THE THERMAL PERFORMANCE OF FIXED AND VARIABLE SELECTIVE TRANSMITTERS IN COMMERCIAL ARCHITECTURE by William A. Bartovics B.A. Williams College, 1972 Williamstown, Massachusetts M.A. ED. Stanford University, 1973 Stanford, California Submitted in Partial Fulfillment of the Requirement for the Degree of Master of Science In Architecture Studies at the Massachusetts Institute of Technology February, 1984 c William A. Bartovics, 1984 The author hereby grants to M.I.T. permission to reproduce and to distribute publicly copies of this thesis docuterlt in whole or in part. Signature of Author Tepartinnt ~o-F Architecture September 27, 1983 Certified by Timothy E. Johnson Principle Research Associate Thesis Supervisor Accepted by Julian Beinart, Chairman Department Committee On Graduate Students MASSACHUSETTS NiTMSR~ OF TiCHNLOGY MAR 11984 LI6RARIES
Transcript
THE THERMAL PERFORMANCE OF FIXED AND VARIABLE SELECTIVETRANSMITTERS IN COMMERCIAL ARCHITECTURE
by
William A. BartovicsB.A. Williams College, 1972Williamstown, Massachusetts
M.A. ED. Stanford University, 1973Stanford, California
Submitted in Partial Fulfillmentof the Requirement for the
Degree ofMaster of Science In Architecture Studies
at theMassachusetts Institute of Technology
February, 1984
c William A. Bartovics, 1984
The author hereby grants to M.I.T. permission to reproduce and todistribute publicly copies of this thesis docuterlt in whole or in part.
Signature of AuthorTepartinnt ~o-F Architecture
September 27, 1983
Certified byTimothy E. Johnson
Principle Research AssociateThesis Supervisor
Accepted byJulian Beinart, ChairmanDepartment CommitteeOn Graduate Students
MASSACHUSETTS NiTMSR~OF TiCHNLOGY
MAR 11984LI6RARIES
THE THERMAL PERFORMANCE OF FIXED AND VARIABLE SELECTIVETRANSMITTERS IN COMMERCIAL ARCHITECTURE
BY
William A. Bartovics
Submitted to the Department of Architectureon September 20, 1983
in partial fulfillment of the requirementsfor the Degree of
Master of Science inArchitecture Studies
ABSTRACT
A parametric model is developed for use in evaluating the relativethermal and lighting performance of a variety of existing and proposedtypes of commercial glazing materials. The glazing materials consideredare divided into three general categories: (a) traditional glass of bothclear and reflectorized types; (b) glazings with selective transmissionproperties of the fixed variety which largely reflect the invisibleportion of the solar spectrum and contain only heat and which establish arange of operating cost bases; and (c) newly proposed electro-chromicglazing materials which variable transmit both the heat and daylightportions of the solar spectrum. This parametric model is based oncomparisons of total annual energy consumption for a typical perimeteroffice in a multi-story office building situated in a variety of citiesin the continental U.S..areas of reasonably dense commercial developmentwithin the continental U.S..
The results of the simulations showed a handsome potential savings,over several standard glazing types, for selective transmitters of boththe fixed and switchable variety. Fixed transmitters were also excellentperformers,several configurations offering savings often only slightlylower than the highest savings attained in the switchable group. Theswitchable transmitter group contained glazings which produced the lowestannual loads. The primary reductions were made in cooling loads withoutdramatic increases in lighting loads, but heating savings, resultingprimarily from glazing materials of high thermal resistance, proved to besignificant in cold climates.
Thesis Supervisor: Timothy JohnsonPrincipal Research Assistant, M.I.T.
For the opportunity and contacts toundertake this porject andFor the support, guidance andknowledge necessary to complete it.
For suggesting the topic,For valuable research helpmaterials andFor his daylighting experience.
and
For the funding, materials necessaryto carry out this projectFor assistance in prograrming,equipnent use, Graphics design,material properties,For the clarity of thought andguidance which each providedin turn with a personal interestfrom which I have benefittedhugely, and for which I amgrateful.
For educating me in the Sun-pulse methodology andFor guidance in its manipulation.
For word-processing equipment andtime without which thisdocument could not have beenproduced.
For architectural Illustrations,Formatting of graphical design,Layout assistance and forunsurpassed nocturnal vigilance.
For editorial and graphicalassistance
For assistance with prograningsolar correlation and integrationtechniques.
For her consistant support andlabor toward the production ofthis thesis.
TABLE OF CONTENTS
PART 1 INTRODUCTION
PART 2 SIMULATION SITES AND WEATHER DATA
PART 3 SIMULATION PROGRAM & STRATEGY FOR SWITCHABLE GLAZING
PART 4 ARCHITECTURAL CHARACTERISTICS & OCCUPANCY REQUIREMENTS
PART 5 AUXILLIARY POWER SYSTEMS AND CONTROLS
PART 6 OUTPUT ANALYSIS
PART 7 CONCLUSIONS AND SUGGESTIONS FOR FURTHER WORK
APPENDIX A
APPENDIX B
APPENDIX C
APPENDIX D
APPENDIX E
TABLE OF RECOMMENDED AVERAGE MONTHLY DECLINATIONS
ASSUMED DIRECT/DIFFUSE SPLITS
CORRECTED WEATHER DATA
MODIFIED SUNPULSE ROUTINES
ENERGY BALANCE EQUATIONS
p. 7
p. 13
p. 27
p. 37
p. 53
p. 57
p. 87
p. 93
p. 95
p. 97
p. 113
p. 115
APPENDIX F SIMULATION PROGRAM FLCW CHART
APPENDIX G SIMULATION OUTPUTS
APPENDIX H ELECTRIC RATES FOR VARIOUS U.S. CITIES
p. 117
p. 121
p. 135
6
PART 1
INTRODUCTION
The increasing base cost of power and changes in rate
structures since 1973, together with a general retreat from high
illumination requirements, have regenerated an interest in using
fenestration to lower energy consumption in commercial buildings. With
the advent of new glazing technologies comes the potential of managing
the solar contribution to the energy required for comfortable working
conditions. The process of this solar management, however, is
complicated by the internal gain schedule which in "load dominated
buildings" coincides, for the most part, with the periods of maximum
solar flux. The issue in commercial glazing strategies is not the usual
matter of maximizing heat gains and minimizing loses as has been the
basis of the approach to residential glazing. The issue in commercial
structures, rather, is a question of supplying the required daylight,
without significantly adding to the already high heat gains which exist
during daytime occupied hours.
Traditionally, the reduction of cooling loads was considered to be
the principal target in glazing design strategies. This attitude led to
the use of small aperture size and/or glass with very low transmission
characteristics in an effort to reduce solar heat gain as much as
possible. The result of this approach was to increase the amount of
purchased lighting energy. The 1981 SERI studies have shown that
lighting and cooling now demand equal amounts of energy. Together they
comprise the largest consistent percent of the annual load in standard
offices. In some climates, however, heating loads during unoccupied
hours can also be significant contributors to total annual energy use.
The fact that heating loads occur primarily during unoccupied hours
makes that category a difficult target for reduction through solar
management. Lack of available storage media rather than inappropriate
glazing material is the source of this problem.
New glazing technology and an expanded repertoire of natural
lighting techniques have begun to offer the means of decreasing lighting
loads without a concommitant increase in demand for cooling power.
These new technologies are based on a selective transmission of the
solar spectrum. Generally these glass types are "tuned" to admit the
visible portion of the spectrun, while at the same time disposing of the
infra-red portions. These materials can be divided into two classes:
those of fixed transmission characteristics, and those of dynamic trans-
mission characteristics. Of the dynamic varieties, electro-chromic mat-
erials provide the greatest control flexibility, thus lending themselves
most readily to simply applied control strategies. In climates which
tend to have moderate ranges in available sunlight, such as Boston,
fixed transmitters offer a great benefit from daylighting. However,
glazing materials with controllable dynamic transmission characteristics
could reduce heating loads during unoccupied daytime hours. At the same
time lighting loads during working hours could be substantially
reduced under both dim and bright conditions without suffering increased
cooling loads. Both of these new materials offer great potential
benefits without the excessive heat gains usually associated with larger
window areas.
As a result of these possibilities, it is quite clear that a
general reduction in the quantity of commercial power consumption is
attainable. The relative benefits in power consumption for the variety
of existing glazing products in the face of current daylighting
techniques is not yet clearly established. Nor is it yet clear what
might be the marginal benefit of glass possessing dynamic transmission
characteristics over these existing technologies.
In order to quantify the relative benefit of glass types which
either exist now or are imminently possible, it is necessary to compare
the impact on total power consumption of each example as a sum of the
simultaneous lighting, cooling and heating loads for a given commercial
archetype. The process of developing such a model was done in two
steps. First, sixteen simulation sites within the continental U.S. were
chosen and weather data constructed for each site. The choice of sites
was based upon areas of reasonable commercial developnent and the ex-
pected annual climatic demands in each of the main categories of energy
consumption: lighting, cooling and heating. This limit to the number of
simulations for each glazing type was set in order to a minimize the
output volume without sacrificing the national scale of the results. A
representative group of six cities, three heating dominated cities and
three cooling dominated cities, were chosen to illustrate the load
pattern of each parametric comparison, but the simulation results for
all sixteen cities are included in Appendix G. The second step was to
develop an appropriate parametric model. The function of this model was
to establish a uniform method for testing each of the selected glazing
strategies against one another. The model is based on a typical peri-
meter-zone office with standardized architectural characteristics and
patterns of use.
The remainder of this comparative study consists of a description
of each glazing type chosen for examination and a discussion of the
simulation results. The glazings chosen for comparison are divided into
three groups. The first group is made up of the traditional clear and
reflective types, and both single and double glazed configurations of
each are included. The second group is made up of four different
selective transmitters of the fixed variety. Four different "heat
mirrors" are examined in this group, and they include single, double and
triple glazed varieties. The third group is made up of five
electro-optic glazings (ELO 1 to 5) of different transmission ranges.
All glazings in this final group are double glazed units. Tables 6.1
and 6.2 list the parameters for all glazings.
The comparisons are based on total annual power consumption, but
the relative contributions of lighting, cooling and heating to the total
load for each glazing type are indicated. The impact of changes in
glass area, azimuth, configuration of thermal mass and heating fuel on
the annual load are also identified. In addition, the relative impact
of peak kilowatt charges per year are illustrated as equivalent KWH for
all comparisons. The conversion of peak KW per year into equivalent IWH
was done by multiplying the sum of each month's peak load in KW by the
ratio of $6 per peak KW to $0.10 per KWH. The assunption here is that
the ratio of peak charge to KWH charge should remain fairly consistent
from city to city even if the absolute rates do not. appendix H shows a
listing of current KWH rates for various cities throughout the U.S. as
tabulated by the Energy Information Administration in Electric Power
Monthly,form 101, May 1983.
12
PART 2
SIMULATION SITES & WEATHER DATA
The number of simulation sites were restricted to the minimum
points necessary to bracket the different climate types within the
coterminous United States, in which significant commercial developnent
is to be found. Particular attention was given to the northeast coastal
area with the middle-atlantic states and south representing second
priority. Six cities (Caribou, ME, Boston, MA, New York, NY,
Washington, DC, Charleston, SC and Miami, FL) were picked from the
available data, as cities which might best illustrate the climatological
picture of the heavily developed eastern seaboard. The mid-western
section of the country, from the Appalachian mountains through the
Mississippi River Valley was given three simulation sites; Madison, WI,
Nashville, TN, and Columbia, MO. The upper plains states in the west
were generally overlooked because of the relatively thin commercial
developnent, but the cities of Fort Worth, TX, and Great Falls, MN,
should give clear boundaries of performance at the southerly and
northerly extremes of this area. The south-western states of Arizona
and New Mexico are simulated by Phoenix and Albuquerque respectively.
The extreme west and coastal states are bracketed by the cities of
Seattle, WA, Ely, NV, and Santa Maria, CA. Figure 2.1 shows the
FICM 2.1 The Continental Distribution Of Simulation Sites
distribution of the sixteen simulation sites chosen for this study.
The climatological factors which are most important to the
simulations are those which directly impact energy flows through glazing
materials, and through the opaque materials which make up the remaining
portion of the weather wall in conmerical architecture. The available
solar radiation together with the ambient outdoor tenperature are the
dominant climatological factors in the calculation of any architectural
energy balance. As a result, the weather data for the simulations was
designed to account for these factors directly. The moisture content of
the outdoor air is also an extremely powerful variable [Henderson,
S.T.,DAYLIGHT AND ITS SPECTRUM,(New York; American Elsevier Publishing
(b., Inc.,1970) pp.23-34]. Although hunidity is not directly accounted
for as an independent data input, there is an implicit accounting for
its impact through variations in both the radiation and temperature
inputs. Both radiation and temperature vary according to daily
atmospheric clearness.
The weather data used for each simulation is a modified version of
the approach developed by Gordon Tully in his "Sunpulse" simulation
program for TI-59 calculators [Tully, Gordon, "The 'Sun-Pulse' concept -
A Simple Approach to Insolation Data" (Newark, Delaware, Proceedings of
the 5th National Passive Solar conference, 1980)]. The "Sunpulse"
program compresses hourly Typical Meteorological Year ('IMY) solar gain
and daily temperature data into a small number of mathmatically variable
inputs for each month. The weather data is designed to supply
insolation and temperature data for seven representative days per month.
The " Sunpulse" data system was chosen because it is based on the real
hourly measurements supplied by TMY data rather than mathmatical
approximations, and because its "seven day per month" simulation format
makes it extremely compatible with the ordinary weekly commercial
schedule. The error, due to intermittent holidays and variations in the
length of each month, is therefore minimized in comparison with
alternative systems such as the "Bin Data" approach which calls for a
seven day simulation for each two month period. Also, "Sunpulse",
generated according to the sinusoidal distribution of sunshine over the
given day, allows the flexibility to more realistically represent the
variable conditions which normally occur during any given day.
Simulations which are based on average data are not variable enough to
realistically model the demand on the lighting system, nor the resultant
impact on heating and cooling loads due to the heat content of the el-
ectric lights.
The typical hourly meteorological data is reduced, by "Sunpulse" to
only 24 numbers per month: IT, IM, IK and 7 CLRNS, 7 temperature average
and 7 temperature range numbers. The outdoor temperatures are compressed
by the monthly derivation of a 24 hour average temperature and an
average daily temperature range for each month. In addition to a single
monthly average temperature and range, "Sunpulse" supplies an average
daily temperature and range for each day of the month with an associated
CLRNS. An average daily temperature and range could be derived for each
of the seven representative CLRNS inputs. Each of the seven simulated
days per month in this application, therefore, were given a specific and
unique average temperature and range. The temperatures for each day are
also sinusoidally distributed according to the hour angle relative to
noon, of the hour under consideration. They are, however, distributed
over a full 24 hours with the minimum and maximum tempertures occurring
at 2h00 and 14h00, respectively, so that the maximum temperature minus
the minimum equals the temperature range for that day (see figure 2.2).
The solar gains are compressed by the monthly derivation of 1.) a
greatest hourly gain in Btu/hr (called IM for insolation maximum), 2.) a
greatest average daily gain in Btu/day (called IT for insolation total
and 3.) seven "clearness" numbers (CLRNS) which represent daily in-
solation totals for each of the seven representative days as a percent
of the clearest day in each month. Both IM and IT are in units per
square foot of receiving surface area. In addition to these nine basic
inputs, there is an adjustment variable (IK) which represents the
where:THEATN = the nighttime thermostat settingQS = total solar gain for the hourIGN = total internal gain for the hourUAW = total heat loss coefficient (UA) for the
office including infiltrationCA = heat capacity of the sheet rock and
furniture in the office attached to theair temperature
0.6 = the percent of total solar gaindistributed to the floor surface
CR = heat capacity of floor coveringUAR = heat transfer rate of floor covering x
areaCS = heat capacity of floor slab under floor
covering
Since the formula is recalculated hourly, it allows an interfingering of
surmer and winter conditions through the swing seasons of spring and
fall, but remains quite consistently in one mode or the other during the
true winter and summer seasons. It is also objective enough to accept
different floor finishes of different heat capacities and U values,
which bring the floor slab into differing degrees of involvement with
the thermal swings of the office.
Under winter conditions, the glazing is assumed to be in the clear
(bright) state until either the air temperature has risen to the cooling
set point (730 when occupied and 800 when not) or until the floor
covering rises to 1100 F. In many climates, the second thermostat in
the floor covering is not necessary as the floor surface never arrives
at 1100 before the air temperature arrives at the cooling set point. It
is only in clear, sunny, hot cities such as Phoenix, that such a control
appears truely necessary, and in these climates, it is only of critical
importance with floor coverings that have small U values and capacitance
such as rugs. Because a rug is the most commonly used floor covering in
commercial buildings, and since the base comparisons are all made with a
rug floored office, this thermostat was consistently applied to all
cases. In the winter, each hour's energy balance is calculated with the
glazing "bright", and then the internal air temperature is compared to
the cooling set point. If the air temperature is above this point, and
if daylighting can still be accomplished in the "dark" state, according
to the lighting level measured in the rear of the office, then the
glazing is switched "dark" and that hour's energy balance is recalcul-
ated in this state before the appropriate loads are recorded. This
recalculation of the "previous" hour assumes that the anticipation of
the thermostat would trigger the switch during the hour under consid-
eration, and that the recalculation of the whole hour is more accurate
than assuming that overheating is allowed for a full hour before the
switch occurs.
If on the other hand, summer conditions have been determined, then
the glazing is assumed to be switched to the "dark" state at all times
except during working hours when the "bright" state is either necessary
to accomplish daylighting, or when it is dim enough outside to require
supplementary lighting. During non-working hours, in the summer, then
the glazing is always "dark". This mechanism is based on the idea that
only the energy which is absolutely necessary for lighting should be
admitted in the first place, since excess sunlight can only contribute
to the cooling loads during this season.
The additional savings produced by this seasonal variation in
switching strategy as compared to one which operates exclusively on the
basis of air temperature is quite small. The extra complexity and cost
of controls, if the switch were to be fully automatic, would not be
warranted. It is conceivable that the seasonal switch on/off strategy
could be done manually with both the dwell and anticipation being es-
tablished over a short period of trial and error in a real office. The
essential purpose of the given strategy was to provide one which would
be objective enough to function equally well in all the cities to be
simulated in this study, and to establish, as effectively as possible,
the upper limit to the savings for the two step pattern of switchability
(on-off) which was proposed.
PART 4
ARCHITECTURAL CHARACTERISTICS AND OCCUPANCY REQUIREMENTS
The architectural aspects of the parametric model were pared down
to those concerned with a single representative perimeter office bay
with a single exposure. The office is seen as the smallest heating,
cooling and lighting unit within a perimeter core commercial building
prototype of undefined height. This approach was taken because core
loads are constant and neither affect nor are affected by the loads
experienced in adjacent offices. It is also assumed that the energy
demand implications of any given glazing strategy will be contained
entirely within the attached office space. This assuntion implies that
it is not necessary to consider the loads of an entire building,
containing many such office units, in order to establish the relative
benefit of one glazing strategy over another in terms of energy use per
square foot of glass.
The office used to compare glazing strategies in all simulations is
rectangular in plan with 12 feet of width along the weather wall, a 16
foot depth and a 10 foot ceiling height. The walls, floor and ceiling
are considered to be adiabatic with regard to adjacent spaces. The
office is daylit from one side only, and the glazings are generally
defined as wall to wall strip windows of varying heights. Figure 4.1
shows the basic office bay in plan and section. These dimensions were
rnu
FIGURE 4.1 The Gerric Perimeter Office: Plan And Section
chosen in part because they are generally representative of
perimeter/core office configurations. The depth of 16 feet, however,
was chosen primarily because of daylighting concerns, because such a
depth poses no serious problem with regard to either the penetration or
level of light, when using light shelves or reflectorized louvers for
the distribution of light [Rosen, James, "NATURAL DAYLIGHTING AND ENERGY
CONSERVATION: INNOVATIVE SOLUTIONS FOR OFFICE BUILDINGS, Masters Thesis(
Cambridge, Ma., Massachusetts Institute of Technology, Department of
Architecture, 1982), p. 64]. Finally, since a relatively even
distribution of light is feasible at this depth, the solar energy is
also evenly distributed by reflection and diffusion from the louvers to
the various room elements.
The office can be faced in any direction because of the flexibility
built into the solar calculation subroutine (south at 00, west at 900,
north at 180 0, and east at 2700 ). However, any given simulation can
consider only one orientation at a time. Any office around the
perimeter of the given commercial structure can be individually
examined, except those occupying a corner position, with walls facing
two orientations at once. By so doing, it is possible to establish, with
a high degree of clarity and accuracy, the impact of orientation on the
relative benefit of the glazing strategies examined.
The interior finishes were designed to represent customary patterns
of color and material type. The ceiling was given an accoustical
treatment which was assumed to be 80% reflective to light, and 90%
absorptive to sound at middle frequencies. This treatment also provided
the conceptual function of isolating the office below from any thermal
impact from the energy flows in the floor slab of the office above. The
walls were assumed to be 5/8 inch gypsum board, and a capacitance of 3
Btu/ 0 F was attached to the room air to account for its mass effect. The
sunlight is well enough distributed, and the gypsum board is thin enough
to cause almost no thermal inertia and thus, one can assume that the
temperatures of the air and dry wall will swing together. The walls are
painted with a finish of 70% matt reflectivity. This configuration
represents an off-white, flat finish paint, and although bright white
(80% reflectivity) would enhance the daylight levels throughout the
space, the former was chosen in order to keep the finishes on the
conservative side of what is ordinarily found in contemporary office
spaces. This issue is implicitly included in the daylighting
calculations and is therefore, like the basic dimensions of the office,
a difficult parameter to change easily. However, these architectural
features are sufficiently common configurations to be valuable, and
changes to them are small in their impact on the value of any given
glazing strategy.
The floor was treated as an area where easy parametric changes
might be valuable. The reflectivity of the floor to daylight was fixed
permanently at 40%, but the type of floor finish used over the concrete
slab may be easily modified in terms of the thermal mass and its
resistence to heat flows in and out of the slab below. Because rugs are
ordinarily found in office spaces, the base simulations were all run
assuming a rug over the slab. The U value of the rug, and its thermal
capacitance were established by experience gained from MIT's Solar
Building V [Johnson,Timothy E., and Edward Quinlan, "MIT SOLAR BUILDING
5: THE SECOND YEAR'S PERFORMANCE"(Cambridge,Ma.,MIT Department of
Architecture, 1979)p.58]. The application of the rug significantly
:E:: RUG COVERED SLAB
TILE COVERED SLAB
PEAK K/YR IN EQUIVALENT KWH
T COOLING CLIMATES0
A 00- EATING CLIMTESL
300 --KWH 200. -
Y
R
V WSTON MIADISON SEATTLE MIMI PNOIX FT. WORTH
FIGURE 4.2 Total Annual Loads With Rug Vs. Tile Covered SlabAssuMing Clear-DG
damps the interaction of the massive concrete floor, though it does not
entirely eliminate its impact. It is possible to largely eliminate the
damping which resulted from the rug by substituting vinyl tiles. The
tiles had a noticeable impact on the participation of the floor slab in
the thermal swings experience by the office, particularly in heating
climates due to their increased U vlaue of 20 Btuh/ 0 F ft2 [ASHRAE
HANDBOOK AND PRODUCT DIRECTORY; 1981 FUNDAMENTALS (New York, ASHRAE
Inc., 1981) p. 26'10, Table 13]. Figure 4.2 shows the relative impact
of a rug versus tile floor for south-facing offices with 64 sq.ft. of
double glazing in representative cities. The tiles were assuned to
retain a 40% reflectivity to light, but the potential qualitative
problem of specular reflections from their surface was not considered.
Window sizes were also easily varied, although the implications of
glass area with regard to daylight distribution and the assumed electric
lighting controls (described in detail below) have not been thoroughly
tested. The ordinary office window is on the order of four feet in
height (48 sq. ft.) but this area is inadequate to meet the minimun
lighting levels on dim days. Figure 4.3 illustrates the differences in
total loads for a south facing rug floored office with strip windows of
48, 64 and 72 sq.ft. respectively, as marked. It was decided,therefore,
to increase the glazing area in order to accomplish full daylighting on
average overcast days (350 fc), assuming a visible transmission of 81%,
and an effective distribution of daylight into the office. This step
was taken in order to illustrate the point that a reduction of window
size for the sake of smaller cooling loads is not necessarily the best
approach, and also to more completely evaluate the relative benefits of
the more recent glazing materials under optimum daylighting conditions
[Rosen, James "Natural Daylignting and Energy Conservation: Innovative
Solutions for Office Buildings", pp. 11-20]. In addition to the in-
creased window area, a new feature for daylight distribution was also
added. This feature consists of replacement window blinds which are
both inverted, in comparison to ordinary blinds, and reflectorized on
the top surfaces in order to provide more even distribution, and a
deeper penetration of daylight into the office. Figure 4.4 illustrates
the configuration of both the older type and the assumed type of blinds.
The illustration in figure 4.5 compares the daylight distribution under
cloudy day conditions which results from an untreated window to one
which employs the assuned system. From these comparisons, it is clear
that the relative uniformity of distribution which results from these
TOTAL ANJAL LOAD IN KWH
PEAK K/YR IN EQUIVALENT K
BOST0TAL
K0H
9l fE qf
Alo - 9Yi f q
CLEAM G t/LT-TG EL-5
mem
32*
Im
288w
2564
CLEmAI RtT-TG ELO-4
PHOENIX
* I - I - I miii & I I * I I I
CLEDG lWLT-Tc E-5
CEAR G Hlt/LT-TC ELW-5
FICLE 4.3 Total Annual Loads Lkder Various Window Amas
FIGRE 4.4 Old Vs. New Stale Window Blinds For Daglight Distribution
blinds is requisite to the effective use of solar energy for
daylighting. The high lighting levels near the window and the great
contrast between levels, front to rear, (200 to 30 fc) in the
undistributed condition will cause qualitative as well as quantitative
problems within the office. Qualitative issues such as contrast glare,
due to the excessive brightness at the window, will cause adverse
working conditions and occupant discomfort. As a result quantitative
issues will then receive a negative impact due to a need for increased
illumination levels at the rear of the office in order to overcome the
contrast glare. These increased lighting levels can only be accom-
plished by turning on at least some if not all the interior lights. The
result, then, is an increased lighting cost. Furthermore, uneven dis-
tribution of sunlight can, even with new glass technologies, create "hot
spots" near the windows. This uneven distribution of heat, together
with the additional heat from purchased lighting can dramatically affect
DAYLIGHT DISTRIJTION WITH REFLECTIVE BLINDSDAYLIGHT DISTRIBUTION WITHOUT BLINDS
MK 2 BE I
HORIZONTALSKY ILLUMINATION
1214 Fc
FIGLE 4.5 Daylight Distributions With And Without Reflective Blirs
the need for air conditioning and hence the total energy cost of the
office. It is therefore assumed that distributive blinds are installed
on all windows as a prerequisite to changes in glazing strategy. The
window area was established in accordance with the British Research
Station protractor calculation techniques, which, together with the
minimum required illumination of 30 foot candles in the back of the
room, established the base window area to be 64 square feet. This area
represents a 12 foot wide strip window, approximately 5.7 feet in
height.
The occupancy schedule was structured to maintain a normal work
week for 52 weeks per year. There were no provisions made for regular
short term breaks in the ordinary commercial schedule such as vacations
or national holidays. However, since any given year is relatively
balanced with breaks, and since vacation days generally comprise no more
10-
0-
00L
-
T0 406-TA RL 3WP
L y N . - -. . ---. BOSTON0 L.. -. 9-.. SEATTLEA .. -.... PHOENIX
U 9 I I I I I I I I I I I IH JA FEB M APR MAY J14 JUL AUG SEPT OCT NOV DEC
MoNTH
FIQE 4.6 Representative MonthlV Loads
than 3% of the work days, their impact should not qualitatively alter
the comparisons to be made between glazing systems. In practical
reality, this aspect of the occupancy schedule might produce payback
periods which are slightly longer (no more than 3%) than the data below
might indicate.
The normal work week begins on day 2 of the seven day simulation,
and ends on day 6. Day 1 and 7 are sunday and saturday respectively.
When coupled with the weather data, this schedule produces a consistent
pattern of clear sundays and cloudy saturdays. Day 1 of the simulation
is always given a CLRNS of one, while day 7, saturday, consistently
draws CLRNS variables on the order of 50% or less. The effect of
changing this pattern was not studied, but again the impact should be
relatively small and consistent across glazing types. If the monthly
total loads for any glazing system in any city are graphed, there is a
noticable dip in February and a peak in March (see Figure 4.6). It is
very likely that the occupancy schedule together with the pattern of
clear versus cloudy days and the relative shortness of February produce
this apparent aberation. It was ignored in this analysis.
The daily work schedule begins at 8h00 and ends at 18h00. All of
the thermal and illumination requirements are met at 8hoo and are
maintained until 18hoo. The building, then, is assumed to be completely
unoccupied all day on days 1 and 7, and between 18h00 and 8hoo on days 2
through 6.
During working hours, the thermostats are set to 68OF for heating
and to 73 0 F for cooling. A variety of unoccupied thermostat settings
(setbacks) were examined, and the results are shown in Figure 4.7 for
both rug floored and tile floored, south facing offices with 64 sq.ft.
of double glazed windows. The impact of setbacks should be parallel for
other glazing types.
It is interesting to note that the additional savings due to "deep"
setbacks are small for a rug covered floor, and virtually non-existant
for a tile floor. In this situation, a protracted demand for purchased
heating or cooling energy, at the beginning of the occupied hours,
reduces the benefit from off hour savings, especially since the daytime
energy gains are generally greater than what can be stored or lost to
the outdoors. The purchased energy necessary to cool or reheat the mass
displaces the heat of internal loads which must then be removed by the
chillers in either case, later in the day. Although allowable setbacks,
particularly for offices with little direct participation of internal
mass, such as those with rug covered floors, could be "deeper", the
setbacks established for all simulations were 550 for heating, and 850
for cooling. These settings were chosen because they reap the majority
of the potential savings, and, perhaps more importantly, because they
fall easily on the conservative end of normal practice.
The illumination requirements assumed in the model follow the
THERMOSTAT SETBACXS IN KEY AR FOR HEATING/CM.ING
NO SETBACXS
SETEC=S G8
SETACS a 55/85
PEAK KW/YR IN EGJIVALENT KWi
T 54.- COOLING CLIMTES0 HEATING CLIMTES
T\
AN'
SK ST jjEFWRK OERDSA
T 5000-0TAL
K
H 2900
AR +m
COOLING CLIMATES
TILE COVEED SLAB
FIGWE 4.7 The Relative Savings For Thermostat Setbacks Assuming Clear-D
current trend toward lower minimum ambient levels with local task
lighting as required. Since the assumed office is not large (16 x 12),
it is likely that most work stations would be located closer to the
windows than to the back wall. For this reason the rear of the office
will be devoted to circulation functions. Furthermore, since work
stations are assumed to be near the windows, and since the windows have
been enlarged, for the base runs, no specific requirement or internal
gains were established for task lighting. The minimum requirement of 35
foot candles will generally be exceeded on the work plane. The model is
designed, finally, to maintain these minimum levels only during working
hours (8h00 to 18h00). There is no lighting requirement or load
established outside of these times or on weekends.
The internal gain schedule also follows working hours. The gains
are considered to be constant through the workday, and are sized to be a
reasonable representation of the gains which would be associated with an
office of a similar size to the model. There are three components to
these internal loads; the heat of lights, equipment and people. The
connected lighting load is assumed to be 1.5 watts per square foot of
floor area. When lights are required, a maximum of 5.1 Btu's per square
foot of lighted floor area is added to the internal load. The heat gain
for equipnent is assumed to be one watt or 3.414 Btu's per square foot
of floor. The occupant gains were established for one person according
to the ASHRAE Fundamentals recommendation of 320 Btu/hr of sensible heat
gain[ASHRAE HANDBOOK AND PRODUCT DIRECTORY, 1981 FUNDAMENTALS, Chapter
23, p. 25'17 Table 16]. There is no accounting of latent loads due to
either people or ventilation air. The impact of latent loads would
certainly boost cooling loads in most areas, but fenestration strategies
will only affect sensible heat gains. Therefore, since the latent heat
of vaporization does not change the relative behaviors of the glazing
materials, it can be ignored.
The ventilation schedule is the only one of the occupancy
requirements which was designed to be constant through working as well
as non-working hours. The fixed hourly ventilation rate for the office
space was established, according to Mass State Code at 0.1 cfm per
square foot per occupant[ASHRAE HANDBOOK AND PRODUCT DIRECTORY, 1977
FUNDAMENTALS (New York, ASHRAE, Inc., 1977) Chapter 21, p.21'14, Table
6]. At this rate, the office receives 1152 cu. ft. of outdoor
ventialtion air per hour, or 0.6 air changes per hour. A variable
ventilation system to reduce the air exchange rate during unoccupied
hours was considered, but because of the cost of the required controls,
and because few commercial buildings have such controls installed, a
constant volume system was chosen for the model. Such a variable
ventilation system uniformly increased cooling loads, probably due to
loss of nighttime cooling during the swing seasons. This increase makes
such a system a potential deficit in cooling dominated climates,
although savings due to reduced heating loads in colder climates
outweighed the annual increase in cooling loads for these cities.
Ventilation systems with the appropriate controls, and particularly
those which were based on the "economizer cycle" model, however, could
substantially reduce heating loads during unoccupied hours. Figure 4.8
shows the effect on heating loads of reduced off-hour ventialtion rates.
The figure is based on double glazing, but the relative impact should be
the same for each window type studied.
VARIABLE VOLMES IN KEY ARE FOR OCCUFIED/L90CCUPIED OMS
CONSTANT VOLUME VENTILATION (1152 efh)
VARIABLE VOLUME VENTILATION (1152/192 cfh)
PEAK KWYR IN EGUIVALENT Kim
COLING CLIMATES
HEATING CLIMATES
BOSTON MADISON SEATTLE MIAMI PHOENIX
RUG COVERED SLAB
COOLING CLIMTES4000-r
HEATING CLIMATES
Iw+
BOSTON MADISON SEATTLE MIAMI
TILE COVERED SLAB
FIGURE 4.8 The Relative Savings For Constant Vs. Variable Ventilation RatesAssuming Clear-DG
T 5006.
40
10*0
0-
FT.WORTH
52
PART 5
AUXILIARY POWER SYSTEMS & CONTROLS
The auxiliary heating system for the parametric model was assumed
to be in-duct electric resistence heaters. The choice of an all
electric system was made in order to allow the total loads to be easily
expressed as a single unit to facilitate eventual cost comparisons.
Furthermore, because of the higher operating cost of electric heat, it
provides an appropriate "worst case" under which to estimate the best
potential savings for any given window system. The heating coils are
controlled by a standard thermostat, and it is assumed that the units
are capable of delivering precisely the number of Btuh needed at an end
use efficiency of 100%. However, since purchased steam or fossil fuel
heat are approximately one half the cost of electricity, the impact of
non-electric heating plants can be estimated with consistent units, by
simply dividing the heating load in half and adding it as KWH to the
total load. The model was designed to allow heating loads to be
excluded from total KW demand, which often changes peak load charges
during winter months. Accordingly, Figure 5.1 shows the rough impact of
non-electric heat on the total peak loads for the representative cities.
The office represented in the figure is a low mass (rug floor) office
with south facing, clear double glazing.
ELECTRIC HEAT U/RUG COVERED SLAB
STEAM HEAT W/RUG COVE SLAB
ELECTRIC HEAT W/TILE COVERED SLAB
STEAM HEAT W/TILE COVERED SLAB
- PEAK Ku/YR IN EQUIVALENT K
T0TA 30-L
K 8
E
RBOSTON MADISON SEATTLE
GRWH ASSLES STEAM HEAT CMPOENT a 1/2ELECTRICAL SOURCE ERGY FOR EUIVALENT 1iI
FIGM 5.1 Electric Vs. Steam Heat Expressed In Equivalent h
Assumin Clear-DG
The air conditioning systen is assumed to be a standard chiller and
air handling system with a system coefficient of performance (COP) of 2
including fan power. 'Ihe cooling loads for all simulations therefore
represent one half of the total number of cooling Btu's in a given time
period. A COP of 2 was chosen in an effort to roughly account for fan
power (which is not otherwise accounted for) . The reduction of pot-
entially higher COP's for comrmercial chillers to the established system
COP of 2, therefore, implicitly attaches the cost of ventilation and
cooling fan power to the cost of air conditioning. It is expected that
any resultant error in total loads is of little importance to this
study. Because "economizer cycles" are still relatively uncommon in
conmercial buildings, and because the retrofit costs are generally
prohibitive, there is no provision made in the model for such a system.
Should the issue of variable ventilation rates become important to the
analysis of other strategies, however, chiller efficiency and fan power
could necessarily become powerful and independent variables, and the use
of a "system COP" would then no longer be an adequate expresseion of
energy use. The cooling system, finally, is also operated by a standard
thermostat, and is capable of exactly meeting any hour's demand.
The lighting system is assumed to be a flourescent system capable
of maintaining a minimum of 35 foot candles on the work plane from a
connected load of 1.5 watts per square foot of floor area. The basic
office of 192 square feet was divided into 3 discrete lighting zones
running parallel to and in from the weather wall. Each zone is 64
square feet and all three zones are controlled by a single central
photocell. The sensor is connected to simple on/off switches which
deliver a full 1.5 watts/sq.ft. to their respective zones whenever
daylight levels during occupied hours drop below 30 foot candles.
Daylight levels are allowed to fall to 30 foot candles before back up
lighting is added in order to insure that back up is truely necessary,
assuming that the rear of the office will be devoted to circulation, and
assuming that each zone of electric lighting will make some contribution
to lighting levels in the adjacent zone. Lighting loads are calculated
hourly according to the daylight admitted by the given glass, and
assuning that daylight has the same or a slightly higher efficiency than
flourescent lighting. Under this assunption, if the average "daylight"
levels in Btu per square foot of floor falls below 5.1 Btu (1.5 watt)
per square foot, as measured by the central sensor, then the level in
each zone is evaluated and, if necessary, the lights for each of the
zones are turned on. The total Btu/hr added to each zone is then added
to the internal gains for that hour. The daylighting distribution
system of inverted blinds, described above, establishes the distribution
of daylighting Btu's between the extreme points at the front and rear of
the office. According to the tests carried out by Jim Rosen, the dis-
tribution ratios (DR) for daylight in the front and rear of the office,
expressed as a ratio to the mid- point, are 1.3 and .67 respectively
during conditions of overcast skies at any orientation [Rosen,James
"Natural Daylighting and Energy Conservation: Innovative Solutions for
Office Buildings", p. 74]. Therefore, since an average solar flux of
5.1 Btu/sq.ft of floor area is assumed to provide the minimun lighting
levels (30 fc) in the back of the office, an actual level of 3.4
Btu/sq.ft. (5.1 x .67) establishes the minimum daylight requirement for
each zone. The triggers for each zone, as read at the central sensor,
then are set at 3.4 Btu/ft divided by the distribution ratio for each
zone (See Figure 4.5). The electric lights, then, will come on indep-
endently for each zone, from back to front. If the available daylight
falls below 5.1 Btu/ sq ft at the center point, the lights in the rear
third of the office will come on. If the daylight level at the sensor
falls below 3.4 Btu per sq.ft, then the center third of the office is
added, and finally, if the threashold of 2.6 Btu/sq ft in the center of
the office is passed, then the third nearest the windows will also be
added.
PART 6
OUTPUT ANALYSIS
The glazings chosen for analysis as base case examples represent
three generic types: Clear glass, reflective glass and static selective
transmitters (heat mirrors that primarily reflect the near I.R.).
Single and double glazed configurations are examined for each category,
and triple glazed configurations are also examined in the third
category. In all cases, single and double glazing units consist of one
glazing layer of the categorical type, with the second layers, if
present, being made of clear float glass. The third layer in triple
glazed units is a polymer substrate which carries the selective coating
between two layers of clear glass. All of the main glass comparisons
are made under a common set of assumptions: 1) that the office space
behind them is low in mass (rug covered slab), 2) that it is ventilated
at a constant rate, 3) that it is electrically heated and cooled by a
constant volume ventilation system, 4) that the system COP's are 1 for
heating and 2 for cooling, and 5) that the glass area is 64 square feet.
These assumptions are discussed in detail above in Parts 3 and 4.
Differences in total energy cost between glazings, therefore,
grow from their respective interactions with the ambient outdoor temper-
ature, and with the visible and infra-red portions of the solar
spectrum. Figure 6.1 illustrates the solar spectrum, and its four main
SO.AR SPECTRUM, AM 1.5
75t -"
5W6-
400 60 80 100 12* 1400 16 18M 20W 2200 2400
ra
VISIBLE NEAR I-R
FIGURE 6.1 The Major Couponents Of The Solar Spectrum
components. Glass is on the order of 90% opaque to ultra-violet light,
so the portions which are most relevant to the energy flow in buildings
are the visible, and infra-red portions. The infra-red (IR) portion may
be subdivided into the short wave length variety (near-IR) and the long
wave variety (far-IR) . Both infra-red components are invisible to the
human eye. 38.8% of the total solar energy is contained in the visible
portion of the spectrum, with the bulk of the remainder being carried in
the near IR band. Both the visible, and near IR portions, however,
eventually "degrade" into simple, heat energy (far IR) when absorbed by
surfaces, indoors and out. The far-IR, which is derived from both the
visible and the invisible portions of the spectrum, can help reduce
unoccupied heating loads, but is generally a negative contributor due to
increased cooling loads during those working hours that demand cooling.
Heat absorbing glass, as a category, was not examined here because
its performance as a commercial glazing is not significantly better, and
in some climates can be worse than clear glass. The relative heat gain
through most absorptive glass is almost as large as clear glass, and
lower transmission of visible light increases internal gains through a
higher the demand for purchased lighting thereby doubly contributing to
cooling loads. These aspects of absorbing glass generally make its
energy balance very unfavorable within internal-load dominated spaces.
The thermal resistances of both clear and tinted glass are the same (the
identical values for conduction gains and losses illustrate their common
U value) so no savings can be made in the conductive component of either
heating or cooling loads resulting from ambient temperature
differentials. The relative solar heat gains of clear and tinted glass
are shown in figure 6.2 for both summer and winter conditions. The
higher sum of the convective and radiative components for tinted glass
results from its additional absorption heating during the daytime. The
hours of maximum heat gain and the hours of maximum internal gain, due
to the occupancy schedule, are generally coincident. The portion of the
visible spectrum which is converted to heat within the glass can become
a double deficit when it causes a demand for auxilliary lighting.
Electric lights will contribute at least 5.1 Btu (1.5 watts) per square
foot of illuminated floor to the internal gain schedule, even in very
carefully organized energy conserving designs. The category of tinted
glass, therefore, has not been specifically examined in this study, but
it is reasonable to assume that the total load performance of any
analyzed glazing compared with tinted glass can be roughly estimated by
its comparison to clear glass.
SUMMERowr T 970o 7',r #75*'F
24 7
20/
WINTERTor - 25'1 T,, w 70'F
S7
2 /7
239
2/67
- 52
/ 6 7
TRANSM1.55iONAND REFLECT/ON
CCNVGCTION AND
TNHERMAL RADIATiON
CONOUC7ON
2417
96%/ 4A/N
qz/
38/
68% 'VA/N
227/07
73
2* /732/3
-NE5AT AGSC0PI-1- 4f/%-qAlcI;4S
75
52
w7
24f
%W~4
-J19%4AIN
FIGURE 6.2 Solar Heat Gains Thru Different Types Of Glass(from The Solar HomeBook, Aderson & Riordan, Brick House, Anover Ma)
97% 4A/N - C1.5AR lLA-
107
q7
-52
/02
75
2q
-52
V7
58% 4AIN - REFLECT/N4-A55
Figure 6.2 also illustrates the relative solar heat gains for the
second base case category: reflecting glass. This traditional type of
reflectorized glass is a "broad spectrum" reflector which does not
distinguish between the visible and near-IR bands of the spectrum as the
fixed "selective transmitters" described below do. Again, there is no
noticeable difference in the conductive gain and loss relative to clear
glass. In addition, the combined convective and radiative components of
the total heat gain are significantly higher than clear glass due to the
extra absorption heating even in extremely reflective glass. But the
great increase in the reflected ccmponent, relative to clear glass,
produces a significant savings in terms of total heat gain. The
similarity in U values (shown by the conduction losses under winter
conditions) between reflective and clear glass is due to the clear
protective overcoat applied directly to the reflective layer to prevent
tarnishing. This overcoat raises the otherwise low emissivity of the
reflective coating to nearly that of clear glass leaving the U value
pp.516-5231. However, the beam component, which provides the greatest
part of the variability in solar gains, might be quite effectively
controlled by such devices throughout most temperate climates. Also,
since well designed shading devices are capable of shading twice their
own area in window below , the unit area savings could significantly
increase at all the simulation sites. Furthermore, the fact that such
devices are easily isolable thermally from the weather wall of the
building gives a greater degree of flexibility to the types of compounds
which may effectively be used.
The entire range of qualitative effects from switchability,
finally, deserves further attention and study. This analysis has made
no attempt to truely evaluate these issues, and the potentially great
positive affect of increased window area may in fact improve the market
potential of such glazings for the sake of more comfortable and
attractive working conditions. The qualitative issues which appear most
important revolve around the value of the extra natural light which can
be admitted by switchable glazings, under dim conditions without great
penalties from increased cooling loads under average conditions. Under
extreme brightness,however, the "deep" switching capability which makes
the best quantitative showing under the assumed conditions, may see a
diminished value due to the potential "gloom" of too little visible
transmission. Further work, therefore, on the psychological threasholds
regarding the reduction in visible light of various wave lengths is a
critical aspect of effective window design. This aspect of selective
transmission, finally, is important to both switchable and
non-switchable glazing designs if occupant comfort is held to be of
issue in their application.
92
APPENDIX A
RECCMMENDED AVERAGE MONTHLY DECLINATION
For the Average Day of the Monthn for ith
Day of Month' Date n, Day of Year'
174775
105135162
198228258
288318334
6, Declination
-20.9-13.0
-2.4
9.418.823.1
21.213.52.2
-9.6-18.9-23.0
* The average day is that day which has the extraterrestrial radiation closest tothe average for the month. See Section 1.8.b These do not account for leap year; values of a from March onward for leapyears can be corrected by adding 1. Declination values will also shift slightly.
Rocn1e i Average Day for Each Mouth and Values of a by Monds[from Klei (1976)]
Month
JanuaryFebruaryMarch
AprilMayJune
JulyAugustSeptember
OctoberNovemberDecember
i31 + i59 + i
90+ i120 + i151 + i
181 + i
212 + i243 + i
273 + i304 + i334 + i
94
APPENDIX B
ASSUMED DIRECT-DIFFUSE SPLITS FOR HORIZONTAAL CORRECTION OF IT
10 'THIS PROGRAM CALCULATES HOURLY SOLAR GAIN PER SQ.FT. OF RECEIVINGSURFACE AT ANY TILT & AZIMUTH
20 DEF FNARCCOS (Y)=-ATN (Y/SQR(-Y*Y+1))+1.570830 PI=3.141592740 RAD=57.295850 TILT=9060 AZIMUTH=0070 GREFLECT=.380 READ CITY$, LATD90 FOR MNTH=1 TO 12100 READ ITIMIKDA110 'DA=RECOMMENDED AVERAGE DAY OF THE MONTH FROM APPENDIX A120 DECD=23.45*SIN(.01721418*(284+DA))130 DECR=DECD/RAD140 LATR=LATD/RAD150 TILTR=TILT/RAD160 AZIMUTHR=AZIMUTH/RAD170 ALSD=IT*PI/(2*IM)180 ASR=12-(ALSD/2)190 ASS=12+(ALSD/2)200 FOR SIMDAY=1 TO 7210 READ CLRNS220 GOSUB 330230 FOR HOUR=1 TO 24240 IF HR<FIX(ASR) OR HR>FIX(ASS) THEN QSH=0:GOTO 260 ELSE GOSUB 430250 GOSUB 580260 NEXT HOUR270 NEXT SIMDAY280 NEXT MNTH290 END300 '310 'THIS SUBROUTINE SETS THE DAILY AMPLITUDE & HOUR OF CLOUDY FRONT320 '330 CIM=IM*CLRNS*(1+(IK*SIN(PI*CLRNS)))340 CFIM=IM*CLRNS* (1- (IK*4*SIN (PI*CLRNS)))350 IF IK>0 AND CLRNS<.9 AND CLRNS >.2 THEN CFHNGL
360 IF CFHNGL>1 THEN CFHNGL=1370 IF CFHNGL THEN GOTO 380 ELSE GOTO 390380 IF MORNFRNT THEN FHASR+((FNARCCOS(CFHNGL))*(ALSD/PI)) ELSE
FH=ASS- ( (FNARCCOS (CFHNGL) )* (ALSD/PI))390 RETURN400 '410 'THIS SUBROUTINE CALCULATES THE HOURLY HORIZONTAL INCIDENT SOLAR
ENERGY (QSH)420 '430 IF FH AND HR<FH AND MORNFRNT=1 THEN CIM=IM
113
440 IF FH AND HR<FH AND MORNFRNT=0 THEN CIM=CFIM450 IF FH AND HR<FH AND HR+1FH AND MORNFRNT=0 THEN
CIM=(FH-HR)*IM+(HR+1-FH)*CFIM460 IF FH AND HR<FH AND HR+1>FH AND MORNFRNT=0 THEN
CIM=(FH-HR)*CFIM+(HR+1-FH)*IM470 IF FH AND HR>FH AND MORNFRNT=1 THEN CIM=CFIM:FH=O480 IF FH AND HR>FH AND MORNFRNT=0 THEN CIM=IM:FH=0490 IF HR>ASR AND HR+1>ASR THEN 520 ELSE 500500 IF HR<ASS AND HR+1>ASS THEN 530 ELSE 510510 IF HR>ASR AND HR<ASS THEN 520 ELSE RETURN520 QSH=(-CIM*(COS((HR+1-ASR)*PI/ALSD))+CIM)*ALSD/PI:RETURN530 QSH=CIM+CIM*COS ((HR-ASR) *PI/ALSD) ) *ALSD/PI: RETURN540 QSH= (-CIM*CCS ( (HR+1-ASR) PI/ALSD) ) +CIM*COS ( (HR-ASR)
*PI/ALSD))*ALSD/PI:RETURN550 '560 'THIS SUBROUTINE CALCULATES HOURLY INCIDENT SOLAR ENERGY (QSI) ON
THE TILTED SURFACE570 '580 IF HR<ASR AND HR+1>ASR THEN W1=(ASR-12)*.2618 ELSE IF HR>ASR AND
HR<ASS THEN W1=(HR-12)*.2618590 IF HR+1<ASS THEN W2=(HR-11)*.2618 ELSE IF HR+1>ASS THEN
- SIN (Wl))+((W2-Wl) *SIN (LATR)*SIN (DECR)))650 KT=QSH/I0660 IF KT<0 THEN IDI=1670 IF KT>0 AND KT<.35 THEN IDI=1-.249*KT680 IF KT .35 AND KT<.75 THEN IDI=1.557-1.84*KT690 IF KT .75 AND KT<.9 THEN IDI=.177700 IF KT>.9 THEN IF CZNGL<THEN IDI=1 ELSE IF CZNGL>.12 AND CZNGL<.42
THEN IDI=.15710 ID=IDI*QSH: IB=QSH-ID720 QSI=IB*RB+ID*( (1+COS(TILTR) )/2)+(IB+ID)*GREFLECT*( (1-COS(TILTR) )/2)730 RETURN
114
APPENDIX E
ENERGY BALANCE EQUATIONS
NODAL EQUATIONS
UAW(TA-Tout) + H(TA-TR) CA(TAI-TA) + 0.40SSOL
UAR(TR-TSI) + H(TR-Ta) a CR(TRI-TR) + 0.60SSOL
UAS(TS1-TS2) + UAR(TS1-TR) = O.5CSCTS11-TS1)
UAS(TS2-TS1) = O.5CS(TS21-TS2)
NODAL DIAGRAM
TERMS:
TM = Outdoor air temperature
UAW - Total conductance of Weather Wall and infiltration Btu/hr 07
TA i = Indoor A i r Temperature Last Hour OF
TA a Indoor Air Temperature in Current Hour OF
CA = Heat Capacity of Air (for sheetrock and furniture) Btu/hr OF
TR 1 = Rug Temoerature Last Hour OF
TR = Rug Temperature Current Hour 0F
UAR = Total Conductance of Rug (Rug area x U rug) Btu/hr OF
H a Total Surface Film Conductance of Rug (Rug area x I rug) BTU/hr OF
CR = Heat Capacity of Rug Btu/OF
1311 3 Temperature of top 2" of Slab Last Hour OF
TS 1 = Temperature of top 2" of Slab Current Hour OF
1S 21 a Temperature of bottom 2" of Slab Last Hour OF
13 2 - Temperature of bottom 2" of S lab Current Hour OF
UAS = Total Conductance of Slab (Slab area x U Slab) etu/hr OF
CAS a Heat Capacity of Slab Btu/OF
QSM= Total Hourly Solar Heat Gain Btu/hr
115
SOLUTION:
A. From Equation #1 for Air Temperature in Current Hour (TA):
HEAT COOL LITE TOTAL ANUAL SUMMER PEAK KW/YR TOTALCITY LOAD LOAD LOAD LOAD PEAK MO DY HR PEAK MO DY HR AS EOUIVALNT EOUIVAKWH KWH KWN KUM KU K KWH KWN------------------------K---- ------------ ---- ------------------------------
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137
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