 a . n r M J u n e 21 ' j

Dec. 21 / 9 a.m .' D ec. 21

(S ) Critical S o la r S k y sp a c e N

/

g

S S o lar A c c e s s Z one

Figure 2.6: Critical Solar Skyspace Translated into a Solar Access zone (Me Pherson, 1984) P . 116.

26 space. The actual Skyspace is included in the space created by these two surfaces and its extent depends upon the pattern of energy utilization, which may be take place in summer or in winter or in both,

(see Figures 2.7 and 2.8) . This mode of

solar access guaranteeing also requires strong restrictions on the zoning process. A new method using computer analysis has been developed by Thayer

(1981). He defines a surface restricting barriers

in front of a collector, as shown in Figure 2.9. His analysis is conducted by assuming an imaginary grid in front of the south side of a building, and a vertical pole at each node of the grid, with a maximum height so as not to cast shadows on the

collector

when

exposure

is

needed.

This

method

needs

intensive computation. Etzion (1982) has proposed to define solar access as the boundaries

of

a

barrier

between

the

sun

and

the

solar

collector, that would cause no interruption in collector solar exposure, as shown in Figure 2.10. This technique is based on a geometric analysis but, like all the previous ones, is not practical for planning purposes. Different models have analyzed the thermal interactions between a building and its surrounding environment, and some of these models have considered building orientation and solar accessibility.

Enders

(1982) has proposed a numerical model

to enable the planner to assess and improve the energy budget of a building added to a built-up site, considering the

27

S p ace heating (Winter use)

(T

l

■JUN VL^: Domestic Hot W ater & Spa (Year-round use)

Vegetable G arden & Swimming P ool (Sum m er u se )

Figure 2.7: Specific Skyspace Configurations for Space Heating, Domestic Hot Water and Spa Heating, and Swimming Pool Heating (Me Pherson, 1984) P.122.

28

Clerestory

Slope S o u th

Slope

Latitude

T exas

Function

S pace Heating

Sw im m ing

Pool

North

Figure 2.8: Solar skyspace Dependent Upon a Variety of Factors, Including Collector Location, Slope and Latitude (Me Pherson, 1984) P. 117.

29

Z one B Z one A,

Z one B

Z one C

Z one C -

Z o n e A: T rees should not penetrate surface Z o n e s B & C: No heightlimitations.

Figure 2.9: Computer Generated Surface Representing Maximum Allowable Height of Obstruction, for Solar Access Protection (Thayer, 1981) P . 122.

30

SUN(H1)

:h 2)

:h 2)

Figure 2.10: The Area in a Barrier to be Out of Obstruction, in Order to Protect the Solar Access of the Collector (Etzion, 1988) P . 153.

31 shadowing effects of all fixed environmental features. This model also offers the possibility of changing the orientation of the building to obtain the optimal design orientation in any

specific

site.

This

option

allows

for

improving

the

building in the design stage. Three dimensional shadowing is calculated, and shadow indices are defined to help in choosing the

optimal

building

orientation.

This

model

is

good

in

defining the optimal solar access for a building in a built-up site, but it does not provide the option of site planning for solar access on the entire site. All traditional methods of assessing shading in a site provide

information

particular hour

only

for

a

given

point

in

and d a y ) . The designer must then

time

(a

consider

several different conditions over the exposure period, which is not practical in planning for maximum solar access. Smith and Wilson (1976) present a computer program that provides a rapid

and simple means

of determining the distribution of

shading over any exposure period for any set of buildings. The user is required to define the site, the exposure period and the

buildings

dimensions.

The

output

of

the program

is

a

contour map showing the average shadow distribution over the site,

in ten degrees of intensity,

2.11,

ranging

from total

exposure

as illustrated in Figure to

the

sun

to

complete

shadow. The program also allows interactive design (change in the

design), to

avoid

shadow

casting

over

buildings.

The

problem with this program is that it calculates the shading

/ ^ f / # / f ^ / / / / / J ti n

i////^////«ittntttitutiiiituiutuutititiiiiituuiitti>ttiiiiiuiitiiif/>/^////>/^'ij)iiiii ■i | / / / / l f / « / / 4 t U t t U \ l l l t t 1 t U U 1 t l 1 l t U l l l l t l l U l t t l t U I I t U l t H t l | l l t | l t | | | k i / / / / > / / / / / l i / i / i i IIII 11

l e u a (di f i i i i i n i i i i n i i j i i i n n i i i i i i i i i i i i i i w i i m i i u i i i m i n i i n i n i i

iirr

r [ - l i m n iJ

i//M //////H tiu u n tin itiiM iiiM tiiiiiiM i(itM iiim v u ji« ii iiitittiiiit» ////i////ii/W iiiM iiii l//////////hlltlltnilM|||MHt|l•■•••

11 !••••••••••#* !:/f/A tfel I.......... -.M in iy /A ty

....................

/ n i i l l * * « .............. ..

^Mll f i a / i !••••••■

f m tiM !--••••

Tllttl/MI I!•••*••'

• in n : 111: 11•
«’ S

31To

If » ( • :(«

I I TO JO TO

70 » C ‘ CC»r S » » o i t j it » t » C t T f S xa S 'T S

• IfosCSCrrj

II TO

gr

0 *C 0®CSCtTs

70TO 133 » c * c c » t S«» 0 | s s

J«4jiTS

Figure 2.11s Shadow Percent Contour Plan (Smith & Wilson, 1976). v '

33 in the horizontal surface and in terms of the maximum possible hours

of

sunshine,

and therefore takes

no

account

of

the

actual meteorological conditions at the site, thus making the shadow patterns inaccurate. Research

in

solar

energy

has

expanded

in

various

directions and into more specific areas, one of which is the study

of

houses

density

in Milton

and

overshadowing

Keynes,

a

for

new town

new

passive

in England

solar

(Cathian,

1982). Solar and typical land use data were fed into a simple housing

layout

typical

house

model,

which

frontages

and

simulated

the

densities.

performance

Cathian

found

of

that

single-story and narrow-frontage two-story housing suffer less from overshadowing. by

introducing

Solar access was improved in some cases

taller

(three-story)

buildings.

Cathian

demonstrated that the proportion of the buildings (height to width

of

density, solar

the

exposed

front)

in the

site,

in

contrast

to

is an important factor in determining the level of

access

estimate

at

a

site.

shadowing

approaches.

Guldmann

Other

effects (1980)

researchers

on

a

tried to

site

have

using

tried

to

different

allocate a number

of

buildings to a development site while maximizing an economic efficiency

criteria

including

costs

and

benefits

of

land

development and energy supply. He found that full solar access throughout the day for all planned buildings at a site may be impossible, and the only way to achieve it is by reducing the site density, which may lead to economic losses. On the other

34 hand, using traditional land-use allocation models may as well lead to energy costs losses. The optimal solution, which lies between those two extremes,

is obtained using optimization

techniques that combine the benefits of an efficient land-use pattern and those of optimal solar energy utilization. Some planners have proposed zoning changes to protect solar access

(Fregonese,

limits etc..

Others

1980),

including

(Erley & Jaffe,

1979)

setbacks,

height

have proposed to

apply solar protection to all land parcels in a democratic process. They were criticized because they subject every land owner to more restrictions, even if she/he has no interest in solar (1980)

energy

utilization

(SolarCal

1981).

Bruke

&

Lemons

proposed a practical form of solar protection between

willing people by using solar easement agreements, which they define as follows: A solar easement is a private contractual agreement between two property owners granting the right to unobstructed sun-light to one property owner across the property of another.

Figure

2.12

illustrates

some

types

of

proposed

solar

easements.

PART TWO: Energy

WIND IMPACTS savings

through wind

control

are

derived

from

reduction in air infiltration and heat convection, as well as from natural cooling in some locations. In the past, builders

35

(§) Uniform height limit

(§} E n v elo p e with s lo p e d top

©

Bulk p la n e at a sp ecified an gle

t3 )C om plex su rface d e s c r ib e d by sun an g les, d a te s & tim es

Figure 2.12: Solar Easements: Various Physical Descriptions (Me Pherson, 1984) P . 120.

36 used to design protective f e a t u r e s

against the troublesome

effects of the wind, as can be seen in old cities where heavy constructions with small openings were flows.

Some

protected

of

side

these of

old cities a

mountain

Mediterranean architecture,

used to control wind

were or

established even

in

a

on

the

valley.

for example has benefitted from

the wind by utilizing it for natural ventilation.

2 .6

Wind Generation The unequal distribution of the sun's heat on the earth's

surface produces varying densities in the atmospheric mass. The rising air of the equatorial zone moves down around the 38th latitude and then towards the North or the South where it meets,

cold polar air flows. The earth's rotation causes

the flow a n d motion of the air. The inclination of the earth causes seasonal variations. The variations in the distribution of

lands

and

oceans

causes

distortions

in

the

series

of

atmospheric pressure belts. Moreover, the local geographical characteristics

of

an

area

greatly

affect

the

prevailing

winds.

2.7

Wind Pressure and Air Infiltration Ventilation is necessary

for health reasons,

and part

of it happens through air infiltration into and out of houses. H i g h rates of infiltration happen when wind speeds are high or

structures are poorly insulated,

and may exceed what is

37 needed

for

ventilation.

Such

high

rates

of

infiltration

produce large energy losses. Air infiltrations around windows, doors, and through pores in walls, are due to a difference in pressure between the inside and the outside air. This pressure difference is mainly due to the wind flow around the building, and the difference in the temperatures inside and outside of the structure. The major effect of windbreaks is in reducing wind speed and air infiltration, thus reducing building energy requirements. Air infiltrations are created by the air flows around and over

a

building,

pressures

on

the

which

produce

building

a

exterior,

region

of

which

smaller than the average indoor pressure

differential

are greater

or

(see Figure 2.13).

Wind pressures are positive on the windward wall and negative on the leeward wall. will

force

the

windward side, leeward side.

air

This pattern of pressure distribution to

infiltrate

into

the

house

in

the

and to exfiltrate out of the house from the Figure 2.13

shows the pressure distribution,

using a laminar flow in a wind tunnel. Usually the w ind flow is turbulent after the windbreak,

and it causes differences

in

level

pressure,

depending

upon

the

of

turbulence.

effect of turbulence on air infiltration is complex, has been analyzed by some researchers

The

but it

(Blomsterberg & Harrje,

1979) . Temperature-induced air infiltration is more important in winter than in summer. The air inside a building in the

38

WIND

-10 1

[ 1 f/

— —

|f)r o n tR r o o f (-i\

10-1

Em

FRONT WAU,, 0 WIND HORIZONTAL PRESSURE DISTRIBUTIONS VERTICAL PRESSURE DISTRIBUTIONS

Figure 2.13: Pressure Distribution (Relative Magnitude of Pressure Indicate by Hatched Area) on Surface of Test House in Wind Tunnel (Buckly et al., 1978) P. 167.

Warm interior, cold exterior, no wind

Figure 2.14: Idealized Pressure-Difference distribution across the walls of a building Due to Insideto-outside Air Temperature Differences With Cold Outside Temperatures (Senden, 1978) P.167.

39 lower level starts to heat and rises up toward the ceiling, then flows out of openings in the upper level of the building. On the other hand, cold air flows into the buildings through lower level openings. This wind infiltration process is known as "The Chimney" or "The Stack" effect. As shown in Figure 2.14,

a neutral pressure level exists,

at the height where

there is no difference in pressure between the inside and the outside. mainly

At on

other

the

levels,

distance

the

from

pressure the

difference

neutral

level,

depends and

the

temperature difference between the inside and the outside air (ASHRAE,1977;

Mattingly,

Harrje

&

Heisler,

1977).

The

relationship between infiltration and temperature difference is linear.

2.8

Relative Importance of Air Infiltration Heat Loss Infiltration and conduction heat losses through a house

envelope for

a

(external walls,

reference house

roof and windows)

during

a

typical

were estimated

heating

season

in

Madison, Wisconsin, by De Walle, Heisler & Jacobs (1983). Air infiltration losses represent one third of total heat losses, which

is consistent

with

other

rule-of-thumb estimates

by

Mattingly et al. (1979). Wind infiltration is proportional to the square of the wind speed,

thus infiltration heat losses

on windy days may exceed fifty percent of total heat losses, depending on building tightness and exposure to winds. Exposed buildings usually have high rates of air infiltration,

and

40 need to be protected. The energy savings derived from their protection may be important.

However, in urban developments

with closely spaced houses, buildings protect each other, and there is little benefit from additional protection. Bates

(1945)

was the pioneer

effects on energy requirements (1982), Mattingly & Peters

in evaluating windbreaks

in buildings.

Harrje et al.

(1977), and Woodruff

(1954) have

evaluated tree effects on the energy needed for heating model houses.

Flemer

(1974)

has

conducted

a

study

in

which

he

compared the fuel consumption of a house before and after a tree windbreak was installed. He found out an average of 10% energy savings throughout the heating period. Energy savings may be very important in case of leaky or exposed structures. Dewalle

et al.

(1983)

have

estimated a potential

seasonal

savings of 12% when using a single-row evergreen windbreak. In a farmhouse with 30% infiltration heat losses in winter, tree windbreaks on all sides would yield a 50% reduction in air infiltration, and thus about 17% energy savings. There are three mechanisms by which windbreaks reduce the average wind speed horizontally.

First, the frictional drag

of the windbreaks absorbs some of the wind energy,

as the

moving air passes through and around them. Second, windbreaks direct barrier,

winds

upward

especially

windbreaks. Third,

to

higher

in

the

levels,

case

of

to

dense

flow and

over

the

nonporous

they change smooth, horizontal air flows

into random directions flows, which generates air turbulence

41 at the windbreak. The three mechanisms work with windbreaks of various structures in different degrees. Different studies have investigated the effect of windbreaks in reducing average horizontal wind velocity. Van Eimern et al.

(1964) have shown

that the height and density of the windbreak affect the extent of its protection. However, in case of very high barriers, the previous relationships may not be true. The distance of the building from the wind break is usually expressed in terms of windbreak

height

(H) . Figure

2.15

shows

wind

measurement

results for various windbreaks, when the wind is perpendicular to a long, narrow windbreak on a flat plain, with no other construction around. The speed of the wind is sharply reduced near the windbreak, with a minimum reached within 10H of the windbreak. The reduction in wind speed can be as high as 90% of the full speed. The wind gains back its speed at a distance ranging

from

20H

to

50H

downwind.

This

distance-related

reduction pattern applies to any height from the ground up to 0.75H. It is important to analyze the effect of windbreaks on the

mean

flow

for

many

reasons,

including

the

effect

on

building energy use. The distance at which a windbreak reduces the speed of the mean wind by a significant amount (say 20 % of open wind speed) is more important than the total distance over

which

there

is

wind

speed

reduction.

The

overall

effectiveness of the windbreak is evaluated by the average of all the reductions at 1-H distance intervals in the leeward

42 of the windbreak. For landscape design, another useful measure is

the

average

downwind.

reduction

This measure

describing

the

between

the

windbreak

is easy to calculate,

effectiveness

of

shorter

and

is useful

wind

breaks,

10H in and

covers the greatest reduction zone, which is proportional to the windbreak density.

Figure 2.15,

shows that a nonporous

windbreak provides the maximum reduction in wind speed. Using wind tunnel analysis, Van Eimern et al (1964) found that the medium

permeability

(20%

to

40%)

windbreaks

produce

the

greatest overall reduction in horizontal wind speed, and for a

longer

distance

in

the

leeward.

For

most

vegetative

windbreaks, the maximum reduction is about 60% to 85%, and a reduction greater than 20% occurs at 15H or 2OH downwind. The performance of a windbreak is affected by its shape, and the cross-sectional width to height ratio. However its density is more important. Van Eimern et al.

(1964)

windbreaks of equal overall density,

found out that for

the speed recovery is

slower with an increase in windbreak width. The

effectiveness

of

windbreaks

approaching air flow is smooth,

is

greater

when

the

than when it is turbulent.

Turbulence increases the mixing of the air in the leeward of the windbreak, and brings down the fast moving cold air. There are

two

factors

that

can

increase

the

turbulence

in

the

approaching air. These are the roughness of the ground surface and the instability of the atmosphere (in sunny days, when the ground is heated, the rising warm air creates turbulence) . In

43

* 100

WIND Very loose* b ells - - “Loose* bells

S p ttd

•— Medium bells D ense b elts V ery dense belts

O

10

20

O isto n c e f r o m th e w in d b reak , H

Figure 2.15: Average Wind Speed at Shelter Belts of Different Degrees of Permeability (Naegell, 1946, Cited in Caborn, 1957) P. 169.

44 an experiment with a 50% pores fence,

it was found that the

protected distance decreases from about 2 OH when the field is smooth to 15H when the field is plowed (Seginer, 1945). Wind velocity increases when the wind flows through constructed space,

such as high buildings in urban areas. This kind of

problems can be alleviated by planting tree windbreaks (Durgin & Chock, 1980) . Near a windbreak, within the area of greatest wind speed reduction, the temperature is about 5° F warmer in clear days (Van Eimern et al., and

slightly

cooler

1964; and Woodruf,Reed & Chepil, in

clear

nights.

The

1959),

evaporational

cooling is not significant at the site, because the air cooled by

a narrow windbreak is quickly mixed with the larger volume

of air moving through the windbreak. In a study of the effect of vegetation behind the windbreak, Parker (1981) has reported on experiments near Miami, Florida, showing that the surface temperatures of a mobile home shaded by vegetation were up to 24° F cooler, and that the air temperature within the shrubs were as much as 13° F cooler than the ambient temperature. The pattern

of wind

speed

and

direction

at the

site

greatly affects the optimum windbreak location. It should be located to protect the building from the most frequent cold air in winter, so as to reduce energy losses. In the U.S., the cold air usually comes from the West and the North/West, but this common direction may vary according to site topography. For an exposed house, any protection (even only two trees) may

provide savings, as found by Harrje et a l . (1982) . The distance between the windbreak and the point of maximum reduction is considered

as

the

optimum

distance

for

reducing

wind

infiltration. Harrje et a l . (1982) suggest this distance to be 2H to 7H for dense windbreaks, and Woodruff simulation

model,

showed

that

2H

(1945), using a

provides

for

maximum

reduction. De Walle & Heisler (1983) have suggested 1H as the optimum distance to locate a windbreak from a mobile home. For latitudes

between

35 to

50

location is at about 50 ft

degrees, (15m)

the optimum windbreak

from the structure.

It is

very important for the windbreak not to block solar access for the building in winter.

Stockeler and Williams

(1949)

have

analyzed vertical flow patterns for three different types of tree barriers

(differing

in density). They

found that the

effect of the barriers on velocity reduction is very small beyond a 2OH distance. Thermal performance, building orientation, and building design must account for the impact of winter winds and summer breezes.

Combining optimum solar orientation with optimum

breeze collection and wind protection,

is the simplest and

most direct approach. However many wind protection strategies are still subject to debate. Olgyay (1963, 1973) presents the following guidelines for the design process: •

Orient the facade with least windows to the wind side.



Orient the smaller building surface to face the wind.



Position the building at 45 degree angle to the wind.

46 The

45

degree

position

reduces

wind

velocity

on

the

building by 50% to 60%. However, another study by Mattingly, Harrje & Heisler (1979), which was conducted to measure air infiltration rates of model homes

in

a

wind

tunnel,

indicates

that

a

45

degrees

orientation to the wind results in the highest infiltration levels, which contradicts the previous orientation proposal by Olgyay.

Furthermore,

Olgyay found that parallel rows

of

buildings shelter the ones behind them, and that the main wind stream tends to rise above the units

after the

first row,

flowing over the others behind without hitting them. Placing a wind break upwind of the first row of buildings will give maximum

protection.

Staggering

units

will

allow

breeze

penetration. If cold winter winds and cooling summer breezes are perpendicular to each other, buildings can be oriented so that cold winds face parallel rows,

and cool breezes strike

staggered buildings.

2.9

Infiltration Models Air

infiltration

nonlinear

phenomenon

building,

its

into

and

depending

environment,

and

out on the

of many

structures details

deriving

of

forces

is

a

the (the

pressure difference between the inside and the outside of a space). Exact infiltration calculation methods for existing building do not exist, and only approximation techniques can be

used.

This

is

due

to

the

nonlinearity

characterizing

infiltration loads, which are proportional to the temperature difference, but also depend on wind velocity. To calculate air infiltration,

approximation techniques range from simple to

complex. There are two types of infiltration models simulating the air flow in a structure under given climatic conditions, with varying capabilities and building sizes. The first type simulates the air flow

in a single-cell structure

(single­

family house). These simple models yield reliable estimates (Sherman & Grimsrud 1980, The

second

chambers.

type

Sherman 1987, and Ethridge 1988).

simulates

the

air

flow

in

multi-cell

The advantages of a multi-chamber model are that

they consider larger buildings and calculate the air-mass flow interactions

inside

the

building.

The

air-mass

flow

is

important to achieve air movement between different zones in a

building.

For

a

given

building,

the

air-mass

flow

distribution depends on pressure differences, whether it is generated by thermal buoyancy,

wind, mechanical ventilation

or a combination of these factors. A literature review of multi-chamber infiltration models has

inventoried

computerized,

models.

including

(1978), Walton de Gid s

15

(1977),

(1983),

Most

of

the models

of

Pedersen

Brinkmann

these Evers

models

& Waterhouse

(1977), Gabrielsson

(1980),

Swetlov

are

(1966),

(1968), Cockroft

(1979), Cockroft (1982), Bilsborrow (1973), and Pitts & Wards (1983) . These models have much similarity.

They use similar

equations to describe the air flow in buildings, and some of

48 them

use

the

same

method

to

solve

the

set

of

nonlinear

equations (Newton's method of iteration) . They differ in their ability to simulate

mechanical ventilation, and some of them

do not simulate the forced ventilation

(when a large amount

of air is needed in a space for a specific reason,

such as

removing odors or excessive humidity in a restaurant kitchen) . They also differ in the number of rooms they can handle. These models are not validated due to the difficulty in measuring air

infiltration

in

multi-chamber

structures.

The

multi­

chamber infiltration models analyze the air flow in buildings considering the effects of internal flow restrictions. They need large amounts of information about pressure distributions and flow characteristics. These models are too complex to be used for simple structure infiltration simulations 1985),

(ASHRAE,

and have been developed primarily as research tools,

and not for the use of professional engineers. New

methods

have

been

developed

for

infiltration

calculations. Klems (1983) has reviewed the mechanism of air infiltration as a background for introducing a procedure that yields more reliable estimates of average infiltration rates through

a

techniques

window used

unit. to

Feustel

obtain

(1990)

leakage

has

data

compared

for

two

multi-zone

buildings, using the standard equipments used for single-zone leakage data. Application type dictates the choice of model type and complexity.

Presently the Air

Infiltration and Ventilation

49 Center in the United States is preparing a guide to help users decide which model to use.

Clearly,

there is much need for

practical and accurate air infiltration calculation methods.

2.10 The Effect of Wind on the Energy Consumption in Buildings The energy consumption of a building is largely affected by the surrounding environment environmental

variables

consumed are: wind,

that

shading,

(Arnes & Williams 1977). The affect

the

amount

of

energy

humidity and temperature.

The

effect of wind depends upon: 1. The air infiltration into and out of the building. 2. The surface heat transmission. 3. The efficiency of the mechanical system. 4. The enclosure of the outdoor spaces.

2.10.1 Air infiltration Heat losses due to infiltration in residential areas are very important, and may cause between 30 to 75% of the total heat loss in winter (Mattingly & Peter 1977). Wind speed and direction affect the air pressure distribution on building surfaces. This wind pressure controls heat transfer through pores in the walls and the roof. The distribution of the pressure depends on: •

The aerodynamics of the buildings and its relationship with

its

surroundings,

distribution

on

the

which

building

determine

the

pressure

surface.

The

pressure

50 increases in the windward, and decreases in zones where the speed of the flow has increased (the corners and the ridge of the roof - see Figure 2.16). •

The

aerodynamics

wh i c h

affect

window

and

different

of

the door

from

architectural

pressure

pattern

casements,

the

surface (Leutheusser,

overall 1970)

surface

features,

especially

where

the

pressure

of

around

pressure the

is

building

(see figure 2.17).

A i r infiltration heat loss is proportional to the amount of flow through openings or cracks. related Williams,

to

pressure

and

incident

As for the flow, wind

velocity

it is

(Arnes

&

1977).

In the case of microscopic pores, with laminar flow and pore diameter < 0.1 inch, we have:

q

oc A P « u2 ,

where q = a

the volumetric heat flow (discharge).

P = the pressure difference between the interior and the exterior

u = is the exterior wind speed

In the case of larger cracks openings, with orifice flow and crack diameter > 0.1 inch:

q etfuFcat

• 0 TurW «ntft m tenrty tlo.il te Mrfac*

0 V flecity d a t a —

Plan

t o w iif a tt

ftcn scd window casement

Figure 2.17: Characteristics of Air Flow Across a Building Near a Recessed Window Casement (Arnes & Williams, 1977) P. 78.

52 Dick (1949, uninhabited average

town

approach

1950) has found that air change in closed, houses,

is

velocity

directly

(wind

proportional

velocity

change

to

the

with

the

height from the ground), whereas in occupied houses this air change is complicated by other factors, such as human comfort (as wind velocity increases, people start to close windows). Members of the Princeton study group at Twin Rivers, New Jersey, have performed wind tunnel and full-scale infiltration tests

on a row of two-story town houses,

to determine the

interaction between infiltration and building orientation protection.

They

found

that

the

rate

of

and

infiltration

is

strongly affected by the direction of the approaching wind and the level of protection (the position of the individual houses in the town house r o w ) . They found that infiltration may vary by 50% under different orientations. Moreover large values of infiltration can be reduced by sheltering the houses using vegetation and landscaping.

2.10.2 Surface Heat Transmission Heat affected

transfer by

the

from wind

and flow

to

the

around

building the

surface

building.

is

Heat

transmission increases energy losses in a building. Convection heat transfer, from and to the walls and roof of a building, is activated by air turbulences flowing around the building. The method used to calculate this wind effect is based on

53 •’Reynold's

Analogy".

Heat

losses

following equations (Schalichting,

are

derived

with

the

1968):

Nu = 0.5 * Re * Cf

(2.8)

(hc * x) / k = (0.5 * u * x * Cf) / v

(2.9)

Or

where Nu = Nusselt number. Re = Reynold's number. hc = Convective transfer coefficient. k

= Conductivity.

u

= Wind velocity.

v

= Kinematic viscosity.

x

= Length from the leading edge.

Cf = Surface drag coefficient.

The convective transfer coefficient (hc) for a given fluid is proportional

to

its

conductivity(k), the

inverse

of

its

viscosity(v), and surface drag coefficient(Cf) . Then, for air with a given conductivity and viscosity, the surface drag coefficient only, wind

velocity

raised

to

(hc) is a function of

which is proportional to

an exponent

between

0.5

and

depending upon the turbulence of the wind flow, with:

cf OC u t where 2 £ n £ 5.

0.8,

54 As

heat

transfer

mechanisms

include

convection,

conduction, and radiation, it follows that convection explains only

a

part

of

heat

transmission.

Total

heat

transfer

q

through radiation, convection, and conduction is represented as:

q =

U * A * aT ,

(2.10)

where A

= the area

aT

= the temperature difference between interior

and

exterior air. U

= the wall coefficient of transmission.

The coefficient U is obtained as:

1/U = R, + F„ + Rr*Rc/ (Rr+Rc) ,

(2.11)

where

Rc

Ri

= Resistance of

interior surface.

R„

= Resistance of wall.

Rr = Resistance of

exterior surface radiation.

R0 = Resistance of

exterior surface convection.

is the only value affected by the external

wind, which

means that U varies with wind velocity. Wind for

poorly

effects on heat transmission are significant insulated

materials;

with higher

only

surface drag

55 coefficient materials velocity 2.18).

on

The

(e.g.,

surface heat nature

building affects

of

the

concrete),

transfer

the

is

the effect of wind minimal

approaching

wind

(see

flow

Figure

around

a

flow pattern and the convective heat

loss. Practically, these losses are found to be muc h larger than what is calculated using " Reynold's Analogy". Sturrock (1977)

has

found

that

convection

heat

losses

for

simple

building shapes are about 50% higher than the values predicted using "Reynold's Analogy".

2.10.3 The Efficiency of Mechanical Systems The wind flow around buildings affects the locations and effectiveness of ventilation

inlets and exhausts. The energy

requirements of a mechanical system (e.g., cooling towers) is affected by

the wind

inadvertent

exhaust

in two major ways. that

reduces

the

First,

it causes

cooling

equipment

efficiency. Second, the wind pressure increases the fan power requirements

and the

energy

loss.

Exhausts and

inlets

are

placed away from each other, which increases the cost of the mechanical

systems

to

overcome

the

previous

two

common

problems. In order to minimize these losses, the knowledge of wind influences is important. daily 20-30 mph sea breeze,

In San Francisco, there are examples

during the of

cooling

towers on high-rise buildings that loose 70% of their cooling capacity, representing up to 5% of the total energy losses in a high-rise.

S " ' j ' c w e n c 9' j h

u»mg COnveCbOn

C P r 1 l< ie * tt

miMJuied o n budding

l u 'U i r i iStui'Ock, 1971) S in g le ptne gins u t m g c o n v e c t i o * COfHiCients d e r iv e d in U m in e * - X

Figure 3.5 : Defining the Walls that Face The Sun, and the Walls that Cause the Shadow.

79 and A define walls CD and DA

as the walls of building B2

that face the sun.

3.1.3 Wall Shadow Area ftalculation The model analyzes the exposure of the complete wall area

(solar glazing all over the wall), unless windows are

part of t h e wall. Figu r e 3.2 presents the flowchart for wall shadow a r e a calculations. The base lines of the walls facing the sun a r e divided into a number of intervals, as shown in Figure 3-6. This number depends on the accuracy needed, and on the computing power available. In our case study we use 50 intervals for each wall. The

process

used

to determine

the

exposed

walls

is

adapted t o determine the walls that create shadows. The model projects

the

building

corners

onto

the

origin

line

and

deletes t h e corner w i t h the projection closest to the origin O.

The

shadows

other on

three

the site

corners (Figure

define 3.5).

the

walls

that

create

Consider building B2 in

Figure 3-5; the projections of its corners E,F,G, and H on the origin

line ON

are points

5,6,7,

and

8 respectively.

Point 8 is closest t o O, thus the model deletes corner H, and corners E , F and G define walls EF and FG as the walls of B2 that create shadows- Each wall creates a shadow area behind it, depending on the solar angles- Consider walls EF and FG

80 in Figure

3.5;

wall

EF creates behind

it the

shadow area

(EIJF) , and wall FG the shadow area (FJKG) , where El, FJ, and GK represent the shadow length at the ground level, using the azimuth direction.

Starting clockwise

from the

first wall

corner of the building currently analyzed (say building Bi, starting

at

the

edge

C) ,

we

take

each

wall

slice

successively. Each slice base is an interval width, and its height is the building height. The mid point of the slice is the center of the interval. The model checks if the mid-point (MP)

of the interval is located in the shadow area that is

created behind the walls (areas EIJF and FJKG in Figure 3.5) . If the mid-point is not in the shadow area, then the slice is not shadowed by these walls. The model then proceeds to the next slice. If the mid point is located in the shadow area, then the shadow height is computed (see Figure 3.6). The geometric relationships between the height of the wall that causes the shadow mid-point creates

(Hz), the distance between the

(MP) and the corresponding part of the wall that

the

shadow

L,

the

shadow

length

SL,

the

solar

altitude 6, and the shadow height SH are summarized by the following formulas (see Figure 3.7):

SL = H2/ tan 6

(3.5)

SH = tan R * (SL-L)

(3.6)

D D 0 D

h2i

hi i 1

Wi

MPMP di

^|< di >

>.

ELEVATION

(X1.Y1

(X2,Y2)

m

T ^

PLAN Figure 3.6: Wall and Window Shadow Calculation.

(X3lY3)

1-

82

H2 HZ

ATP

$

L SL

Figure

3.7

shadow

ght Calcmatlon

r^., ^

83 The model

checks

if the calculated

shadow height

is

greater than the previously calculated height for that slice, as a result of the shadow created by another building. This process

thus

guarantees

accounting

for he

maximum

shadow

impact over that slice in any specific hour, up to the top of the wall. The program then checks whether the current slice is the last one. The shadow heights for all the slices in the wall are calculated for each wall separately, because solar intensities radiation

vary

from

incidence

wall

to

wall,

angle.

If

the

depending currently

upon

the

considered

building is not the last one creating shadows, then the model starts the process again with a new building. When the last building

causing

shadows

has

been

considered,

the

final

shadow area on the wall is calculated, equal to the sum of the areas of shadow slices, with:

SA =

Selioes D * SH

where D

= slice or interval width (m).

SH = shadow height (m). SA = shadow area on wall (sq.m).

(3.7)

84 3.1.4 Window Shadow Area Calculation This part of the algorithm is detailed in the flowchart in

Figure

3.3,

and

is used

only if the wall

has

partial

exposure through windows. The model considers a slice in the wall,

as before,

and

checks

if that slice

is covering a

specific window, in order to calculate the shadow height over that

window.

To

find

out

if the

shadow

slice

is

located

within the window base, the model checks if the distance from the wall edge to the mid-point (MP) of the considered slice is greater than d,- and less than the sum of d,- and the window width

w,-

(Figure

3.6).

If

intersect with the window,

the

shadow

slice

does

not

then the model goes on to check

the next window . If it does intersect, then the model checks the shadow height. the window base

If the shadow height is not higher than

height,

then

no

shadow

is

cast

over

the

window, and the model continues to consider the next window on the wall. If the shadow height is higher than the window base height,

then the model checks if the shadow is higher

than the window top. If the shadow height is higher than the window top,

then

the

shadow area

is

equal

to

the

window

height multiplied by the slice width. If the shadow height is not higher than the window top, then the model computes the window

shadow

exposure wall.

area

in

the

same

way

as

for

the

complete

The model proceeds with theses calculations

85 for all the slices of all the windows on the wall. Once these shadow area calculations are completed,

the energy gain is

calculated.

3.1.5 Energy Gain calculations In order window,

the

to

calculate solar intensity on any wall or

model

uses

equation

3.3

and

the

diffused

radiation calculated with eq. 3.4. F o r application purposes, the model considers vertical walls w i t h a tilt angle of 90° (ev) ,

and direct

radiation

IDN from

the

TMY's

data.

Then

equation 3.4 for incident energy becomes:

0.8* It = IDM * cos 6 * cos ( $ - e) + Id

Using Equation 3.8, azimuth

and

the

the model

incident

solar

(3.8)

calculates

intensity

the surface

for

any

wall

orientation at any hour. This incident energy is considered only for the clear exposed window or wall area. The shadowed Part of the window is considered as a North-oriented window with diffused radiation only (ASHRAE, 1989). The total energy gain for the wal l is calculated as:

T E = SA * Id + CA * I t where

(3.9)

86 TE = the total energy gain (k j ), SA

= the shadow area (m2),

Id= the diffused radiation intensity (ASHRAE, CA

= the clear area (in2),

It

= the solar intensity on

a

1989),

vertical wall (kj/m2.h).

The total energy gain on each wall is then added to the heating

or

cooling

accumulated

season's

separately

for

energy

each house

gains and for

site. As the model calculates the energy gains

or

losses,

the

entire

for all the

buildings on the site, it checks if the considered building is the last shadowed building in the site. If it is, then the model reads the next climatic data set

(new hour).

If the

last climatic data set has been considered, then the model computes the total annual energy gain for the site.

PART TWO:

A METHODOLOGY FOR WIND IMPACT ASSESSMENT ON A N URBAN SITE

3.2 Wind Infiltration Analysis and Energy Losses Calculations Energy losses due to wind infiltration are significant in

both

the

heating

and

the

cooling

seasons.

The

model

estimates the velocity of the wind that hits a building as an average

of

several

reduced velocities

resulting

from the

interactions of different buildings on the site. The volume

87 of air infiltration per hour is calculated as a function of wind velocity. The total energy losses for each building and the entire site, over the exposure period, and the cooling seasons these

model

(separately),

calculations.

In

the

for the heating

are the outcomes of

following

sections,

we

present some background data needed for the development of the simulation model for wind speed estimation in an urban site. The model methodology is illustrated by the flowchart on Figure 3.8.

3.2.1 Wind Protpntion Reduction Factor The reduction factors used in the model are taken from Woodruff's

(1954) experiment, as discussed in Section 2.12,

and from ASHRAE (1989). The reduction values adopted in the model are those for a plate barrier in an open area

(Table

3.1). We consider the plate barrier as the best barrier type to

represent a building barrier,

because both of them are

nonporous. Barrier density is an important factor that

Table 3.1: Wind Velocity Reduction Factors for a Vertical Plate

Velocity Reduction Distance

75%

50%

25%

13.OH

15.5H

21.5H

* H represents the barrier height.

88

Read air change rate tables for heating and cooling Read grid data Read climatic data

□sing the wind direction project the building into the Y-axis

Find max and min intersection points

Sort max and ain for all houses in ascending order

Hind corridor ** the space between each two consecutive intersection points

Find barriers in the corridor and their distances

Compute wind speed at each barrier in the corridor

Compute building average wind velocity

Figure 3.8: Wind infiltration calculations flowchart.

Figure 3.8:

(cont'd)

Compute infiltration heating losses

Camput e ventil ation heatin g losses

Compute infiltration cQoling losses

Accumulate losses for each house

Compute ventilation cooling losses

Read next climatic data Print energy losses '' End

Wind infiltration calculations flowchart

90 affects

the

reduction

in

speed

behind

a

barrier.

The

experiment was carried out at a constant velocity of 25 mph. With these reduction factors, the reduced wind speed at any distance behind the barrier can be computed, as:

UR = U0 * RF

(3.10)

where UR = reduced wind speed (m/s), UQ = original wind speed (m/s), RF = reduction factor.

Regressing

reduction

factor on

distance,

to

obtain a

general model, was not possible, because of the small sample size, and the obvious nonlinearity of the relationship (see Figure 3.9). Instead we use a direct interpolation method. We assume

that the

reduction factor is

75% for all

distances

less than 13H, so as not to consider a 100% reduction factor in the area behind the barrier, which is the site of the air flow turbulence. An interpolation line is used between any set of two consecutive points, and assumed to take place at 4 OH.

full speed recovery is

91

INDUCTION

FACTOR

100 *__

sox _

75%

10 H

distance

Figure 3.9:

from

barrier

30H

20m

(,n

barrier

m i i o h t

)

Reduction i n velocity w i t h distance behind the building barrier*

92 3.2.2 Air Infiltration Calculations The volume of outdoor air infiltration is affected by wind speed and direction,

and width of

openings.

air

There

are

less

changes

cracks o r in

summer

size of than

in

winter, due to the higher wind speed in winter. To calculate the volume of air infiltration, we select the air change rate method presented in section 2.13.2. The sensible and latent energy losses equations adjusted for the

metric

system are:

qs = 1.207 * V * n * (Ti-T0)

(3*12)

qx = 2936.76 * n * V (V>i - WQ)

(3*13)

The indoor relative humidity ratio used in the model is the ASHRAE includes

(1989)

a range

temperature.

relative of

Tables

humidity

humidity

ratios

3.2 and 3.3

comfort at

(ASHRAE,

ratio,

the same

which

interior

1989) a re used in

the model to calculate the infiltration rate as a function of building tightness and outdoor design temperature*

3.2.3

Building Tightness

Tables

3.2, and 3.3 apply to single and multi-family

structures. The tightness of buildings is a measure of the wind infiltration ability, defined as follows:

Table 3.2 Air Change Rates as a Function of Air Tightness and for 15 mph Wind Speed and Indoor Temperature of 68° F (ASHRAE, 1989)- Winter Outdoor Design Temperatures.

Outdoor Design Temperature Class 50

40

30

20

10

0

-10

-20

-30

-40

Tight

0.41

0.43

0.45

0.47

0.49

0.51

0.53

0.55

0.57

0.59

Medium

0.69

0.73

0.77

0.81

0.85

0.89

0.93

0.97

1.0

1.05

loose

1.11

1.15

1.20

1.23

1.27

1.30

1.35

1.40

1.43

1.47

Table 3.3 Air Change Rates as a Function of Air Tightness and for 7.5 mph Wind Speed and Indoor Temperature of 68° F (ASHRAE, 1989)- Summer Outdoor Design Temperatures.

Outdoor Design Temperatures, F° Class 85

90

100

105

110

Tight

0.33

0.34

0.36

0.37

0.38

Medium

0.46

0.48

0.52

0.56

0.56

Loose

0.68

0.70

0.74

0.76

0.78

VO

94 Tight;

Tight structures include (a) new houses wit h no fire

place, with well fitted windows, and weather stripped doors, with only one story, area,

and

and with

less than

1500

sg.ft floor

(b) multifamily constructions with close-fitting

doors. Medium; Medium structures include (a) two-story frame houses, (b)

one-story

maintenance, average-

houses and

a

older

floor

fit windows

than

area

10

of

and doors,

years,

more

and

a

with

than

average

1500

sq.ft,

fire place

with a

closure, and (c) below-average multifamily constructions with medium-fitting doors. Loose:

Loose

structures

fitted doors and windows,

include (b)

(a)

houses

with

houses older than

poorly

20 years,

with open fire places, and (c) mobile homes.

3.2.4 Outdoor Design Temperature The design temperatures (ASHRAE, 1989) are based on data from the National Climatic Data Center of the US /Vrmy, the US Navy, and the US Air Force. Winter There are two temperatures

for each station that are

equalled or exceeded by the 99% or 97.5% of the total hours in the months of December, January and February. there are

22 hours

(out of 2208)

In winter,

with temperatures

at or

95 be l o w the 99% quantile,

and 54 hours at or b e l o w the 97.5%

quantile. For Dayton, the winter dry-bulb temperatures a t the 97.5%

is



F.

This

is

the

winter

design

temperature

recommended for Dayton, Ohio, b y ASHRAE (1989) • Summer Summer dry-bulb temperatures represent v a l u e s equalled or exceeded b y 1% , 2.5% and 5% of the total h o u r s during the months of J u n e through September. There are 30 hours (out of 2958)

at or above the 1% design value, and 1 5 0 hours a t or

above the 5% design value. For Dayton, the s u m m e r dry-bulb temperature a t the 2.5% quantile is 89° F. This is the summer outdoor design temperature recommended by the A S H R A E Handbook of Fundamentals

(1989).

Interpolation is used in t h e model for outdoor reported

design in

temperatures

Tables

3.2

that

and

t h e values

are between

3.3

values.

of

the v a lues

However,

the

infiltration rates in Tables 3.2 and 3.3 are c o r r e c t only for the

wind

speeds

of

15

and

7.5

mph.

The

volume

of

air

infiltration into a given space is proportional to the square of the wind sp e e d (Section 2 .I0 .I) . To account f ° r different w i n d speeds,

a correction of the air change r a t e s is uaed,

proportional t o the ratio of wind speeds, with:

nc = nT * (U / UT)2

(3.13)

96 where nc = corrected air c h a n g e rate, n,, = Table (3.2/3.3)

air change rate,

U = the actual wind speed (mph), UT = Table (3.2/3.3) w i n d speed ( 15 and 7.5 mph).

Health a n d

comfort

are

minimum air change rate

of

the two 0.5 per

reasons hour is

for which

a

necessary for

ventilation. It is not a c o d e requirement, but it should be considered if t h e computed infiltration rate is less than 0.5 air volume per hour. When ventilation is used in a building/ special devices used.

It

is

considers

a

for control

worth

and energy recovery should be

mentioning

minimum

0.5

that

air

the

change

simulation

rate

per

model

hour

for

ventilation. Moreover, the model calculates losses and gains in energy consumption, considering the interior temperature of

68°F

in wint e r

and

75°F

in

summer.

These

values

are

recommended as energy conservation principles.

3.2.5

Description nf the Methodology

The simulation methodology for wind speed estimation, calculation

of

the

volume

of

air

infiltration,

and

calculation of energy losses is explained below. Figure 3.8 presents the flowchart of the methodology.

97 The data in Tables 3.2 and 3.3 are used to estimate the rate

of

air

change

per

hour.

We

use

these

tables

to

generalize the scope of the model and to give it the ability to work with any outdoor design temperature ranges. The model starts

by

reading

these

tables

and

then

the

grid

data,

exactly as for the solar simulation model. However, it also reads building tightness data,

which were not used in the

solar model. The same source of climatic data is used, but in this case only wind speed and direction are considered. For simulation purposes, we assume that the wind travels between and over the buildings in air corridors. We assume that each building facing the wind acts as a barrier, which is defined as follows. The model projects each building along the wind direction onto the Y-axis, in order to determine the corners that act as the ends of the building barrier (Figure 3.10). Each building has four Y-projections, the maximum and the minimum ones representing the building barrier extreme points. In order to define the wind corridors created on the site by the interaction between wind direction and location of buildings,

the model

sorts

the maximum and minimum Y-

projection values for the site in ascending order. The wind corridors

are then defined by

consecutive projection points.

the

space between each

two

Each corridor has a maximum

(Cmax) and a minimum (Cmin) Y- projections (Figure 3.10). In

98

Y

Bm ax7

B8

Bm ln7

i---

C m ax3 Cm in3 C m ax2

C3

Cm in2 C m axl

C2 r~ B&

B4 C m inl

Figure 3.10: Defining the Wind Corridors (Cl) and the Building Barrier (Bl).

99 order to find all the buildings located in a corridor, the model checks if a given corridor intersects with any building barrier, selects all such building barriers, and repeats this analysis for all the corridors. Practically, the model checks the overlap of the Y-projections of the corridor and the Yprojections of the building barriers. Within each corridor, the model assigns an order (rank) to all the barriers in this corridor

by

intersection building

calculating of

the

barriers

the

considered

located

in

distance

from

corridor

to

the corridor,

the

each

Cmin

of

the

and ranks

the

barriers by increasing distance. Distances between barriers are then

calculated,

velocity

reduction

to be used in the estimation of the factors.

In

barriers of different heights,

a

corridor

an average,

with

several

height-weighted

wind speed is calculated for each barrier (barrier width is the

same

at

any

height).

The

method

of

calculation

is

illustrated below. Consider a corridor C, with five barriers Bj (where j is the building index) (Figure 3.11). Dj is the distance between building (j) and the next building downwind. Hj is the height of building j. Rj is the reduction factor due to distance Dj. U cj is the average wind speed in corridor C hitting barrier Bj.

The

average

corridor

wind

velocities

that

barrier in this corridor are computed as follows:

hit

each

100

UC3^

UC5,

UC2

UC8

UC1

UC5 = UMAX

UC3. R3+2

UC5 = UMAX

UMAX

UC5.R5 B5 H5

UC3.R2 B3 H3

D5

B2 H2 D3

UC8.R8 B8 H8

D2

Figure 3.11: Wind Speed Calculation in a Corridor.

D8

101 Ucs

= Umax

(3.14)

Uc3

- (Uc5*R5*H5+ UBax*(H3-H5) )/ H3

(3.15)

Uc2

= Uc3*R3

(3.16)

Uc8

* (Uc2*H2*R2+ Uc3*(H3-H2)*R3+2 + Umax*(H8-H3)) / Ha

U=i

(3.17)

- U=8*R8

(3.18)

where Umax =

the open wind velocity

R3+2 =

the reduction factor corresponding to the sum of two distances behind barrier 3 and 2.

The model always takes the previous barrier and checks if it is higher than the current barrier. velocity

on the barrier

is equal

If so, then the

to the previous

average

velocity adjusted by the reduction factor based on the clear distance between the two barriers. If the previous barrier is not higher than the current one, then the reduced velocity of the previous barrier affects the portion of the current one that is equal in height, the other portion being impacted by the

next

higher barrier upwind.

This

process

is

repeated

until the complete height of the barrier has been considered. To

calculate

calculates the

the

average

building

velocity Uj,

width-weighted

velocities for that building. Each

the

model

corridor

building

consists

wind of

102 several

barriers

velocities

with

(Figure

different

3.12).

The

widths

model

and

average

calculates,

for

wind each

building, an average building velocity Uj, which represents the

average

corridors

velocities

UCJ-, considering all

barrier portions of a building barrier, width

WCj .

the

weighted by their

Then the building velocity is calculated by :

Uj =( Zc (Ucj * W CJ)) / Wj

where Wj = building barrier width

p.19)

(m).In the case of Figure

3.12, building B5 consists of three corridors Cu

C2, and C3,

hit by average corridor velocities U^, U25, and U35, and with widths w 15, w 25, and w35. Thus building B5 wind velocity

is

calculated by:

U5 = ((U15*w15) + (U25*w25) + (U35*w35)) / W 5

(3.20)

The model then analyzes the calculated building velocity into its components normal to the building sides which are hit by the wind. In Figure 3.12, these components are U5sinw and U5COSW. These two components are then used to find the different air change rates for the building sides hit by the wind, using Tables 3.2 and 3.3. The energy losses for the two seasons are considered separately in the model. The model

U5.Sinco

U5.Cosco

B5

U5.Sinco

cn S2 U5.C0SC0

5m

B5

Figure 3.12: Building Velocity Calculation and Its Components, for Calculating Air Infiltration.

104 checks

first

the

outdoor temperature.

If it is

less than

68°F, the model computes infiltration heat losses. Chapter 2 has discussed air infiltration and provided two methods for its calculation. The model methodology adopts the air change rate method for estimating the air infiltration per hour. In order to find the air rate change per hour if temperature is less than 68°F, the model uses the data in Table

3.2, the

outdoor winter design temperature of 4°F (ASHRAE, 1989), and data on building tightness. A correction of the air change rate is needed if the velocity component for any side of the building is not equal to 15 mph. The adjustment is:

nc = n * (U/15)2

(3.20)

where nc = corrected air change rate, n

= original air change rate,

U

= wind speed,

15 = the wind speed for Table 3.2 (mph).

The sides of the building that are hit by the wind are impacted by air infiltration

(Figure 3.12). Meanwhile, the

other sides and the interior middle parts of a building are not affected by the wind and its infiltration. Then, only the part of the building in contact with the wind is considered

105 in infiltration losses calculation. The volume of the exposed spaces is represented by the row of the outer rooms, and is computed as the product of the building front length by the outer room depth (5 meters)

by the height of the building.

Assuming that the building sides are St and S2 meters long, the room depth is 5 meter, and the height of the building is H meter, then the

energy losses due to air infiltration are

expressed by:

qs1- = 1.207 * ( 8 ^ * 5

+ S2*n2*5)*H * (T{ - T0)

q u = 2936.85 * ( S ^ n ^ S + S2*n2*5) *H * (W, - W 0)

Equations

3.21

and

3.22

are

directly

derived

(3.21) (3.22)

from

equations 2.21 and 2.22 developed in Chapter II. A minimum of 0.5 air change rate per hour is needed for health reasons

(section 2.15). Ventilation heat losses are

computed as: For

nfc 0.5

qsv= 1.207*

( S ^ n ^ S +S2*n2*5

+ 0.5*(S,-5) (S2-5))*H*(Ti-T0)

q lv= 2936.85* ( S ^ n ^

+S2*n2*5

+ 0.5*(8,-5) (S2-5))*H*(W,-W0) where

(3.23)

(3.24)

106 qsv = sensible ventilation heat losses (kj/h). q lv = latent ventilation heat losses (kj/h).

The

calculation

knowledge

of

the

of

hourly

latent

energy

relative

losses

humidity

of

requires the

site.

Because this data is not available in the climatological data base,

we

were not able to precisely

calculate the

latent

energy losses. However, the model estimates the latent energy losses using the

indoor ASHRAE

Comfort

Relative

Humidity

(Figure 3.13). With the summer indoor temperature of 75° F (23.9 C°), the range of the comfort ratio Wj is (23% - 64%]. The model checks if W 0 is in the summer comfort range. If so, it does not add any latent energy losses. than 64%,

If W0 is greater

then the model sets W { at 64%. If W0 is less than

23%, then Wj is set at 23%. Winter latent energy loss calculations are done using the

same

procedure,

but

with

a

winter

comfort

interior

temperature of 68°F (20 C°), and an indoor relative humidity winter comfort range of [50% - 82%]. The model first checks if W0 is in the winter comfort range. If so, then no latent energy losses is added.

If W0 is greater than 82%, then the

model sets Wj to 82%. If W0 is less than 50%, then the model sets

Wj

to

50%.

Using

these

values,

the

model

estimates

latent energy losses and add them to the sensible energy

OPERATIVE TEMPERATURE, *C

Figure 3.13: Standard Effective Temperature and The ASHRAE (1989) Comfort Zones. P 8.14.

108 losses. If

the temperature is more than

68°F, then the model

checks if cooling is needed. If the temperature is less than 75°Fi then no air conditioning is necessary and zero losses occur, and the model processes a new climatic data set.

If

the temperature is more than 75°F, then cooling is needed and the hot air will cause cooling infiltration losses, which are computed similarly to heating losses, but with slight changes pertaining to using the cool air change rate in Table 3.3 and the summer outdoor design temperature of 89°F value (ASHRAE, 1989). Ventilation cooling losses are calculated in the same way as the ventilation heating losses. The model proceeds to accumulate losses,

hourly

infiltration

and

ventilation

cooling

for each building and for both seasons separately,

over the whole year.

CHAPTER IV APPLICATIONS

This chapter presents the results of applications of the simulation methodology developed in chapter

III

and their

analysis.

the

efficient

It

utilization

also of

proposes

climatic

a

strategy

factors

for

towards

achieving

energy

conservation goals, through progressively improving energyconserving site design,

including marginal changes

in the

location of poorly sited buildings.

4.1 Data Inputs 4.1.1 Building Characteristics For the sake of model simplification, we assume that all buildings have vertical walls, and are rectangular in shape. The orientations of the buildings on the site can be in any direction (not only parallel/perpendicular to the Cartesian axes). The buildings tightness varies from 1 to 3. The site area is 200*200 square meters and is characterized by a flat topography.

The

buildings'

dimensions

presented in Appendix A.

109

and

tightness

are

110 4.1.2 Climatoloaical Data Simple descriptive statistics have been computed for the basic meteorological data --- Temperature, Wind Speed, Wind Direction,

and

Global

and Direct Radiations

---

for

each

month and the whole year. The results of this analysis are presented in Tables 4.1 through 4.3. The mean hourly temperature varies over the year between -20 and 32.8 Celsius degrees, with an overall mean of 11.16. The hourly wind speed varies over the year between 0.0 and 14.9 meter per second, with an annual overall mean of 4.47 (Table 4.1). The hourly direct radiation varies over the year between 0.0 and 3303 kj/m2, with a mean of 902, and the hourly global radiation varies between 0.0 and 2999 kj/m2, 983.57

with a mean of

(Table 4.2).

When wind

direction

is specified

according

to

eight

direction sectors and the "calm" condition (no specific wind direction), the combined S/SW/W sectors are characterized by the highest frequency (48.5%) over the year (Table 4.3). The monthly

data

distributed

show

over

that

the

12

this

high

months

of

frequency the

year

is and

fairly is

not

concentrated over any specific period or season.

4.1.3. Alternative Site Designs W e consider a given site,

twenty given structures of

different dimensions, and different possible layouts for

Table 4.1 Monthly and Annual Statistics for Temperature and Wind Speed, for a Typical Meteorological Year for Dayton, Ohio.

Temperature (degrees cels]LUS)

Number Month

Wind speed (meter per second)

of

Observations

Mean

Std. Dev.

Min.

Max.

Mean

Std. Dev.

Min.

Max.

January

744

-1.32

8.13

-20

16.7

5.29

2.41

0.0

12.9

February

672

-0.46

6.30

-19.4

13.9

4.83

1.8

0.0

9.80

March

744

3.00

5.68

-7.80

21.7

5.98

2.60

0.0

14.90

April

720

10.94

6.11

-1.70

27.8

5.04

2.15

0.0

13.40

May

744

16.76

5.78

2.80

30.00

4.14

1.71

0.0

10.30

June

720

21.71

4.70

9.34

32.80

3.98

2.13

0.0

13.90

July

744

22.94

3.68

13.3

32.20

3.49

1.51

0.0

8.80

August

744

23.11

3.73

13.3

31.10

3.21

1.70

0.0

13.40

September

720

18.53

4.27

7.80

28.90

3.55

1.60

0.0

8.80

October

744

13.00

5.57

- 1.1

26.10

4.08

2.10

0.0

11.30

November

720

5.57

6.36

-7.2

24.40

4.56

2.41

0.0

14.40

December

744

-0.64

6.41

-13.9

17.20

5.45

2.05

0.0

12.40

Annual

8760

11.16

10.79

-20.0

32.80

4.47

2.21

0.0

14.90

Table 4.2 Monthly and Annual Statistics for Direct and Global Radiations, for a Typical Meteorological Year for Dayton, Ohio.

D irect Radiation (kilo joule/sguare meter)

Global Radiation (kilo joule/square meter) Min

Max

0.0

2859

January

310

594

491

5.0

1837

680

895

February

332

703

624

0.0

2301

691

972

o • o

Std. Dev.

2936 .

March

390

934

794

o o

Mean

2903

732

943

0.0

2999

April

420

1132

938

3107

845

984

0.0

2972

May

476

1284

1021

0.0

3302

961

1013

0.0

2890

June

480

1341

1056

3303

997

978

0.0

2779

July

486

1290

1024

0.0

3279

970

953

0.0

2815

August

438

1350

968

0.0

3137

1148

966

0.0

2781

September

402

1090

881

2895

958

1037

o • o

Max.

o • o

Min.

o • o

Std. Dev.

o • o

Mean

|



Month

Number of Observations

2818

October

372

915

796

0.0

2495

991

1051

0.0

2851

November

316

607

529

0.0

1892

692

955

0.0

2810

December

310

434

396

0.0

1440

449

783

0.0

2625

Annual

4742

1022

902

0.0

3303

867

984

0.0

2999

Table 4.3 Monthly Wind Direction Frequencies, for a Typical Meteorological Year, for Dayton, Ohio (%).

Wind Direction Month

N

NE

E

SE

S

SW

W

NW

January

11.7

4.4

5.5

7.5

29.7

13.0

20.0

8.1

February

9.70

5.40

13.4

11.3

13.5

17.1

11.3

18.3

March

9.5

8.1

4.3

12.8

13.6

9.5

26.7

15.5

April

9.7

8.8

14.2

13.3

8.8

16.4

11.3

17.6

May

9.7

10.5

12.9

12.8

14.0

16.1

17.6

6.5

June

13.9

6.1

5.0

11.9

21.8

17.9

13.2

10.1

July

14.2

5.8

5.5

9.0

8.7

20.6

21.4

14.8

August

15.6

12.0

14.0

3.8

10.6

19.6

12.1

12.4

September

8.1

5.1

3.3

21.7

22.6

16.5

12.4

10.3

October

19.2

2.2

0.1

5.1

25.0

24.5

10.8

13.2

November

9.2

6.9

3.6

11.8

21.2

12.1

8.8

26.4

December

14.7

11.0

11.3

9.9

21.2

13.4

7.80

10.6

Annual

12.1

7.2

7.7

10.9

17.6

16.4

14.5

13.6

113

114 these structures on that site. All structures are assumed to have

full

exposure

windowless

glass

walls

(except

the

northern wall) . This assumption makes it easier to understand the interaction between climate factors, building locations, and the overall site energy budget. The numerical simulation models developed in Chapter III are applied to these layout designs.

Each

site

design

includes

exactly

the

same

buildings, but their spatial arrangements are different so as to

consider

density

and test

distribution.

contrasted The

site

cases is

of

orientation

overlaid

by

a

and

grid

to

define buildings' locations on the site.

4.2 Design Strategy In order to achieve energy-conserving design goals, we propose the following strategy:



Design a number of different and strongly contrasted layouts reflecting different orientations and buildings arrangements.



Analyze the results of model applications to these designs, and derive site arrangement principles that are likely to achieve the energy conservation goals (e.g., maximum wind protection and energy collection in winter, minimum solar gain in summer, etc.).



Design a new site layout which accounts for the above principles.

115 •

Analyze this new design and, if it improves the energy goals,

keep

it

as

a

good

design

(otherwise,

design

another layout). •

Improve the previous design marginally by moving around poorly located buildings on the site.



Continue testing marginal changes, subject to time and computer resources constraints, and retain the best design.

4.3 Results and Analysis 4.3.1 The Case of Contrasted Designs Site Design 1 The first site is a randomly organized site,

with no

emphasis on energy collection and conservation (Figure 4.1). The high and low-rise buildings are mixed over the site area. The solar and shadowing analysis shows that this site has the second kilo

lowest energy collection in winter

joule = mmkj),

summer (33.578 mmkj)

and the

highest

(63.054 million

energy

(Tables 4.4 and 4.30).

collection

in

The net positive

annual solar energy collection is the second lowest of all sites (29.476 mmkj) the

highest

annual

(Table 4.30) . The wind analysis points to infiltration

and

ventilation

losses

(Table 4.5). Total annual net energy collection at the site due to wind and sun interactions is the lowest of all sites (13.573 mmkj)

(Table 4.30).

116

(15)

IS (6) U

12 (8)

(6)

(18)

(12)

(10 )

10 (15)

(10) 16 (10) 6 (15)

19 (8) (1 5 )

(12) 1 7 (1 3 )

1 do)

(18)

(12)

a: Building Index Number, b: Building Height. Figure 4.1: Plan of Site 1.

Table 4.4

Annual Solar Energy Gains on Site 1 (million k j ) .

Building

Winter Energy Gain

% Winter Solar Access

Summer Energy Gain

% Summer Solar Access

1

2.3093

94.08

1.1637

96.95

2

6.6810

96.14

3.1029

93.78

3

2.5658

67.66

1.276

71.58

4

4.2341

73.21

2.5572

89.47

5

1.4329

56.77

0.72521

58.38

6

3.6776

77.83

2.1473

88.36

7

2.2915

67.83

1.2939

84.52

8

2.6065

68.74

1.4864

83.38

9

1.9269

68.64

0.86758

64.6

10

4.44499

70.74

2.3206

68.77

11

5.8164

76.69

3.1820

89.24

12

3.4362

74.55

2.3715

93.79

13

5.2879

85.1

2.4480

83.6

14

0.79815

47.55

0.56425

63.65

15

0.75190

51.05

0.44881

62.32

16

3.07440

79.94

1.46400

71.77

17

3.58410

87.65

1.77600

80.79

18

4.20430

99.74

1.92180

98.36

19

1.74200

77.70

1.04450

92.58

20

2.18320

78.04

1.4161

95.85

Site

63.0541

33.5778

Table 4.5 Annual Wind Energy Losses on Site 1 (million kj) Winter Energy Lossses

Summer Energy Losses

Building Infilt.

Vent.

Infilt

Vent.

1

1.00560

1.22319

0.04170

0.04910

2

0.06474

1.24674

0.00454

0.04422

3

0.01432

0.44881

0.00022

0.01485

4

0.07533

1.17758

0.0

0.04014

5

0.0

0.35109

0.0

0.01182

6

0.01004

0.67707

0.0

0.02257

7

0.00000

0.21361

0.00063

0.00724

8

0.00923

0.44371

0.00076

0.01525

9

0.01150

0.30137

0.00024

0.01053

10

0.01660

1.21632

0.00034

0.04097

11

0.01460

1.39259

0.00034

0.04656

12

1.00540

1.66245

0.04230

0.06485

13

0.02604

1.14149

0.00198

0.03940

14

0.01525

0.19529

0.00037

0.00650

15

0.01603

0.14657

0.00051

0.00492

16

0.02344

0.70304

0.00175

0.02479

17

0.12216

0.61643

0.00802

0.02489

18

0.02910

0.55081

0.00271

0.02026

19

0.18121

0.44519

0.01256

0.02148

20

0.88649

1.18657

0.04218

0.05240

Site

3.52710

15.33994

0.16394

0.56272

119 The monthly analysis of winter solar energy gain shows the

highest

energy collection

in March

(9.6 mmkj)

(Table

4.6) . The maximum summer energy collection takes place in August (9.15 mmkj). Maximum wind energy losses take place in January (2.903 mmkj)

(Table 4.7).

Site Design 2 In designing this site, an attempt is made to promote solar access,

and consequently solar energy collection, by

increasing the site exposure to sun rays

(Figure 4.2). Tall

buildings are located on the southern edge of the site (which is not the usually recommended approach for maximum energy collection), so as to increase the southern exposure of the site's tall buildings. The low-rise buildings are located on the

northern

part

of

the

site,

with

a

good

separation

distance from the high-rise buildings to promote solar access for all buildings. The solar and shadowing analysis shows a great Design

improvement 1.

This

in

winter

design

energy

offers

the

collection highest

over

winter

Site

energy

collection (64.44 mmkj) (Tables 4.8 and 4.30) . The annual net solar energy collection is the highest (30.882 mmkj)

(Table

4.30).

second

The wind

analysis

for

that

site

shows

the

highest energy losses due to ventilation and infiltration (Table 4.9). Thus, wind protection on this site is next to the worst case (15.544 mmkj).

Promoting solar exposure has

promoted wind exposure. The annual net energy collection of

120

Table 4.6 Monthly Solar Energy Gains on Site l (million kj).

Month

Winter-Type Energy Gain

% Winter Solar Access

January

6.60920

95.59

-



February

7.04920

95.69

-



March

9.60200

95.85

-



April

9.26470

95.93

0.92039

81.28

May

7.14000

95.89

3.75310

83.70

June

2.13240

95.95

6.75280

85.08

July

0.98763

95.40

8.83400

86.59

August

0.61489

94.94

9.15340

83.99

September

3.44190

95.85

2.87260

77.97

October

6.32720

95.60

1.17980

66.88

November

5.82360

95.62

0.11161

64.51

December

4.60120

95.68

Summer-Type Energy Gain

-

% Summer Solar Access

-

121

Ta b l e 4.7 Monthly Wind Energy Losses on Site 1 (million kj)

Winter-Type Energy Losses

Summer-Type Energy Losses

Months Infilt.

Vent.

Infilt.

Vent.

January

0.8191

2.90278

0.0

0.0

February

0.3957

2.34540

0.0

0.0

March

0.90813

2.60480

0.0

0.0

April

0.29306

1.24505

0.01170

0.01608

May

0.08562

0.51969

0.00869

0.40828

June

0.03275

0.15187

0.00623

0.15954

July

0.00439

0.54000

0.02988

0.14222

August

0.02071

0.04530

0.03898

0.16574

September

0.02974

0.26867

0.11457

0.03291

October

0.18136

0.89710

0.00090

0.00502

November

0.30731

1.74270

0.0

0.00040

December

0.46781

2.56260

0.0

0.0

122

(10)

17

18 (10)

10

14

15 W

(10)

10

18 (»)

(10)

(13)

(15)

(18)

(18)

a: Building Index Number, b: Building Height. Figure 4.2: Plan of Site 2.

(12)

(15)

123

Table 4.8

Annual Solar Energy Gains on Site 2 (million k j ) .

Bulding

Winter Energy Gain

% Winter Solar Access

Summer Energy Gain

% Summer Solar Access

1

7.24970

95.59

3.49900

98.14

2

6.45320

92.87

2.77340

83.82

3

5.84170

92.43

2.45100

82.49

4

5.41950

93.82

2.40850

81.40

5

3.30900

69.92

2.19070

94.05

6

3.53750

61.09

2.05570

74.56

7

3.10970

65.61

1.75720

78.86

8

2.65120

62.9

1.47900

75.70

9

2.85820

75.72

1.93950

95.79

10

1.61380

57.49

0.96535

71.88

11

1.30190

58.07

0.83345

73.88

12

1.22160

83.11

0.71208

93.63

13

3.14130

83.22

1.97070

97.33

14

2.91000

75.66

1.46650

71.89

15

1.47970

88.15

0.86758

97.87

16

2.35550

84.20

1.45030

98.16

17

2.16810

77.10

1.0086

79.06

18

2.04930

83.49

1.01980

84.96

19

3.26480

89.47

1.49850

85.50

20

2.50230

89.29

1.20880

85.72

Total

64.43800

33.55566

124

Table 4.9 Annual Wind Energy Losses on Site 2 (million kj)

Winter Energy Losses

Summer Energy Losses

Building Infilt.

Vent.

Infilt.

Vent.

1

0.37262

1.75059

0.01934

0.06556

2

0.03223

1.21422

0.002713

0.04239

3

0.12891

1.27725

0.010675

0.04919

4

0.0506

1.16399

0.00509

0.04261

5

0.67882

1.33713

0.03157

0.05374

6

0.00831

0.99330

0.00011

0.03317

7

0.00388

0.5470

0.00033

0.01861

8

0.00426

0.52599

0.00114

0.01869

9

0.35091

0.80717

0.02339

0.03896

10

0.00374

0.29357

0.00003

0.0098

11

0.0

0.26399

0.0

0.0089

12

0.02444

0.15752

0.00269

0.0072

13

0.49153

0.94778

0.02299

0.03856

14

0.04382

0.72343

0.00123

0.02425

15

0.03896

0.21900

0.00271

0.008842

16

0.61460

0.91468

0.0266

0.03682

17

0.0155

0.19354

0.00066

0.00669

18

0.0756

0.29319

0.00126

0.00862

19

0.05058

0.87129

0.00083

0.02835

20

0.01945

0.49089

0.00131

0.01719

3.0089

14.98549

0.15467

0.55820

Site

125 the

site

due to

sun

highest (15.338 mmkj)

and wind

interactions

is the

second

(Table 4.30).

The monthly solar results indicate maximum winter energy collection in March (9.8 mmkj), and maximum summer collection in August (9.23 mmkj)

(Table 4.10). The monthly wind results

indicate maximum energy losses in January (2.82 mmkj)

(Table

4.11).

Site Design 3 The organization of this site is centralized, with the tallest buildings in the center of the site, and the lowest on

the

southern

part

(Figure

4.3).

The

medium-heights

buildings are located on the eastern and western sides of the site. The solar and shadowing analysis points to the second highest energy collection for winter

(63.98 mmkj),

(Tables

4.12 and 4.30). The annual energy collection for both seasons is the second highest (30.623 million kj). The wind analysis shows

that

losses,

this

site

has

the

second

lowest

wind

energy

with nearly the same value as site 1 (15.526 mmkj)

(Tables 4.13 and 4.30). The annual overall net energy gain of this site is the second lowest, with a value of 15.097 mmkj (Table 4.30). The monthly solar results indicate maximum winter energy collection

in

March

(9.77

mmkj),

collection in August (9.12 million kj)

and

maximum

summer

(Table 4.14). The

126

Table 4.10 Monthly Solar Energy Gains on Site 2 (million kj)

Month

Winter-Type Energy Gain

% Winter Solar Access

Summer-Type Energy Gain

% Summer Solar Access

January

6.30010

95.55

-

-

February

7.27270

95.70

-

-

March

9.81460

95.95

-

-

April

9.36860

96.09

0.92620

83.50

May

7.10660

96.09

3.71600

84.95

June

2.11270

96.14

6.64150

85.95

July

0.98247

95.77

8.7098

87.49

August

0.619360

95.48

9.23120

86.37

September

3.52170

95.98

2.95770

81.43

October

6.54510

95.67

1.25450

72.19

November

6.04830

95.58

0.11833

69.00

December

4.74550

95.62

-

-

127

Table 4.11 Monthly Wind Ener g y Losses on site 2 (million kj)

Winter-Type Energy Losses

Summer-Type Energy Losses

Months Infilt.

Vent.

Infilt.

Vent.

January

0.70260

2.81975

0.0

0.0

February

0.35002

2.33000

0.0

0.0

March

0.82986

2.55760

0.0

0.0

April

0.20764

1.17337

0.00899

0.01348

May

0.08077

0.52276

0.00802

0.04026

June

0.02915

0.14944

0.05603

0.15461

July

0.00379

0.05425

0.02928

0.14339

August

0.00141

0.04547

0.04117

0.16962

September

0.02196

0.26506

0.01029

0.03155

October

0.15451

0.8697

0.00089

0.00495

November

0.02534

1.70397

0.0

0.000349

December

0.37380

2.49420

0.0

0.0

128

(12)

19

(1 5 )

(1 8 ) 16 (18)

(10)

13

14

(12)

11

(10)

15

(1 5 )

(1 5 )

1 0 (10)

20

(10) (12)

a: Building Index Number, b: Building Height. Figure 4.3: Plan of Site 3.

7

(13)

129

Table 4.12

Annual Solar Energy Gains on Site 3. (million k j ) .

Building

Winter Energy Gain

% Winter Solar Access

Summer Energy Gain

% Summer Solar Access

1

1.64350

97.57

0.80291

99.64

2

1.37230

93.18

0.65192

90.52

3

2.03930

90.96

1.02890

91.20

4

2.99370

96.81

1.26940

89.60

5

2.34050

92.72

1.07740

86.73

6

2.44400

87.36

1.44050

97.50

7

3.51550

86.46

1.68450

87.22

8

4.79210

82.75

2.36810

85.89

9

4.64230

80.73

2.33880

79.04

10

2.95880

76.93

1.28180

62.84

11

2.10250

75.28

1.46050

94.55

12

3.56750

75.38

2.62700

87.02

13

3.38150

80.67

1.96570

86.34

14

1.91230

78.06

1.21880

96.15

15

4.59540

73.05

2.91940

86.51

16

5.78980

83.32

2.91190

88.01

17

3.08280

81.67

1.58120

78.09

18

5.63500

85.66

2.21620

93.07

19

2.02720

72.46

1.37520

93.08

20

3.10580

81.90

1.73450

97.29

Site

63.97780

33.355463

130

Table 4.13 Annual Wind Energy Losses on Site 3 (million kj)

Winter Energy Lossses

Summer Energy Losses

Building Infilt.

Vent.

Infilt.

Vent.

1

0.3022

0.47608

0.01178

0.01765

2

0.01765

0.14820

0.00196

0.00637

3

0.02094

0.28493

0.00345

0.01236

4

0.13695

0.54258

0.00990

0.02353

5

0.02601

0.37710

0.00294

0.01477

6

0.54393

0.84401

0.02513

0.03536

7

0.03085

0.50155

0.00051

0.01636

8

0.00130

0.98629

0.0

0.03307

9

0.00465

1.11804

0.00032

0.03783

10

0.01783

0.69744

0.00129

0.02432

11

0.25492

0.45525

0.01687

0.02388

12

0.03687

0.69518

0.00066

0.02283

13

0.00641

0.26267

0.00165

0.02070

14

0.55968

0.78146

0.00306

0.03814

15

0.30946

1,50920

0.00801

0.04875

16

0.00283

1.18483

0.0

0.03968

17

0.0809

0.53713

0.00336

0.01893

18

0.11172

2.20542

0.01059

0.09703

19

0.23079

0.53087

0.00931

0.01953

20

0.08423

0.51872

0.00348

0.01810

Site

2.78012

14.95695

0.14181

0.56919

131

Table 4.14 Monthly Solar Energy Gains on Site 3 (million kj) Summer-Type Energy Gain

Month

Winter-Type Energy Gain

% Winter Solar Access

January

6.28390

93.75

-



February

7.24870

94.07

-



March

9.76880

94.61

-

-

April

9.25000

94.94

0.91111

85.12

May

7.06030

95.15

3.69790

87.18

June

2.12490

95.15

6.62790

88.34

July

0.961210

94.97

8.73530

89.59

August

0.59711

94.69

9.12210

87.75

September

3.47390

94.66

2.90620

83.61

October

6.46600

94.06

1.23990

75.23

November

5.98850

93.71

0.11437

71.42

December

4.75410

93.87

-

-

% Summer Solar Access

132 monthly

wind

results

indicate

January (2.94 million kj)

maximum

energy

losses

in

(Table 4.15)

Site Design 4 The tall buildings are located in the north, and the low buildings in the south of the site (Figure 4.4). This site arrangement is the usually recommended one for maximum solar energy collection. The winter solar energy collection (61.64 mmkj) and the annual net solar energy collection (29.19 mmkj) are the

lowest

of all

sites

(Tables 4.16

and

4.30).

The

annual wind results point to the lowest energy losses due to infiltration

(1.49

mmkj)

and

ventilation

(

13.49

mmkj)

(Tables 4.17 and 4.30). The total net energy gain for this site,

considering the interactions of sun and wind effects

over the whole year, mmkj)

is the highest of all 4 sites

(15.704

(Table 4.30). The monthly solar results indicate maximum winter energy

collection in March

(9.38 mmkj),

collection in August

(8.7 mmkj)

and maximum summer energy (Table 4.18).

The monthly

wind results indicate maximum energy losses in January (2.37 mmkj) thus

(Table 4.19). minimal

ventilation.

energy Given

Site 4 offers maximal wind protection, losses the

due

selected

to

wind

climatic

infiltration

and

conditions,

the

energy losses due to the wind represent, on average, one half of the solar energy gains.

133

Table 4.15 Monthly Wind Energy Losses on Site 3 (million kj)

Winter-Type Energy Losses

Summer-Type Energy Losses

Months Infilt.

Vent.

Infilt.

Vent.

January

0.61320

2.9388

0.0

0.0

February

0.35717

2.29493

0.0

0.0

Ma r c h

0.75770

2.4688

0.0

0.0

April

0.19935

1.15491

0.008916

0.01409

May

0.07812

0.54025

0.007626

0.03978

Jun e

0.03150

0.15488

0.05195

0.15918

July

0.00278

0.05027

0.02377

0.13921

August

0.00137

0.04069

0.03890

0.17700

September

0.02000

0.26577

0.00968

0.03430

October

0.13480

0.89644

0.00093

0.00530

November

0.20575

1.62740

0.00001

0.0

December

0.37833

2.52390

0.0

0.0

V

134

N 20

i

(12)

19 (10)

18

(18)

17(13)

14(10)

15 (15) 16

(18) 13(13)

12 (15)

11

(10)

10 (10) 7

• (10)

(1 3 ).

8

(15)

9

(15)

5 3

(8 )

a: Building Index Number, b: Building Height. Figure 4.4: Plan of Site 4.

CO

to

#—N

w

(8)b

CM

l"

(8 )

135

Table 4.16 Annual Solar Energy Gains on Site 4 (million kj).

Building

Winter Energy Gain

% Winter Solar Access

Summer Energy Gain

% Summer Solar Access

1

2.09480

93.43

1.10750

98.17

2

3.00720

97.25

2.27160

89.76

3

0.95354

64.74

0.56350

78.24

4

1.20520

71.80

0.60308

68.03

5

2.12430

84.29

1.27320

98.23

6

3.15555

83.60

1.77110

87.47

7

4.15640

91.40

1.81170

76.16

8

4.63360

80.22

2.42560

81.98

9

1.4394

58.64

0.74582

62.14

10

2.09750

74.72

1.13810

84.75

11

2.60590

92.83

1.32890

98.96

12

3.57520

92.61

1.79210

97.50

13

3.06420

80.81

1.51830

85.17

14

4.31130

74.45

2.2477

81.52

15

3.24380

68.54

1.62380

69.71

16

5.47650

79.11

2. 65470

72.30

17

4.86810

64.19

2.64730

74.25

18

4.16810

65.95

2.48510

83.64

19

3.14450

74.60

1.86470

95.44

20

2.32600

95.46

1.18370

99.07

Site

61.64326

32.05750

136

Table 4.17 Annual Wind Energy Losses o n Site 4 (million kj) Winter Energy Losses

Summer Energy Losses

Building Infilt.

Vent.

Infilt.

Vent.

1

0.12837

0.3924

0.00934

0.01825

2

0.12453

0.5301

0.00923

0.02286

3

0.00195

0.1325

0.00002

0.00443

4

0.00666

0.1867

0.00007

0.00620

5

0.12394

0.4797

0.00761

0.01963

6

0.13838

0.5946

0.00544

0.02101

7

0.08917

0.8188

0.00659

0.03128

8

0.00363

1.11702

0.00042

0.03793

9

0.00035

0.21793

0.00006

0.00742

10

0.00011

0.29090

0.0

0.00978

11

0.07419

0.36402

0.00208

0.01185

12

0.49633

1.15300

0.02431

0.04636

13

0.00419

0.43868

0.00005

0.01468

14

0.0

0.98499

0.0

0.03307

15

0.0

0.65832

0.0

0.02217

16

0.0315

1.25483

0.00126

0.04272

17

0.00071

1.37871

0.00011

0.04623

18

0.06537

1.21370

0.00103

0.03954

19

0.10145

0.62319

0.00536

0.02292

20

0.03202

0.19522

0.00064

0.00626

Site

1.423859

13.02529

0.07351

0.46459

137

Table 4.18 Monthly Solar Energy Gains on Site 4 (million kj)

Month

Winter-Type Energy Gain

% Winter Solar Access

Summer-Type Energy Gain

January

6.16590

95.51



_

February

7.03830

95.78





March

9.38580

96.23





April

8.84320

96.65

0.88197



May

6.70190

97.00

3.54820

82.43

June

1.97720

97.44

6.34510

83.57

July

0.88681

97.63

8.37410

85.56

August

0.54169

97.88

8.74120

83.12

September

3.28620

96.67

2.83350

79.08

October

6.25060

95.89

1.21870

71.07

November

5.90360

95.52

0.11485

67.90

December

4.66970

95.64

-

% Summer Solar Access

-

138

Table 4.19 Monthly Wind Energy Losses on Site 4 (million kj)

Winter-Type Energy Losses

Summer-Type Energy Losses

Months Infilt.

Vent.

Infilt.

Vent.

J anuary

0.31827

2.36630

0.0

0.0

February

0.15413

2.07130

0.0

0.0

March

0.43189

1.21023

0.0

0.0

April

0.10231

1.03939

0.00378

0.00774

May

0.04595

0.47330

0.00450

0.03570

June

0.01153

0.12819

0.02763

0.12318

July

0.00109

0.04985

0.01668

0.12725

August

0.00037

0.04300

0.01724

0.14168

September

0.00837

0.24385

0.00362

0.02430

October

0.05336

0.74809

0.00046

0.00440

November

0.11770

1.52500

0.0

0.00034

December

0.17950

2.23390

0.0

0.0

139 4.3.2 Improved Site Design 5 In an attempt to improve over the previous best site design,

we propose

a new site 5

(Figure 4.5).

To promote

solar access, site's 2 arrangement of tall buildings in the south,

resulting

in

maximum

solar

energy

collection,

is

adopted. To promote wind protection, site's 4 arrangement of minimum western exposure to wind, resulting in minimum wind energy losses,

is also adopted in this arrangement.

Thus,

tall buildings were placed on the southern part of the site to maximize solar collection,

with minimum exposure to the

west to maximize wind protection. The results of the simulation analysis show that this design is characterized by an important increase in winter solar energy gain (66.16 mmkj)

(Table 4.20). Meanwhile, the

wind results do not show any decrease in wind energy losses (Table 4.21), which may be explained by an increase in wind losses due

to an

increased

southern

exposure

affected

by

strong southern winds. However, the net annual energy gain of site 5 displays a significant increase over previous designs, to a value of 18.084 mmkj (Table 4.30). While this site does not achieve the lowest wind energy losses,

it achieves the

best overall energy budget so far.

4.3.3 Marginal Analysis Marginal

improvements

of

site

5

are

attempted

by

modifying the location of some poorly sited buildings, which

140

17

16 (6)

10 .(8 )

20

(15)

14

15 (8)

111

(13)

(1 0 )

(10) (12)

(12) 4(10)

il81

(18)

a: Building Index Number, bs Building Height. Figure 4.5: Plan of Site 5.

(15)

141

Table 4.20

Annual Solar Energy Gains on Site 5 (million K j ) .

Building

Winter Energy Gain

% Winter Solar Access

Summer Energy Gain

% Summer Solar Access

1

7.32660

96.61

3.52080

98.75

2

6.58040

94.70

2.86870

68.70

3

6.15290

97.36

2.56820

86.44

4

1.85830

75.71

1.12230

93.50

5

2.56220

67.57

1.63400

91.66

6

2.95170

70.00

1.65130

84.52

7

3.11980

82.27

1.54480

83.65

8

2.65380

72.95

1.53410

88.67

9

1.06210

63.05

0.74245

92.14

10

1.87070

83.44

1.11100

98.39

11

2.06610

73.47

1.16670

91.46

12

1.94970

69.45

1.12160

83.52

13

2.44180

86.98

1.21710

90.63

14

2,23480

72.27

1.31670

92.94

15

1.88830

74.81

1.13940

91.72

16

1.15950

78.73

0.70545

97.95

17

5.30210

91.56

2.71390

98.43

18

4.96140

85.78

2.45660

85.95

19

4.43070

84.32

2.09160

79.11

20

3.58600

87.30

1.48760

77.00

Site

66.15890

33.71430

142

Table 4.21 Annual W i n d Energy Losses on Site 5 (million kj)

Winter Energy Losses

Summer Energy Losses

Building Infilt.

Vent.

Infilt.

Vent.

1

0.3151

1.69310

0.15803

0.062022

2

0.04140

1.2234

0.00604

0.04572

3

0.11791

1.26624

0.00867

0.047186

4

1.15795

1.37551

0.045735

0.05309

5

0.058930

0.49342

0.00109

0.01572

6

0.00153

0.52327

0.0

0.01755

7

0.024355

0.45885

0.00357

0.01819

8

0.00968

0.62165

0.00083

0.02081

9

0.04869

0.22258

0.002144

0.00800

10

0.17075

0.43473

0.01165

0.0206

11

0.008281

0.18628

0.00008

0.006111

12

0.00015

0.28998

0.0

0.00977

13

0.10890

0.39873

0.00624

0.016016

14

0.00018

0.40580

0.0

0.01363

15

0.01004

0.36114

0.00022

0.01204

16

0.23155

0.36209

0.00969

0.01410

17

0.1635

1.1485

0.00823

0.04130

18

0.01304

1.1153

0.00056

0.03759

19

0.07810

0.96206

0.00097

0.03073

20

0.10651

0.57721

0.00436

0.02021

Site

2.66657

14.11979

0.12588

0.51037

143 are

identified

by

considering

energy gains and losses.

each

individual

building's

For instance, the analysis of the

annual solar energy gains on site 5 (Table 4.20) that

building

buildings

No. 9

(63.05%

has

of

the

lowest

available

improvement in its solar access,

solar

winter

indicates

access

energy).

of

Then,

all an

if possible, may increase

the solar energy collection of site 5. First, analyzing site 5 layout, we found it possible to marginally move building No. 4 by rotating it in by 90 degrees to reduce its southern front, which blocks building No.9 solar access. This change produced a new site layout 6 (Figure 4.6). Analyzing site 6, we found that we achieved an increase in winter energy gain, but, at the same time, we increased the summer energy gain, leading to an overall decrease in the net

annual

solar

energy

gain

for

the

site

(32.435

mmkj)

(Table 4.22). Wind energy losses for this site are reduced (14.501 mmkj)

(Table 4.23), but the total annual energy gain

of the site is decreased this

marginal

site

(17.934 mmkj)

change

was

not

(Table 4.30). Thus, successful,

and

was

discarded. Next,

in another attempt to

proposed

to

move

possibly

improve

building building

No. 14 19

improve solar access, to

solar

movement produced site design 7

the

right

access.

This

(Figure 4.7).

so

to

marginal

The results

show no improvement in solar energy gain (32.434 mmkj) 4.24) or in wind protection ( 14.50 mmkj)

as

we

(Table

(Tables 4.25). The

144

17

20

(15)

15

10

(a)

(8)

ii

14

\ (B)

g°)

(13)

13 (1°)

(10)

(12)

(18)

(18)

a: Building Index Number, b: Building Height. Figure 4.6: Plan of Site 6.

(15)

145

Table 4.22

Annual Solar Energy Gains on Site 6 (million k j ) .

Building

Winter Energy Gain

% Winter Solar Access

Summer Energy Gain

% Summer Solar Access

1

7.32330

96.56

3.51980

98.72

2

6.58040

94.70

2.86870

86.70

3

6.15290

97.96

2.56820

86.44

4

1.91440

78.14

1.20450

95.02

5

2.57030

67.78

1.62340

91.06

6

2.95230

70.04

1.65220

84.56

7

3.11960

82.27

1.54490

86.66

8

2.65370

72.95

1.53410

88.76

9

1.03800

61.63

0.72445

89.48

10

1.87150

83.47

1.11120

98.49

11

2.06550

73.45

1.16670

91.45

12

1.94870

69.42

1.12110

83.48

13

2.44180

86.98

1.21710

90.62

14

2.23480

72.27

1.31670

92.94

15

1.88800

74.80

1.13940

91.72

16

1.16410

79.04

0.70652

98.10

17

5.30210

91.56

2.71390

98.43

18

4.96140

85.78

2.45660

85.95

19

4.43070

84.32

2.09160

79.11

20

3.58600

87.30

1.48760

77.02

Site

66.19950

33.76547

146

Table 4.23 Annual wind Energy Losses on Site 6 (million kj).

W i nter Energy Losses

Summer Energy Losses

Building Infilt.

Vent.

Infilt.

Vent.

1

0.31846

1.69643

0.1653

0.06275

2

0.04040

1.2224

0.00604

0.04572

3

0.11625

1.26458

0.00885

0.04737

4

1.04130

1.26308

0.04699

0.05453

5

0.04729

0.48178

0.00093

0.01556

6

0.00075

0.52249

0.0

0.01755

7

0.02412

0.45862

0.00364

0.01826

8

0.01040

0.62237

0.00083

0.02080

9

0.04573

0.21962

0.00153

0.00739

10

0.16504

0.42903

0.01128

0.02020

11

0.00777

0.18577

0.00009

0.00612

12

0.00008

0.28991

0.0

0.0977

13

0.1081

0.39792

0.00610

0.01588

14

0.00014

0.40576

0.0

0.01363

15

0.00912

0.36022

0.00026

0.01208

16

0.22659

0.35714

0.00962

0.01403

17

0.16747

1.15246

0.00788

0.04095

18

0.01666

1.11891

0.00062

0.03766

19

0.07829

0.96224

0.00099

0.03072

20

0.1085

0.57916

0.00445

0.02030

Site

2.5324

13.98985

0.12662

0.51130

147

17

20

(15)

18

(13)

19 (15)

(15) N

! 16 (6)

15

10 (5 ) 9

t

(8)

11

li

(1°)

'

' 'V' 4*1 (8) .11

12 (10)

8

13 (10)

(10)

(6) 5

(12)

6

(12)

7

(12)

4 (10)

118)

(18)

a: Building Index Number, b: Building Height. Figure 4.7: Plan of Site 7.

(15)

148

Table 4.24 Annual Solar Energy Gains on Site 7 (million k j ) .

Building

Winter Energy Gain

% Winter Solar Access

Summer Energy Gain

% Summer Solar Access

1

7.32330

96.56

3.51980

98.72

2

6.58040

94.70

2.86870

86.70

3

6.15290

97.36

2.56820

86.44

4

1.91440

78.14

1.20450

95.02

5

2.57030

67.78

1.62340

91.06

6

2.95230

70.04

1.65220

84.56

7

3.11960

82.27

1.54490

86.66

8

2.65370

72.95

1.53410

88.76

9

1.03800

61.63

0.72045

89.41

10

1.87150

83.47

1.11120

98.49

11

2.06550

73.45

1.16670

91.45

12

1.94870

69.42

1.12110

83.08

13

2.43170

86.62

1.18870

88.52

14

2.19790

71.08

1.31820

93.04

15

1.89070

74.90

1.13950

91.72

16

1.16400

79.04

0.70652

98.10

17

5.30260

91.57

2.71390

98.43

18

4.98290

86.16

2.45670

85.96

19

4.44080

84.52

2.09440

79.21

20

3.57380

87.00

1.48760

77.00

Site

66.17510

33.74155

149

Table 4.25 Annual Wind Energy Losses on Site 7 (million k j ) .

Winter Energy Losses

Summer Energy Losses

Building Infilt.

Vent.

Infilt.

Vent.

1

0.32883

1.7068

0.001773

0.063953

2

0.03958

1.2216

0.00592

0.045595

3

0.11993

1.26826

0.009084

0.047600

4

1.10499

1.26276

0.04669

0.05423

5

0.04835

0.48284

0.00096

0.01559

6

0.00075

0.52249

0.0

0.01755

7

0.02185

0.45634

0.00363

0.01826

8

0.00722

0.61919

0.0

0.02078

9

0.04559

0.21949

0.00154

0.0074

10

0.16496

0.42894

0.01126

0.02017

11

0.00785

0.18585

0.0

0.00612

12

0.0

0.28990

0.0

0.00977

13

0.10054

0.39037

0.00613

0.01591

14

0.0

0.40566

0.0

0.01363

15

0.00920

0.36029

0.0003

0.01208

16

0.22531

0.35585

0.00951

0.01393

17

0.16526

1.1503

0.00767

0.04073

18

0.01674

1.119

0.00062

0.03766

19

0.07548

0.95944

0.00096

0.03073

20

0.1098

0.58051

0.00454

0.02039

2.52837

13.98578

0.12741

0.5121

Site

150 net annual overall energy gain of this site is very close to that of site 6, thus pointing to a failure in improving over site 5. A

third

marginal

change

involved

promoting

wind

protection on the western side of site 5, by moving building No.4 to the south, to join buildings 1,2 and 3 in one row, producing site design 8 (Figure 4.8). Analyzing the results for site 8 indicates an increase in winter energy collection (66.494 mmkj), thus

and a decrease in summer energy collection,

increasing significantly the net annual

gain of the site (33.025 mmkj) indicate

a

(14.264 mmkj)

significant

solar energy

(Table 4.26) . The wind results

reduction

in

wind

energy

losses

(Table 4.27). The total net energy gain of site

8 is 18.762 million kj

(Table 4.30), an increase of

0.680

mmkj over the energy collection of site 5. In a final attempt in further marginal improvement, we considered increasing site 8 wind protection, by marginally moving

building

No.

9

to

the

south,

joining

in

a

row

buildings 5, 6 and 7, thus producing site design 9 (Figure 4.9) . The results indicate increase in the net annual solar energy gain (3 3.08 mmkj) 4.28),

over all the previous sites (Table

and a decrease in wind energy losses over all sites

(Table 4.29) but site 4 (Table 4.30). The total energy gain of site 9 is 18.917 mmkj, representing an increase of a 0.16 mmkj over site 8 energy budget.

151

20

i & M

10 (8)

15

(8)

11

(13)

14

(» )

(10)

(12) 4(10)

(18) a: Building Index Number, b: Building Height. Figure 4.8: Plan of Site 8.

(15) ,J

152

Table 4.26 Annual Solar Energy Gains on Site 8 (million kj).

Building

Winter Energy Gain

% Winter Solar Access

Summer Energy Gain

% Summer Solar Access

1

7.09340

93.53

3.18840

89.43

2

6.58130

94.71

2.86880

86.70

3

6.15580

97.40

2.56800

86.40

4

2.21210

90.12

1.13690

94.72

5

2.65260

69.95

1.69610

95.14

6

2.93820

69.70

1.66270

85.10

7

3.04160

80.21

1.54270

86.54

8

2.64650

72.75

1.53400

88.75

9

1.25770

74.67

0.76788

95.30

10

1.88360

84.01

1.11010

98.40

11

2.08800

74.25

1.16680

91.46

12

1.96100

69.86

1.12220

83.56

13

2.43260

86.65

1.18870

88.52

14

2.19730

71.06

1.31820

93.04

15

1.89250

74.98

1.13950

91.72

16

1.1597

78.75

0.70545

97.95

17

5.30260

91.57

2.71390

98.43

18

4.98290

86.16

2.45670

89.96

19

4.44080

84.52

2.09440

79.21

20

3.57380

87.00

1.48760

77.02

Site

66.49400

33.46903

153

Table 4.27 Annual Wind Energy Losses on Site 8 (million kj). Winter Energy Losses

Summer Energy Losses

Building Infilt.

Vent.

Infilt.

Vent.

1

0.14924

1.52724

0.00871

0.05493

2

0.04768

1.22967

0.00467

0.04435

3

0.13810

1.26642

0.00968

0.04820

4

0.89204

1.10961

0.04519

0.04895

5

0.83967

0.51846

0.00242

0.01705

6

0.00167

0.52342

0.0

0.01755

7

0.01845

0.45294

0.00313

0.01776

8

0.00402

0.61598

0.00062

0.02059

9

.07577

0.24967

0.00355

0.00942

10

0.17281

0.43679

0.01223

0.02114

11

0.00857

0.18658

0.0

0.00613

12

.00014

0.28996

0.0

0.00977

13

0.10265

0.39348

0.00617

0.01594

14

0.00018

0.40580

0.0

0.01364

15

0.00887

0.35996

0.00025

0.01207

16

0.22252

0.35307

0.00963

0.01404

17

0.15247

1.13746

0.00800

0.04107

18

0.01554

1.11779

0.00070

0.03774

19

0.08752

0.97148

0.00102

0.03078

20

0.11237

0.58307

0.00460

0.02045

Site

2.29455

13.74779

0.11708

0.51568

154

20

13 (1Q)

15 (8)

10 (S)

(13)

111. . .(121

(10) (12)

4 (10) 1

-1

(18)

(18)

a: Building Index Number, b: Building Height. a: Building Index Number, b: Building Height.

Figure 4.9: Plan of Site 9.

(15) —

J

155

Table 4.28 Annual Solar Energy Gains on Site 9 (million k j ) .

Building

Winter Energy Gain

% Winter Solar Access

1

7.0934

93.53

3.1884

89.43

2

6.5813

74.71

2.8688

86.70

3

6.1558

97.50

2.5680

86.43

4

2.2121

90.12

1.1369

94.72

5

2.6093

68.81

1.6257

91.19

6

2.9382

69.70

1.6627

85.10

7

3.0416

80.21

1.5427

86.54

8

2.6473

72.77

1.5345

88.78

9

1.2050

71.54

0.77302

95.93

10

1.9382

86.45

1.1200

99.28

11

2.1481

76.39

1.1834

92.77

12

1.9632

69.93

1.1262

83.86

13

2.4326

86.65

1.1887

88.52

14

2.1973

71.06

1.3182

93.04

15

1.8952

75.08

1.1395

91.72

16

1.1598

78.75

0.70545

97.95

17

5.3026

91.57

2.7139

98.43

18

4.9829

86.16

2.4567

85.96

19

4.4408

84.52

2.0944

79.21

20

3.5738

87.00

1.4876

77.02

Site

66.5185

Summer Energy Gain

33.43477

% Summer Solar Access

156

T a b l e 4.29 Annual Wind Energy Losses on Site 9 (million kj)

Winter Energy Losses

Summer Energy Losses

Building Infilt.

Vent.

Infilt.

Vent.

1

0.13589

1.51389

0.00833

0.05455

2

0.04711

1.2291

0.00465

0.04433

3

0.13899

1.287324

0.00983

0.04835

4

0.86427

1.08184

0.04086

0.04822

5

0.04089

0.47539

0.00078

0.01541

6

0.000827

0.52257

0.0

0.01755

7

0.02077

0.45527

0.00344

0.01806

8

0.00412

0.61609

0.00061

0.02058

9

0.06379

0.23768

0.00359

0.009458

10

0.19964

0.46362

0.01341

0.02233

11

0.00586

0.1839

0.00011

0.00614

12

0.00009

0.29073

0.0

0.00977

13

0.10104

0.39087

0.00609

0.01587

14

0.0001

0.40580

0.0

0.01364

15

0.00823

0.35932

0.00023

0.01205

16

0.21328

0.34382

0.00987

0.01428

17

0.15333

1.13833

0.00710

0.04017

18

0.02640

1.1229

0.00077

0.03781

19

0.08261

0.96657

0.00101

0.03078

20

0.11175

0.58205

0.00442

0.02027

Site

2.21414

13.66739

0.11510

0.49959

157

Table 4.30 Summary of Annual Site Energy Gains (million kj)

Solar Effect Winter Energy Gain

Summer Energy Loss

Site Energy Gain

Site Wind Energy Loss Vent.

1

63.05405

33.578

29.476

15.903

13.573

2

64.438

33.556

30.882

15.544

15.338

3

63.978

33.355

30.623

15.526

15.097

4

61.643

32.058

29.194

13.490

15.704

5

66.159

33.714

32.714

14.630

18.084

6

66.200

33.766

32.435

14.501

17.934

7

66.175

33.742

32.434

14.498

17.936

8

66.494

33.469

33.025

14.264

18.762

9

66.519

33.435

33.084

14.167

18.917

Site

Site Net Energy Gain

158 4.3.4 Summary This chapter has presented an example of the modeling methodology application to design a hypothetical site with 20 buildings that can be

located anywhere

in the

site.

Four

strongly contrasted site designs were initially developed and analyzed,

so as to derive planning principles

for further

designs. The analysis of these four contrasted designs points out a maximum annual solar energy gain for site design 2 and minimum annual wind infiltration and ventilation losses for site design 4. Using the solar access design criterion of site

design

2

and

the

wind

protection

criterion

of

site

design 4, we next developed site design 5. The analysis of site design 5 points out a net annual energy gain of 18.084 mmkj the

(Table 4.30) thus an increase of 4.5 mmkj, or 33%, over randomly

organized

site

design

1.

In

an

attempt

to

marginally improve the solar energy gain of site design 5, we have analyzed the percentage of winter solar access for each building, located

and tried to improve the solar access of poorly buildings.

Two

attempts

of

solar

energy

gain

improvement through site designs 6 and 7 failed to increase the annual energy gain.

Another two trials to improve the

wind protection of site design

5 were

successful

analysis of the final site design 9 points out energy gain of 18.917 mmkj (Table 4.30), thus

and the

a net annual an increase of

5.344 mmkj, or 40%, over site design 1. Thus, the incremental improvement

approach

used

here

has

enabled

us

to

significantly

improve the

site's

net

annual

energy gain.

Moreover, this improvement has involved both an increase in the net annual solar gain( 29.47 mmkj for site l to 33.08 mmkj for site 9) and a decrease in wind-related energy losses (15.90 mmkj

for

site l to

14.17

mmkj

for

site

9).

Thus,

contrary to the widespread belief that there are unavailable trade-offs

between

solar

gain

and

wind

protection,

this

analysis has demonstrated that it is possible to win on both fronts through judicious locational arrangement on the site.

CHAPTER V CONCLUSIONS AND RECOMMENDATIONS

5.1 Conclusions

The methodology presented in chapter III constitutes a new

contribution

planning

and

to

the

climatic

process

design.

of

Until

energy now,

conservation

there

were

no

comprehensive models quantifying the effects of climate to help

in

site planning.

All

previous

related

quantitative

models were only concerned with the thermal comfort of one building and the effect of the surrounding environment on it. The interactions between buildings' siting on the site were ignored because of the absence of a quantitative measure of these

interactions.

Moreover,

the

existing

models

never

treated simultaneously all the climatic factors that affect a site, but always considered one factor at a time, whether passive solar energy gain, or wind infiltration. The models presented in this research should be useful to planners, the

architects and civil engineers,

opportunity

to

account

for

solar

offering them

energy

and

wind

protection more efficiently. Such models are practical tools to help planners in the selection of the "best” site design based

on

energy-conservation 160

criteria.

Analyzing

each

161 building's annual energy gain can help developing marginal improvements over a good site design. The effects of climate on buildings may suggest specific utilizations of buildings (e.g. poor solar access buildings could be used in commercial centers

or

for

parking).

The

monthly

results

provide

additional information and may suggest ways to improve target monthly energy budgets with such external remedies as sun shades,

insulators, etc. The usage of the external remedies

in a specific season may lead to an increase in the energy gain value. Finally, the overall energy gain in a site offers a

quantitative

planning

measure

purposes,

that

while

can all

be

used

partial

efficiently outputs

for

provide

important information as well. The applications of the modeling methodology presented in

chapter

IV

involved

several

site

layouts

that

were

evaluated exclusively from the viewpoint of their net energy gains. No other site planning criteria were considered (e.g. type of soil,

drainage,

aesthetics,

etc.),

so as to focus

exclusively on the effects of buildings locations on the net energy

gain.

Thus,

the

layouts

considered

might

be

very

objectionable with regard to other criteria, and should only be viewed as illustrative of the methodology.

However, the

sun/wind models could become tools and components of the site planning

process,

and

energy-conservation

could

become

a

routine part of the traditional planning/development process, increasing energy usage efficiency,

in balance with other

planning

objectives

related

to

environmental

protection,

aesthetics, market demand, and other social and psychological factors.

Energy considerations such as solar access,

wind

protection, and the site's potential for energy utilization should be recognized early enough in the development process so as t o affect decisions regarding the size and location of the development,

the mix of land uses, the choice of basic

service systems, and the transportation network layout. Large scale

developments

provide

opportunities

for

considering

alternative functional and locational patterns, and thus for integrating a variety of energy-saving techniques. Actually, most

landscape

architects

measures in their designs, to

consider

energy

conservation

but few developers are committed

comprehensive energy-conserving planning due to lack of

evaluation

of

conservation

its

value.

approaches

on

The a

evaluation

site

is

very

encourage the developers and the designers to

of

energy-

important account

to for

them. T h u s a computer simulation of the site's annual energy gains through its interaction with the prevailing climatic factors provides data that could be used to guide decision making

in

site

planning,

through

the

assessment

of

the

various tradeoffs taking place on the site.

5.2 Recommendations Further

research

clearly w a r r a n t e d :

work

along

the

following

lines

is

Instead of flat topography sites, the models could be applied to slope sites, because slopes sometimes offer better choices for energy conservation. Different building geometries could be considered, that may offer better choices for energy conservation (for instance, not only vertical wall s ) . The sun and wind simulation models could be embedded within an optimization algorithm that would modify the site layout in a systematic way to maximize total net energy gains, while accounting for site locational constraints. The models could be embedded within a broader energy model that would consider the cost and availability of other energy sources, accounting for their variations over time. This would provide an avenue for assessing the monetary value of climatic energy design.

APPENDIX A SAMPLE OF SITE DATA

This

appendix presents a

(Table A.l),

sample of

a sample of window data

buildings' dimensions (Table A . 3).

164

site 5 grid data

(Table A.2),

and the

Table A.l Grid.Data for Site 5: (Xi,Yi)= Building Coordinates on the Site, Height, Ti= Building Tightness, and Wi= Number of Windows in the Building.

*1

*1

x2

*2

X3

Y3

X4

*4

1

20

30

60

30

60

10

20

10

2

80

30

115

30

115

10

80

a

135

30

175

30

175

10

4

5

55

25

55

25

S

55

75

85

75

6

100

75

135

7

155

75

185

8

135

110

9

20

85

10

5

11

Ti

wi

54

1

2

10

54

1

5

135

10

54

2

10

40

5

40

30

3

0

85

60

55

60

36

2

1

75

135

60

100

60

36

1

0

75

185

60

155

60

36

1

7

170

110

170

90

135

90

30

2

0

45

85

45

70

20

70

18

1

0

110

25

110

25

90

5

90

24

1

0

45

105

75

105

75

95

45

95

30

1

0

12

8S

110

110

110

110

95

85

95

30

2

0

13

165

140

190

140

190

125

165

125

30

2

0

14

105

140

145

140

140

145

125

105

24

3

0

15

40

140

65

140

65

120

40

120

24

1

0

16

5

140

25

140

25

125

5

125

18

2

0

11

10

180

45

180

45

160

10

160

45

1

0

18

65

180

95

180

95

155

65

155

45

1

4

19

110

180

135

180

135

155

110

155

45

3

2

20

150

180

180

180

180

165

150

165

39

2

3

Hi= Building

165

Table A. 2 Sample Window Data: Blding= building number, windows= number of windows in a building, Fn= number of the wall that includes the windows ( see chapter III for the definition of all the other variables).

Biding

Windows

Fn

di

h,i

h2i

Wj

4

1

5

15

20

15

-

-

2

5

7

10

20

-

-

2

5

27

10

20

-

-

3

5

20

15

15

2

1

5

10

25

15

-

2

5

10

25

15

20

3

1

3

9

20

9

-

-

2

5

24

10

20

-

-

3

3

9

20

9

18

19 -

167

Table A . 3 Buildings Dimensions Building Number

Width (meters)

Length (meters)

Height (meters)

Tightness

1

20

40

54

1

2

20

35

54

1

3

20

40

45

2

4

15

20

30

3

5

15

30

36

2

6

15

35

36

1

7

15

30

36

1

8

20

35

30

2

9

15

25

18

1

10

20

20

24

1

11

10

30

30

1

12

15

25

30

2

13

15

25

30

2

14

15

40

24

3

15

20

25

24

1

16

15

20

18

2

17

02

35

45

1

18

25

30

45

1

19

25

25

45

3

20

15

30

39

2

APPENDIX B SOLAR CALCULATIONS COMPUTER PROGRAM

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IF (OIFFUSINT.LT.0.0] OIFFUSINT-O.O

sxaointmiffusint AZIHTH*PI/2*AZ INTH 00 UALL>1.3 SIflHTSHA0CW(WALL)*O UINOSIGNTSHAO(WALL)*0 WlN0StGNTCLRCUALL)*0 SlGHTCLR(UALL)»0 ENO 00 00 HCUSEMUN2-1.HUN OF HOUSES c C PROJECT THE POINTS ONTO AN AXIS UNICH IS PARALLEL TO SUN DIRECTION C ANO OMIT THE POINT WITH MINIMUM VALUE TO DEFINE THE UALLS THAT ARE C COVERED SY SHADOW

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*

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ENOIF ENOOO MINH*YINTER(1) MAX*YINTER(1) MINL-LC1) H IN L2*L(1) OO J * 1 ,4 IF {(YINTERCJ)) .L T . HINM) THEM MINM*YINTSR(J) GRIONNO, t)* G R ID X (I, J) G R I0M H (I,2)«G R I0YC I.J) H IH L*L(J) NIHPTC t ) * J ELSE IF ( (T IN T E R !J).E Q .M IN N ).A N D .(L(J).LE .M IN L)) THEN G R tO H N C t,l>*G R lO X(l,,l) GRIONNO ,2>*G R !0Y(I,.I) MIML-LCJ)

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