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/NBS building science series TA435 .U58 V71;1975 C.I NBS-PUB-C 1974 NBS BUILDING SCIENCE SERIES 71

U.S. DEPARTMENT OF COMMERCE / National Bureau of Standards

MUMmil: I

III

A Proposed Concept

for Determining the Need for

Air Conditioning for Buildings

Based on Building Thermal Response

and Human Comfort
The Buildinji; Science Series

The Building Scieiu-n Series disseminates technical information developed at the National Bureau of Standards on

iiuildinfi materials, components, systems, and whole structures. The Series presents research results, test methods, and performance criteria related to the structural and environmental functions and the durability and safety characteristics of huilding elements and systems. These publications, similar in style and content to the NBS Building Materials and Structures Reports (1938-59),

are directed toward the manufacturing, design, construction, and research segments of the building industry, standards organizations, and officials responsible for building codes. The material for this Series originates principally in the Center for Building Technology of the NBS Institute

for Applied Technology. The publications are divided into three general groups: Building Systems and Processes;

Health, Safety and Comfort; and Structures and Materials. For further information regarding these publications

please contact the .Scientific and Professional Liaison Section, Center for Building Technology, Institute for Applied Technology, National Bureau of Standards, Washington, D.C. 20234.

ISee mailing list announcement on last page j
LIBBJiJiT A Proposed Concept for Determining the Need

for Air Conditioning for Buildings Based on

Building Thermal Response and Human Comfort

J. E. Hill, T. Kusuda,

S. T. Liu and F. J. Powell

Institute for Applied Technology

National Bureau of Standards

Washington, D.C. 20234

Sponsored by

The Deprartment of Housing and Urban Development

451 Seventh Street, S.W. Washington, D.C. 20410

U.S. DEPARTMENT OF COMMERCE, Rogers C. B. Morton, Secretary

NATIONAL BUREAU OF STANDARDS, Ernest Ambler, Acting Director

Issued August 1975
Library of Congress Cataloging in Publication Data

United States. National Bureau of Standards. A Proposed Concept {or Determining the Need for Air Conditioning for Buildings Based on Building Thermal Response and Human Comfort.

(National Bureau of Standards Building Science Series: 71) Supt. of Docs. No.: C 13.29/2:71

1. Air Conditioning. 2. Buildings—Thermal Properties. I. Hill, .lames Edward, 1942- II. Title: A Proposed Concept for Determining the Need for Air Conditioning for Buildings . . . III. Series: I'nited States. National Bureau of Standards. Building Science Series: 71. TA43.5.U58 No. 71 [TH7f)871 690'08s [697.9'3121 75-619194

National Bureau of Standards Building Science Series 71

Nat. Bur. Stand. (U.S.), Bldg. Sei. Ser. 71,155 pages (Aug. 1975) CODEN: BSSNBV

U.S. GOVERNMENT PRINTING OFFICE

WASHINGTON: 1975

For sale by tlie Superintendent of Documents. U.S. Government Printing Office, Washington, D.C. 20402 (Order by SO Catalog No. C13.29/2:71). Price $2.25 . (Add 25 percent additional for other than U.S. mailing).
Table of Contents

Page

1. Introduction 1

2. Proposed Concept for Air Conditioning Criteria

.

. 4

3. Calculation of Indoor Space Conditions by Building Thermal Simulation. . . 5

4. Classification of Buildings According to Their Thermal Response

Characteristics 6

5. The Predicted Indoor Habitability Index 11

6. Preliminary Calculations and Analysis for Air Conditioning Criteria .... 13

7. Conclusions and Recommendations 19

8 . References • 21

9 . Appendix A - Derivation of the Equations to Calculate the Mean

Radiant Temperature Within NBSLD la

10. Appendix B - A Review of Comfort and Physiological Indices lb

11. Appendix C - Discussion of Regulatory Sweating Model Ic

ili

A Proposed Concept for Determining the Need for Air

Conditioning for Buildings Based on Building Thermal Response and Human Comfort

James E. Hill, Tamami Kusuda, Stanley,!. Liu, Frank J. Powell

Center for Building Technology

Institute for Applied Technology

National Bureau of Standards

Washington, D.C. 20234

Abstract

Determining the need for air conditioning can be based on a wide variety of factors.

To date, the only criteria that have been written and can be referenced are those of several

federal organizations and many are not really criteria in the true sense of the word. They are guidelines to be used in the determination of fund allocation; in other words, provisions

are made to air condition federal facilities in specific geographical locations if pertinent

weather characteristics of that locality meet certain requirements. This paper presents the

concept that a true criteria can be established based both on weather characteristics of

the locality as well as characteristics of the building or structure under consideration.

The paper gives the details of a study showing the feasibility of such a scheme. A

simulation was made of two proposed residences in several geographical localities. For the

simulation, actual hour-by-hour weather data was used in conjunction with a sophisticated

computer program. The results revealed for the non air-conditioned spaces, the extent and

duration of undesirable indoor conditions based upon generally accepted comfort indices. The

concept of a new "comfort" or "discomfort" index called Predicted Indoor Habitability Index

(PIHI) is introduced. The authors indicate the way in which a criterion could be established

that would be in the form of tables, indicating for a given specified building and geographical

locality, whether mechanical cooling should or should not be installed.

Key Words: Air conditioning criteria; building thermal response; comfort indices; human

comfort; predicted indoor habitability index

1. Introduction

At the present time, several United States government agencies make the decision to air

condition single family or multifamily dwellings based on cost and general location of the

housing unit (i.e., northern or southern part of the country). The United States Air Force,

for example, specifies in their Manual 88-8 that if family housing is to be located in a region where the wet-bulb temperature is above 67 °F for 1000 hours or more or the dry-bulb

temperature is above 80°F for 400 hours or more during the hottest six consecutive months

of the year, consideration should be given to installing mechanical cooling [1].* Criteria

similar to this were adopted by the Department of Housing and Urban Development for their

Operation BREAKTHROUGH Program [2]. Using this as the basis for the decision to provide air

conditioning is clear cut and definitive; however, it is felt that other factors besides

weather should be considered. These include the thermal performance of the enclosing

structure and the range of indoor thermal conditions under which people can remain reasonably comfortable. Other factors that are considered "secondary" and have not been recommended

for inclusion here involve such things as the surrounding acoustical environment and human

preferences for visual communication with the surroundings.

One of the most important items that govern the indoor environment is the "thermal

performance" of the enclosing structure. J. F. van Straaten of the Building Research In- stitute of South Africa discusses in his recent book Thermal Performance of Buildings [3] the way different structures respond when subjected to periodically varying solar conditions

* The number in the brackets refers to references at end of report.

1
and environmental temperatures. The overall heat transfer coefficient for wall, floor

or ceiling which gives a direct measure of the resistance to heat flow under steady-state

conditions, is not the sole indicator of the heat flow to the inside environment when

unsteady-flow conditions exist. The mass of the wall, floor and ceiling, which governs the

energy storage capacity, is also a pertinent parameter to be considered.

Several studies are summarized in the van Straaten book that help to illustrate the

complex interaction between the building and the environment. Several four-room singlestory structures of approximately 500 ft^ (46 m^) of floor area were built in both Pretoria

and Durban, South Africa. These unoccupied, non-air conditioned buildings were instrumented

to observe the indoor environmental parameters as a function of time. The climate in

Pretoria can best be described as warm and dry with large daily variations in solar radiation and outdoor air temperature (a daily range exceeding 20°F (11°C)). Under these conditions,

massive brick buildings proved to be superior to lighter-weight buildings in minimizing the

daily variation of the indoor temperature. The reason is that the "time lag" associated

with the massive structure was such that t;he indoor environment remained cool during the hot

part of the day (for example, a 79°F (26.1°C) indoor temperature compared with an 84°F

(28.9°C) outdoor temperature at noon) and also remained wajrm during the night (74°F (23.3°C)

compared with 61°F (16.1°C) outside at 5:00 a.m.). The lighter wood structures with essentially no "time lag" allowed the indoor temperature to increase to undesirable limits during

the day (for example, 93°F (33.9°C) inside compared with 87°F (30.5°C) outside at 2:00 p.m.)

and to decrease to correspondingly low levels during the night (a 62 °F (16.7°C) indoor

temperature compared with a 61°F (16.1°C) outdoor temperature at 5:00 a.m.).

The conclusions that van Straaten made from the experiments in Durban were just the opposite

of those in Pretoria. The climate is generally warm but humid which is also accompanied by

large solar radiation intensities and outdoor temperature variations smaller than those in

Pretoria (for example, a daily outdoor temperature range of less than 10°F (5.5°C)). The

massive buildings proved to be a distinct disadvantage. The walls could not cool down during

the night enough to provide comfortable temperatures in the enclosures during the day.

Other interesting results of van Straaten 's research include the improvement in

performance of the lightweight structures in warm and dry climates by the addition of con- crete floors and by painting the exterior of the structure white.

During 1971 and 1972, an experiment was conducted at the National Bureau of Standards

where measurements of the dynamic heat transfer in an experimental masonry building were

made in a large environmental chamber [4]. The structure was a one-room house 20 ft (6.1 m)

wide, and 10 ft (3 m) high with walls of solid concrete block (8 in. (0.2 m) thick) and a flat roof made of reinforced precast concrete slabs (4 in. (0.1 m) thick). The building was exposed to a diurnal temperature cycle having a range of 60°F (33.4°C) extending from 40°F

(4.4°C) to 100°F (37.8°C) for a series of tests where changes were made in the amount and

location of insulation, and the amount of indoor mass. Tests were conducted where internal

heating was used to maintain the indoor air temperature between specific limits as well as tests where no internal heating was supplied and the indoor air temperature was allowed to float.

For the floating tests, it was found that the combination of mass in the walls and roof

facing the interior with the insulation placed on the outer surfaces of the building was

very effective in reducing and controlling the variation of the indoor air temperature. Placing 2 in. (0.051 m) of commercial acpanded polystyrene insulation on the inside building surface

reduced the variation of the inside air temperature from 10.5''F (3.1°C) (for the uninsulated

case) to 5.1°F (3.1° C). Furthermore, when this insulation was placed on the outside surface

of the building, the variation in the inside air temperature was reduced to 2°F (l.l'C).

It should be apparent from the types of investigations cited above that climate as well

as building construction plays a significant role in determining a need for air conditioning.

Obviously, another factor to be considered in establishing air conditioning criteria is

the range of indoor thermal conditions under which people remain comfortable or not overly

uncomfortable. The American Society of Heating, Refrigerating and Air-Conditioning Engineers'

Standard 55-74 [5] is very specific in its stipulation of thermal comfort conditions. It states in part that at the center of and 2.0 ft (0.61 m) from each exposed wall and at the center of the room, the following should be met at all times:

2
1. When a dry-bulb temperature (DBT) equals the mean radiant temperature (MRT)

,

the dry-bulb temperature equals the -adjusted dry-bulb temperature

(ADBT = DBT + MRT ) and the values measured within the occupied zone shall

.

, 2

' be on the boundary or within the "comfort envelope." The "comfort envelope"

is defined as a quadrangle with the following corner coordinates:

ADBT = 71.5 and 77.6°F (21.9 and 25.3°C) at 14 mm Hg

(1.87 X 103 N/m2) vapor pi;essure and ADBT = 72.6 and

79.7°F (22.6 and 26.5°C) at 5 mm Hg (0.667 x 10^ N/m2)

.

2. The water vapor pressdre in the occupied zone shall be at or between 5.0

and 14.0 mm Hg (1.87 x 10^ and 0.667 x 10^ N/m^) , These conditions

. correspond approximately to 20 and 65 percent relative humidity.

3. When the mean radiant temperature in the occupied zone differs from

the dry -bulb temperature, the dry-bulb temperature shall be reduced

by one degree for each degree mean radiant temperature elevation above

air temperature and vice versa.

4. The air velocity in the occupied zone shall be 70 fpm (0.35 m/s) or less at any time.

In addition, it also states the allowable limits of oscillation in the temperature and

relative humidity.

One might conclude based o^i this Standard then that if the indoor thermal environment

of non-air conditioned buildings falls into this condition "most of the time", the building

need not have mechanical cooling even if it is located in an area where climatic criteria

might indicate a need for it. Obviously, the biggest unknown factor needed to be established

in a study such as this, is how to quantify the phrase "most of the time" in the preceding

sentence. In addition, as will be pointed out later in this paper, a better evaluation of

the tolerance of people to varying indoor conditions above and below the recommended steady

state domfort conditions is needed.

It should also be noted that the concept of determining a need for air conditioning

based on building thermal performance is not new. Givoni in his latest book [6] introduces

a "Building Bioclimatic Chart". His concept is based on the "Bioclimatic Chart", introduced

earlier by Olgay [7]. Givoni 's chart is essentially a psychrometric chart on which he has

drawn an enclosed region indicating thermal comfort conditions. Frdm experience and study,

three additional regions have been drawn: one to indicate the range of outdoor conditions

where choice of building materials and design features (large thermal resistance, large

thermal mass, etc.) make comfort conditions inside attainable without air conditioning; a

- second region to indicate the outdoor conditions where efficient ventilation through the

structure could result in comfort conditions; and a last region showing the range of outdoor

conditions where mechanical cooling would be required.

Loudon [8] describes a method of calculating summertime indoor temperatures based on climatic and building factors which was developed at the Building Research Station in England

In addition, experimental data is presented showing that there was a strong correlation

between the predicted peak temperatures in occupied schools and office buildings and users' comments on overheating in the summer, obtained from social surveys. He concludes, "... if

temperatures are calculated on assumptions which have been set out, criteria can be set which

enable one to decide in advance whether a given design of office or school is likely to be

thermally comfortable". This is precisely the basis on which the study described in this

paper was undertaken.

The present paper shows how a sophisticated building simulation computer program can be used in conjunction with actual weather data to predict the time-varying indoor thermal

conditions. In addition, it is conceptually shown how such results could be used for establishing air conditioning criteria.

3
2. Proposed Concept of Air Conditioning Criteria

One of the ways to determine if a building should have mechanical cooling is to construct

it without cooling equipment, determine if the indoor environment is acceptable, and if not,

install the equipment. This is, of course, not feasible in most cases. However, the particular concept presented here is similar in many respects. By combining the pertinent weather

parameters with those of the building under consideration, a simulation model predicts what

would occur without mechanical cooling. The conditions are then compared with accepted

Indoor comfort data to determine whether the space should or should not be conditioned.

Anquez, et . al. of the Centre Scientifique et Technique du Batiment (CSTB) in France,

published in 1965 the results of a study entitled "The Protection of Glazed Windows from

Solar Radiation" [9]. Their objective was to develop standards for devices that are used

to protect windows from solar radiation in non-air conditioned buildings of average and low

thermal inertia. Their procedure was to divide France into four climatic regions and then

through the use of mathematical simulations on "typical" buildings of specified dimensions,

exposure of glazed areas, thermal inertia, and degree of ventilation, determine to what

extent shading devices could be used to insure the maintenance of a comfortable indoor

temperature during an average summer. The results were published in the form of tables, one

of which is shown in Table 1. Someone considering a specific design wh-o could locate his

building at the proper place in this table, could tell at a glance what type of window shading, if any, could be used to insure comfortable conditions in the summer^.

The determination of air conditioning criteria by the present authors has not been carried

to the point of publishing tables such as the one cited from the French study. However, it

is felt that the ultimate goal of this project, which has been funded by the Department of

Housing and Urban Development (HUD) , would be to publish a document containing information

analogous to the table. For a given climatic region of the United States and given building

(characteristized by the pertinent parameters) , one could tell during the design phase whether

mechanical cooling should or should not be installed.

The manner in which a computer program could be used for determining a need for air

conditioning is depicted in Figure 1. Weather data from a specific climatic zone and adequate

specifications of a building would be combined in the simulation model, the output of which

would be the space conditions. The frequency and duration of the various indoor parameters

would then be compared with a suitable indoor comfort index (identified in this paper as the

Predicted Indoor Habitability Index (PIHI)) to determine whether the space should or should

not be conditioned.

Before the project can successfully be completed, the following is required:

1. A computer program which has been proven accurate for predicting indoor

temperatures

,

2. A division of the United States into climatic zones and a knowledge of

representative weather parameters from each zone,

3. A classification of buildings according to their thermal response, and

4. A clear definition of the Predicted Indoor Habitability Index (PIHI) as introduced in this paper.

Section 3. presents a description of the computer program used in this study and which

adequately satisfies requirement 1. above.

Technical Committee 4.2 of the American Society of Heating, Refrigerating and AirConditioning Engineers is in the process of developing "typical weather data" for the

purpose of computing building energy requirements. For the first phase of the study re- ported in this paper, hour-by-hour weather conditions obtained from the National Climatic

Center in Asheville, North Carolina were used for the specific localities studied.

^The meaning of the "solar factor" referred to in Table 1 has not been explained in the

present paper. It is felt not necessary for the purpose of the illustration.

4
Section 4. of this paper describes the analysis that has been done to date on the

classification of buildings.

Section 5. describes the authors' concept of a Predicted Indoor Habitability Index and

Appendix B contains a review of various comfort and heat stress indices that could be con- sidered now as a basis for PIHI.

Section 6, describes what is called a feasibility analysis that has been done to give

an indication of how successful the project might ultimately be.

3. Calculation of Indoor Space Conditions by

Building Thermal Simulation

Numerous papers have been published and calculation manuals prepared in the area of

heating/cooling load determination. Very few of these, however, have dealt with the indoor

temperature estimates for the condition where air conditioning is non-existent or inadequate.

Room temperature prediction is, on the other hand, very actively studied in Europe, Japan,

Israel, and India where mechanical cooling is still very expensive for the majority of

dwellings and consequently a determination of the basic need for air conditioning is very

important

.

The heat transfer calculations for room temperature prediction are similar to the heating/

cooling load calculations; however, the former are somewhat more complex than the latter

because they require exact heat balance calculations for the room air, surrounding walls and

infiltrating outdoor air. Since the major importance is the hour by hour room temperature

profile, it is necessary to account for the transient heat conduction and thermal storage

in the building and internal mass

.

In order to determine the temperature and humidity in non-air conditioned rooms responding

to randomly fluctuating outdoor climatic conditions, a computer program to simulate hourly

performance of building heat gain and heat storage has been developed at the National Bureau

of Standards [10, 11, 12]. The program is called "NBSLD" and consists of various subroutines

for calculating heat gains, which are similar to those recommended by the ASHRAE Task Group

on Energy Requirements [13]. One major extension of the program beyond the recommended

ASHRAE TG subroutines is a routine called RMTMP, which solves for room air temperature through

the use of a series of simultaneous heat balance equations. The details of this routine is

given in reference [12]

.

Figure 2 depicts the overall calculation sequence of NBSLD. Shown in the dash lined

boxes are input data to be supplied where as those in solid lined boxes indicated calculations to be performed. The cycle indicators show the iteration cycles for the number of

buildings, the number of rooms in a given building and the number of days for which the calculations are performed. Table 2 lists all the pertinent building data required for the

calculations. More specific identification of the exact way in which the input data is

prepared is described in reference [12].

This particular computer simulation has been verified by experimental work on two separate research projects at NBS [4, lA] . The first study [4] involved a small masonry

building and the experiment was described previously in this paper. Figure 3 is a typical

test result taken from reference [4] and shows to what degree NBSLD was able to account for

the transient conduction occurring in the thick masonry walls (to within + 1.0°F (0.55°C)

for outdoor temperature variations from 45 to 100°F (7 to 38°C) and to compute the indoor

temperature fluctuation. In the latter study [14], a more realistic living unit was used,

namely a four-bedroom, lightweight house that was completely furnished and had the activity

of a six-member family simulated within. The house was also tested inside the environmental

chamber where the outdoor conditions were simulated and precisely controlled.

5
In order to evaluate indoor conditions for human comfort or physiological stress, it is

desirable that the indoor air velocity be estimated. The indoor air velocity is, however,

believed to vary depending upon the air leakage rate, ventilation rate, thermal gradient of

the room, basic design of the room, and any local air moving device such as a portable fan.

According to Givoni [6] ,' the indoor air motion could vary between 5 to 60% of outdoor wind

velocity depending upon the nature of the air passage resistance through the room.

Since the information available for predicting indoor air velocity as function of

temperature distribution and wind velocity is very scanty, NBSLD has not been designed to calculate this parameter. It has been assumed in the present study that the indoor air

velocity would be less than 20 ft per minute (0.1 m/sec). This assumption should yield, an upper-bound value of comfort index or physiological index' for summer conditions and is

therefore safer to use than to overestimate the cooling due to elevated air velocities.

The form of NBSLD available at the start of this study did not allow for the calculation

of mean radiant temperature (MRT) . Since the room temperature calculation routine (RMTMP)

does calculate the temperature of all the interior surfaces, it was very simple matter to modify the program to calculate this quantity. Then MRT was used as part of the input data

to the calculation of the appropriate physiological or comfort indices that were used in this

study. Appendix A describes the equations that were inserted into the, program to calculate

MRT.

Classification of Buildings According to Their Thermal Response Characteristics

This part of the paper describes a method for classifying kinds of residential buildings

in relation to their thermal behavior.

Construction data were taken from the proposals of 18 of the 22 participating Housing

System Producers in the HUD Operation BREAKTHROUGH Program. Since the contractors involved

in that program represented a cross section of the Housing System Producers in the building

industry, it was felt that data contained in their proposals provided meaningful information

about the practice, and the state of the art, in housing design. Consequently, it was felt

that a realistic classification procedure could be established relative to the typical

residential building based upon thermal parameters for composite structural components.

4.1 Type of Building Data Compiled

From the drawings and specifications submitted by the Housing System Producers in the

Operation BREAKTHROUGH Program, two types of data were collected. The first concerned the

method of construction and materials used for the exterior enclosures and interior partitions of a building, and the associated thermophysical property data of the materials.

Pertinent thermal performance paramet ers associated with the structural components such as the U-value, weight per unit area, thermal mass, and the thermal time constant were then

computed. Their computation, physical meaning and usefulness will be discussed later in

this section. The second type of data was of a geometric nature and involved the following:

1. Total floor area of a dwelling unit.

2. Floor area for each of the rooms in a dwelling unit.

3. Type of walls and openings, windows, doors, and their areas for each of the rooms in a unit

.

4. Total glass area of a dwelling unit.

5. Crack length of the windows and doors. These data are required in order

to know air movement and infiltration characteristics.

6. Shading coefficient for the glazed area.

6
4.2 Method of Data Presentation

Data collected from the drawings and specifications were processed by the NBS UNIVAC

1108 computer and printed out in the unified manner in tabular form. Two types of tables were developed, corresponding to the two types of data discussed in 4.1. Typical examples

are given here as Tables 3 to 5.

Table 3 gives the building construction and material data for one of the dwellings of one of the 18 Housing System Producers surveyed. This table contains a typical layer by

layer description and the thermophysical properties of the materials used in the construction

of the structural components (exterior walls, interior partition, party wall, floor/ceiling,

roof/ceiling, ground floor, basement wall, basement floor, window). The order of the layers

are from the outside of a room toward the inside for the side walls and from top to bottom

for roofs and floor/ceilings. The thermal property values were taken from the contractor's

drawings and specif! cations and from the 1972 ASHRAE Handbook of Fundamentals [15] . Occasionally data from the specific heat (Cp) of certain materials were not available, and a value

of .20 Btu/(lb-°F) (.013 cal/(g'°C)) was assumed. Since the value of Cp does not vary

much for most of the building materials (on the order of .15 (.0098) to .40 (.026) with a major portian of the materials in the lower range of the spectrum), the value of .20 (.013) was chosen. The surface air film resistance values were taken from the ASHRAE Handbook of

Fundamentals also and based on the summer design conditions since the overall project was established for the purpose of determining summer air conditioning criteria.

Table 4 gives the four relevant parameters associated with and affecting the thermal

performance of a building. They were computed from the data given in Table 3. A brief

description follows

:

1. U-value: The U-value is the overall heat transfer coefficient including the

surface air film resistance (at 7.5 mph (3.4 m/s) wind outside and still

air inside) under steady-state conditions. This is the major factor used by

designers in estimating the cooling load of a building. As pointed out previously, under unsteady-state conditions the U-value is no longer the only

controlling factor in heat flow through walls since it does not take into

account the energy storage effect of the walls. However, it does give an indication of the amount of resistance the wall offers to heat flow and,

therefore, acts as one of the parameters in determining the overall heat

transfer through the walls.

2. Thermal Mass, pC L: The thermal mass is a counterpart of the U-value

and gives an indication of the energy storage capacity of the walls.

It is computed from the following equation:

where p^, C^^, are the density, specific heat, and thickness,

respectively, of the ith layer in a multilayer wall. N is the total

number in the wall.

3. Weight per unit surface area, pL: Because of the small variations in the

specific heat for most building materials, the energy storage capacity of

a wall is almost directly proportional to the weight per unit surface area

of the wall. This parameter is, therefore, closely related to the thermal

mass in that a knowledge of the values of the specific heat, which are not available for certain materials, is not required. The weight per unit area of a wall is computed by

N

(1)

N pL = E (2)

i=l

7
4. Thermal Time Constant: The thermal time constant is a function of the

thermal dif fusivities of the layers in a multilayer wall and is defined ' [6] as the heat stored per unit of heat transmitted. It is, therefore,

a combination of the thermal mass ai)d the thermal resistance of the wall.

It is derived on the basis of the' analogy between the heat flow represented

by a thermal circuit and the time constant of a R-C electrical circuit,

and is given by Givoni [6]':

Thermal Time Constant = Z (t^)

i where

Ti = (R^^ + Li/ki + ... + Li/2ki) . (L.PiCp.) (3)

where R is the resistance of the surface air film and is the thermal

OS conductivity of the material of the ith layer. In the case of an air

space, the resistance of the air space is substituted for L-j^/k-j^.

Similar to the thermal diffusivity of a homogeneous single layer wall,

the thermal time constant is a measure of the thermal damping capacity

of a multilayer wall on the amplitude and time lag of the inner surface

temperature, or indoor air temperature, with respect to a periodically

varying outdoor temperature. It should be pointed out that the thermal

time constant given by equation (3) also takes into account the order

the layers of materials are arranged. A change in the order of the

arrangement will change the rate of heat flow through the wall under

transient conditions. This is because the outside surface temperatures

of> the walls with different orders of arrangement in their layers will

be different during the transient states. For example, during the day,

the outside surface temperature of a wall with an insulation layer next

to the external surface layer will be higher than a wall constructed of

the same layers of materials but with the insulation layer placed further

away from the external surface layer. The former construction will

result in more heat being transferred back to the external environment

by convection and radiation, and consequently less heat being transferred

into the interior space. It is noted that this phenomenon is not accounted for by either the U-value or the thermal mass where the order

of arrangement of the layers is immaterial.

Table 5 gives the geometrical data for one of 28 dwelling units ranging from 1-bedroom

to 4-bedrooms. The 28 units were chosen randomly from six of the 22 Housing System Producers.

The survey of the 6 Housing System Producers was done for the purpose of obtaining some average values of unit size, floor area, and window area for a normal dwelling unit. The

orientation of the unit is not specified since this is one of the factors that is influenced

by site location, terrain, units group plan, etc. as much as by thermal performance consideration. For a group of attached units (single family attached, multi-family low rise or high rise), the unit at the ends, or corner, of the group was chosen since it has the largest

amount of wall area exposed to the outside environment and consequently results in the most

severe indoor temperature variation, or the largest cooling load, among the group, and re- presents the worst case as far as air conditioning is concerned. Table 5 also gives the

crack lengths of the windows and doors which are required in an air infiltration study. Data

for lighting (as an internal heat source) and furniture (as an internal heat sink) were not available. The data for the shading coefficient on windows were assumed values for regular

sheet glass with light indoor Venetian blinds shading. These data would, of course, be

different values for other types of glass and shading.

Table 6 gives a summary of the different type areas associated with the dwelling, plus

three parameters that can be used for the classification of dwelling units on a geometrical

basis. These three parameters are:

8
1. Floor Area: The floor area represents the total amount of living space

in a dwelling unit and gives an indication of the size of the unit among

the same type of dwellings

.

2. Ratio of Exterior Wall Area to Floor Area: The ratio gives an indication

of the complexity of the shape of the unit. For example, a simple rec- tangular unit will have a lower ratio than a complex geometrically shaped

unit.

3. Ratio of Window Area to Floor Area: This ratio indicates the relative

amount of glass area in a unit which has a direct bearing on the amount

of solar radiation transmitted directly into the interior space.

In general, data contained in Tables 3 to 6 are required by the computer program NBSLD

for indoor temperature or load prediction purposes.

4.3 Analysis of Data and Discussion

A study of all the data compiled in this part of the project indicates the following:

1. Unit Size: The range and average size of the dwelling units in terms of

total ft2 (m^) of floor area are tabulated below:

Total

Min. Max. Units

Area Area Average Used

4-Bedroom

Unit

1065 (98,.9) 1740 (161.6) 1340 (124.5) 11

3-Bedroom

Unit

910 (84..6) 1480 (137.5) 1100 (102.2) 16

2-Bedroom

Unit

700 (65,.0) 1200 (111.5) 905 (84.1) 15

1-Bedroom

Unit

580 (53,.9) 960 (89.2) 735 (68.3) 8

It is noted that the total number of units upon which the average values were based is not statistically significant. However, for the study of

air conditioning criteria where a typical size unit is to be used,

slight variation from the above listed average values would not have

any significant influence on the results.

2. Glass Area: The total glass area in the dwelling units ranged from 10%

to 26% of the total floor area, with an average value of 17% for 50 units

studied. The variation of 10 ~ 26% occurs in both the large size and the

small size units (FHA Minimum Property Standards require 10% minimum for

light). It can, therefore, be said that the size of a dwelling unit has no effect on the relative amount (with respect to floor area) of the

glass in the design of a typical housing unit.

3. Individual Room Size: The variations in the sizes of the major rooms

in a dwelling unit are quite large, and are listed below for reference:

9
Range Average

ft" ft2

(m2) (mh

Living Room 140 - 270 (13.0 -25.1) 200 (18 .6)

Dining Room 95 ~ 125 (8.8 • 11.6) 110 (10 .2)

Kitchen 50 - 150 (4.6 - 13.9) 95 (8. 8)

1st Bedroom 125 ~ 220 (11.6 - 20.4) 165 (15 .3)

2nd Bedroom 100 - 220 (9.3 ~ 20.4) 135 (12 .5)

Other Bedrooms 80 ~ 180 (7.4 ~ 16.7) 115 (10 .7)

Bathroom 35 - 45 (3.3 - 4 .2) 40 (3. 7)

Normally, the larger living rooms were associated with a 3 or 4-bedroom

unit. The lower limits in the above list are controlled by the FHA Minimum Property Standards.

4. U-value! The U-values for the different designs of the walls and roof/

ceiling constructions by the 18 housing system producers were fairly

uniform within each weight class of construction. The ranges and average

values for the exterior wall and the roof/ceiling elements were.

Exterior wall = .062 ~ .178 Btu /(h • ft^-^F) (.352 ~1.01 W/(m2-°C)

average value = .]04 (.59)

Roof/ceiling = .041 ~ .114 Btu/(U • ft^-T) (.233 - .647 W/(m^.°C)

average value = .062 (.35)

In general, for the exterior wall system, the higher than average U-values were associated with the heavy type construction such as concrete wall.

For lightweight construction such as wood frame wall and sandwich panel

wall with various cores and facings, the U-values were all comparable.

Weight per Unit Area: As stated previously, the weight per unit area and the

thermal mass are closely related, having an almost linear relationship

because of the slight variation in the values of the specific heat for

different building materials. This linear relationship is shown in Figure

4. The weight can, therefore, be used to indicate the thermal storage

capacity of a wall or roof/ceiling system. For the 18 Housing System

Producers studied, the ranges of the weight of different building enclosures

were,

Exterior wall: 2.5 - 98 Ib/ft^ (12 ~ 478 kg/m^)

Roof/ceiling: 2.5 - 69 Ib/ft^ (12 - 337 kg/m^)

Floor/ceiling: 4 - 86 Ib/ft^ (20 ~ 420 kg/m^)

Ground floor: 2 ~ 90 lb/ft (10 -439 kg/m^)

2 Party wall: 5 - 72 lb/ft (24 ~ 351 kg/m^)

(including load bearing interior wall)

10
The types of the construction of the building included: wood frame,

sandwich panel with various cores and facings, metal frame, brick wall,

and concrete wall systems. A classification based on the weight of the

exterior wall system is recommended as follows:

Lightweight (wood frame, sandwich panel) : Less than

20 lb/ft2 (98 kg/m2)

Medium weight (wood frame with frace brick, brick,

lightweight concrete) : 20-50 Ib/ft^ (98 ~ 244 kg/m2)

Heavyweight (brick, concrete) : higher than 50 Ib/f t^ (244 kg/m2)

6. Thermal Time Constant: The ranges of values for the different building

enclosures are.

Exterior wall: 3,.2 - 115 h

Roof /ceiling

:

4,.1 - 165 h

Floor/ceiling: 3,,4 - 86 h

Ground floor: 2,.2 - 96 h

Party wall: 6,,2 - 44 h

Interior Partitions: 1.7 -

It can be seen that the ranges of values for the thermal time constant are quite large

and are comparable with the ranges for the weight of the structures. Figures 5 and 6 show

the relation between the thermal time constant and the weight of exterior wall and roof/

ceiling systems, respectively. The large scattering of the data points shows the effect of

the arrangement of the layers of different materials and the placement of insulations and/or

air spaces in a wall system. However, Figures 5 and 6 also show that even though the local

scattering of data points is large, the overall trends of increasing thermal time con- stant with increasing weight is preserved, and the classification of buildings by weight may

be sufficient. For a more refined and accurate classification of buildings, with respect to indoor thermal environment, the thermal time constant might be a better index because of its

close functional resemblance with the thermal diffusivity of a single layer wall. This should

however, be verified by further work, using data on a variety of selected typical residential

units of different design as input to the computer program NBSLD and comparing the results

under identical external environmental conditions at various locations throughout the country.

5. Predicted Indoor Habitability Index

There are approximately fifteen published indices or groups of experimental data that

have been presented to indicate man's comfort or discomfort when subjected to a certain

environment. The majority are experimental in nature (i.e., human subjects have been ex- posed to a specified and controlled environment and asked to describe their feeling or at least have physiological measurements taken on them during the exposure). However, during

the last several years there has been a great deal of interest in describing mathematically

the thermal interaction between man and his environment, thus enabling one to predict what

occurs or how one might feel in given surroundings. Appendix B contains a comprehensive

review of those indices felt to be the most pertinent to this study.

11
The authors of this paper have introduced the concept of Predicted Indoor Habitability

Index (PIHI) for several reasons. It is felt that the decigion to air condition a building

should be based on the fact that the value of certain chosen parameters describing the indoor

environment would exceed a certain level for a specified amount of time during the "air con- ditioning" season unless mechanical cooling were installed. Therefore, it would be desirable

to establish a new scale to satisfy this requirement. For example, a very simple arbitrarily

chosen scale might be: PIHI =0 if the KSU index never exceeds a value of 5 during the summer months (corresponds to slightly warm - see Appendix B)

PIHI =5 if the KSU index exceeds a value of 5 for 5% of the hours during

the summer months

PIHI = 10 if the KSU index exceeds a value of 5 for 10% of the hours

during the summer months

.

However, there are other factors that should also be included in the analysis to establish

PIHI. These include among other things, consideration of the "persistency factor". Certainly

a situation where the indoor environment is "uncomfortable" for long periods of time wouldn't

necessarily be equivalent to one where it was just as uncomfortable for more but shorter

periods of time. In addition, shouldn't consideration be given to the relative level of

"discomfort" that occurs during these periods? An indoor environment where the KSU index was

6 (warm) for a certain period of time wouldn't be equal to one where it was 7 (hot) for the same period even though they did exceed 5 for the same amount of time.

Other important factors should also be noted at this point. Most of the indices reviewed

in Appendix B are valid for, or at least have been developed for, quasi-steady situations.

The subjects have been exposed to (or the models simulate the subjects being exposed to)

steady-state environments for periods of time up to four hours and their response given accordingly. Very seldom does this occur in the average residence and the technique of extending

these indices to a more transient environment needs at least a "close look". ASHRAE, in their

Comfort Standard [5], recommend limiting the rate of change of dry-bulb temperature in a space

to 4°F/h (2.2°C/h) and the rate of change of water vapor pressure to 4.5 mm Hg/h (600 N/m )^.

These limits have been verified somewhat by an experimental study at Kansas State University

reported by Sprague and McNall [16]. College students wearing the "standard clothing" (see

Appendix B) were subjected to an environment where the dry-bulb temperature and relative

humidity was oscillated one at a time about the "comfort value" while the other parameter

was maintained at the "comfort value". The conclusion of the study was that the Comfort

Standard values are somewhat conservative but no change was recommended. In addition, Wyon

et. al. [17] studied the cyclic variations of temperature about some optimum. Subjects were

free to reverse the direction of change of temperature swings and could thus control the

amplitude and period of swings to which they were exposed. It was found that "their subjective

tolerance of temperature swings was very much greater than is supposed by existing regulations".

Another factor to be considered is the effect of nonuniform environments. There is a capability built into many of the indices to handle a situation where the wall temperatures

are different than the ambient air temperature. McNall et. al. [18, 19] have done studies

at Kansas State University which have shown that for "reasonable degrees" of temperature

separations between the enclosing surfaces and the air, the subjects experienced no significant discomfort which could be attributed to asymmetry and that the use of the mean radiant

temperature in the computation of environmental condition was satisfactory. Other studies

had been done earlier at Kansas State University [20, 21, 22] and at CSTB in France [23] on

the same subject.

Finally, it was felt at the beginning of the study that the PIHI scale should ideally

take into account the type of occupant in the residential dwelling under consideration or

at least there should be a different scale for the different types of occupants. Recent

studies, both within the U.S. and at the Technical University of Denmark, have shown that

comfort conditions do not significantly depend upon age, adaptation, sex, or seasonal and

This condition corresponds to approximately 20 percent relative humidity per hour.

12
circadlan rhythm [24, 25, 26, 27, 28]. However, It should be noted that even though the

preferred comfort conditions have been the same, conditions of discomfort, which are perhaps

the relevant ones to consider here, could very well be different for different age groups,

sex, etc. [29]. This latter field is one that is just beginning to be researched.

In summary, the concept of the Predicted Indoor Habitability Index has been introduced

as a scale or index that is required in order to successfully complete the job of establishing air conditioning criteria.

The authors have pointed out a number of factors that should be accounted for in

establishing the scale and it is hoped that a separate research task can be initiated so that the index can be established. During the first phase of the project described in

this paper, the state-of-the-art comfort indices were used in the analyses as will be

seen in the next section.

6. Preliminary Calculations and Analysis

for Air Conditioning Criteria

In order to determine whether the approach outlined in Section 2 is feasible for

determining a meaningful air conditioning criterion, some preliminary analysis was carried

out. Different apartments within complexes planned as part of HUD's Operation BREAKTHROUGH

Program have been simulated in the National Bureau of Standards' computer program (NBSLD)

described in Section 3. Hourly values of the important weather parameters, outdoor dry-bulb

temperature, wet-bulb temperature, wind velocity, and cloud cover were taken from the United

States Weather Bureau tapes (available from the National Climate Center in Asheville,

North Carolina) . The output of the simulation was hourly values of indoor dry-bulb and

wet-bulb temperature. Algorithms for pertinent physiological and /or comfort indices were

written so that daily profiles showing values of these indices could be obtained.

The analysis was begun by arbitrarily taking, the weather data for the years 1949 through

1958 in Jersey City, New Jersey and simulating the behavior of one of the heavyweight apartments to be built on that site. The building data that were used are as follows:

1. The apartment building was assumed to face west and the individual apartment

chosen was one at approximately mid-height of the 130 feet (39.6 m) high

structure. No building shadow was used and the adjacent apartments and

hallway were assumed to always be at the same temperature as the apartment.

2. The exposed wall is constructed 'of 7 inches (17.8 cm) of concrete and 2 inches (5.1 cm) of insulation. It contains a 100 ft2 (9.3 m2) glass window

(shading coefficient = 0.22 corresponding to a double pane window with a white opaque roller shade) . The total wall area is 212 ft2 (19.7 m2) 1 eaving 112 ft^ (10.4 m^) of solid structure.

3. The floor/ceiling unit is composed of 5 1/2 inches (14 cm) of concrete and

1/8 inch (0.32 cm) cork tile with a total area of 550 ft^ (51.1 m^) . The

floor to celling height is 8.5 ft (2.6 m)

.

4. The partition walls contain 6 inches (15.2 cm) of concrete.

5. The maximum number of occupants is 2, the maximum equipment load is

1/2 W/ft^ (5.4 W/m2) of floor area, and the maximum lighting load is

3 W/ft2 (32.3 W/m ) of floor area.

6. The infiltration or natural ventilation rate was simulated as 1 air

change/h between 6 a.m. and 7 p.m. and 6 air changes /h from 7 p.m. to 6 a.m.

13
Typical results for the months of July and September in Jersey City are shown in

Figures 7 through 24. The data is for the summer of 1952 which was hotter than the mean

for the 10 year period that was examined. The outside dry-bulb temperature was equal to

or greater than 80°F (26.7°C) for 615 hours during the four months, June through September

(3rd highest in ten year period) , and the outside wet-bulb temperature was equal to or greater than 67°F (19.4°C) for 1258 hours (3rd highest)^. Shown in Figure 7 is a plot of

the solar energy falling on the west facade of the apartment (after modification by actual

cloud cover) and a plot of outdoor dry- and wet-bulb temperature for the month of July.

Figure 8 shows the output of the thermal simulation for this apartment; in other words,

a monthly profile of indoor dry- and wet-bulb temperature. Since the ASHRAE Comfort Standard gives limits on the rate of change of indoor temperature and relative humidity, these

values were computed and are shown in Figure 9. As can be seen, the suggested values of

4°F/h (2.2°C/h) and 20%/h were only exceeded once or twice during the month of the ten

year period regardless of how hot the weather was.

Figures 10 through 15 show monthly profiles of several of the physiological indices

discussed in Appendix B, calculated from the corresponding algorithms. Eight different

indices are plotted in these figures for the month of July 1952. The particular indices

selected were based on comfort votes of subjects exposed to selected environmental conditions for different periods of time, on calculated comfort responses using an analytical

equation fitted to comfort data, and on several different expressions of heat stress related to the ratio of measured sweat rates to maximum possible sweat rates. Comments

applicable to these profiles are as follows:

1. The new effective temperature (ET*) was equal to or higher than 81°F

(27.2°C) 60.8 percent of the time and equal to or higher than 85°F

(29.4°C) only 27.0 percent of the time during the month (Figure 11).

2. The predicted mean vote for a person in standard clothing (0.6 clo) was equal to or exceeded 1 (slightly warm) 40.3 percent of the time

but was equal to or above 1 only 19.4 percent of the time then the

clothing was reduced (0.25 clo) (Figure 12).

3. There was little or not heat stress regardless of the particular index

used (old or new) (Figure 14)

.

4. The Kansas State Index was equal to or above 5 (slightly warm) only 21.1.

percent of the time (Figure 10)

.

5. More than 10 percent of the people were dissatisfied a significant

portion of the time during the month regardless of whether light

clothing or the "standard" clothing was worn (Figure 13)

.

Corresponding analysis could be made of the month of September from Figures 16 through 24. In addition, summary information for all ten years is given in Table 7. The table shows

for the 10 summers in Jersey City, the number of total hours in each summer that the outdoor dry-bulb temperature exceeded 80°F (26.7°C) and the outdoor wet-bulb temperature

exceeded 67°F (19.4°C). In addition, the percent of the time in each month that selected

indices exceeded prescribed levels was calculated and are shown.

The point has already been raised in Section 5 that an entirely new index will have

to be established to serve the needs of this study. To demonstrate one reason why this is

so. Figures 25 and 26 have been included for two warm months in 1953 and 1958, respectively.

Figure 25 shows that the indoor ET* exceeded 85°F (29.4°C) 14 percent of the time during

August of 1953. The specific way in which it occurred was for one two-hour period, twice

it went above 85°F (29.4°C) for a duration of between 12 and 18 hours, and once for more

than a 48 hour period. Figure 26 shows that in July of 1958, ET* was above 85 °F (29.4''C)

for 13 percent of the time; however, the specific way in which it occurred was entirely

different from that indicated in Figure 25. The question that arises is: would the feeling of discomfort be identical during these two months? If not, there appears to be justification for the establishment of a new scale (PIHI) that accounts for frequency and duration

of uncomfortable conditions.

^nder these conditions, air conditioning should be considered according to the previously

referenced Air Force guidelines [1]

.

14-
It is felt that given the kind of information just shown for a specific structure and

location, the decision to air condition could certainly be made. However, it would be

neither practical nor economical to undertake such an analysis for each individual case.

It is still questionable whether it is feasible to carry out the analysis for many combinations of building groups and climatic zones across the United States. Therefore, a shortcut method was sought by examining the results of this thermal simulation very closely.

In Figures 27 through 32, it can be seen that correlations were attempted between

time (in 4 months) each year for 10 years that a chosen index was above a prescribed value

inside and time the outdoor dry-bulb or wet-bulb temperature exceeded 80°F (26.7°C) or 67°F

(19.4°C), respectively. Because of the structure of the present HUD criteria [2], it was

felt that this would be one way to describe quantitatively the "thermal performance" of the

unit. As the figures indicate, the correlations were not very significant.

Seeking a correlation covering a shorter period of time. Figures 33 and 34 show the

daily maximum values of the KSU index inside as a function of maximum dry-bulb temperature

and wet-bulb temperature outside for August of 1954 in Jersey City. The results are much

better than the previous ones but still too scattered to be of much value. Additional

similar correlations were tried where the independent variable was respectively, the outside dry-bulb temperature at 4 p.m., the outside dry-bulb temperature at 5 p.m., and the

average of maximum dry-bulb temperatures the day before and on the day in question. However,

when the same dependent variable was plotted as a function of average (over a 24 hour period)

outdoor dry-bulb temperature the result was very much improved as shown in Figure 35. The

correlation coefficient (r) for this particular set of data was 0.97 (maximum possible value

= 1.0)^. The same degree of success was attained with other indices such as the new effective temperature shown in Figure 36 and for other months (see Table 8) . This is in agreement

with the findings of Loudon [8] in which he states: "...heavy buildings screened from solar

radiation do not rise more than a few degrees above the mean outside temperature unless there

are appreciable heat gains from lighting, occupants or other heat sources. It is primarily

the daily-mean temperature that has to be considered, rather than the maximum; diurnal temperature variations can be smoothed by the thermal capacity of the building".

The daily average temperature used was not the average of the twenty-four hourly values

but rather the average of the daily maximum and daily minimum. The particular average was chosen due to the fact that many United States Weather Bureau Stations report this parameter

[31]. The discrepancy is usually quite small as the curves of Figure 37 indicate.

The straight lines of Figures 35 and 36 were determined by regression analysis (method

of least squares) in order to fit the data as close as possible. In fact, similar regression

lines were determined for June, July and August of all ten years. It was found that each of

the 30 lines fell within the corridor of Figure 38.

The importance of such correlation results lie in the fact that if proven valid for a class of buildings with similar thermal response characteristics, a particular line could

be determined for a given housing unit-weather data group by a small number of calculations

compared to a lengthy hour by hour computation. The results for an extended period of time

could then be determined by scanning of weather tapes alone.

Table 9 was constructed by using a special routine to scan the weather tape. It shows

for the year 1949 in Jersey City, the number of days during the year (in the right-hand

column) in which the daily outdoor average dry-bulb temperature is equal to or greater than

the temperature in the left-hand column. Consequently, if a linear relationship, such as Figure 35 or Figure 36, is established for a particular building, then the number of days

^According to reference [30], for the population chosen, a significant correlation exists

for r > 0.4.

15
in which the indoor environment could be expected to be at or above a certain specified

comfort condition could be determined at a glance. For example. Figure 38 shows that for

the particular building being analyzed, a KSU value of 5 corresponds to an outside temperatur

of approximately 81°F (27.2°C)^. Table 9 indicates that the daily average temperature was

equal to or exceeded this value 23 days during 1949 in Jersey City. This corresponds to approximately 20 percent of the summer days (4. months) . From the detailed printout of the

hour -by-hour simulation computer run, it was determined that the KSU value equalled or exceeded 5 on 32 different occasions''.

For the remainder of the feasibility study conducted to date, emphasis was placed on determining the validity of the above "short-cut" approach. There were several questions

that had to be answered. Was the correlation with outside average dry-bulb temperature

valid for other types of buildings? Did the correlation change when the building was moved

to another climatic region or could one "line" be assumed valid for all localities. What

is • the minimum amount of hour by hour simulation needed to determine the relationship? What

is the sensitivity of the correlation to changes in the configuration of a given building?

The degree to which the above questions were satisfactorily answered is described in the

remainder of this section.

The simulations and calculations done thus far did not include the calculation of mean

radiant -temperature in the space. Consequently in the calculation of the indices, the MRT

was always assumed equal to the dry-bulb temperature. Once the equations described in

Appendix A for the calculation of mean radiant temperature were included in the simulation

model, some plots were made to determine if the effect was significant. Figure 39 shows

to what extent the mean radiant temperature differs from the indoor dry-bulb temperature

on a relatively cool day that followed several warm ones. As can be seen from the plot,

the difference can be as much as 4°F (2.2°C) if the MRT is calculated near a cold surface

but only 1°F (0.55°C) if calculated in the center of the space. In addition, the calculation showed that equation (8) of Appendix A was sufficiently accurate for the present application. Figure 40 shows the difference in the resulting correlation due to the inclusion

of the MRT calculation. This was to increase the comfort vote by 0.5 at an average outdoor

temperature of 75°F (23.9°C). Therefore, for the remainder of the study, the MRT calculation

(in the center of the space) was included.

The air change rate assumed in the apartment simulation was most favorable for taking

advantage of "natural cooling"' that is, a high rate of air flow rate at night (6 volume

changes per hour) to precool the apartment and a low flow rate during the day when the out- door temperature is likely to be high. Perhaps an assumption such as this shouldn't be used

as a base for establishment of the criteria tables since this "optimum control" of outside

air introduction will seldom be used in actual practice. Consequently some of the calculations were repeated to determine the effect of this variable.

Hour-by-hour calculations were repeated three times for the year 1949 for three additional rates of air change. First the air change rate was assumed constant at 1 volume

change per hour*^. The calculations were repeated for the case where the flow rate was controlled according to the outdoor temperature. Finally, one other simulation was done

where the air flow rate was controlled according to an empirical equation developed by

Coblentz and Achenbach [32]. They measured actual infiltration rates in ten electricallyheated houses in Indiana. The homes were a variety of one- and two-storey brick and frame

built over basements, crawl spaces, and concrete slabs. Based on the findings of earlier

studies done at the University of Illinois [33], Coblentz and Achenbach expressed their

results in terms of a polynominal expression where the infiltration rate was a linear function of the outdoor wind velocity (W) and inside-outside temperature difference (AT)

.

I = A + BW + CAT (4)

Corresponding to the center of the corridor.

Since 32 is larger than 23, the KSU index went above 5, dropped below, and rose ab. again on the same day.

This is the common assumption in most design calculations.

16
Figure 41 shows the effect of the different assumptions on the indoor dry-bulb temper- ature during one particular day. Figure 42 is the corresponding plot for indoor wet-bulb

temperature. Finally, Figure 43 shows the effect on the resulting correlation line. As can

be seen, the Coblentz-Achenbach expression is perhaps the most "conservative" assumption to use, causing the comfort vote to be increased by 1.0 at an average outdoor temperature of

75°F (23.9°C) compared to the original assumption of 1 during the day and 6 at night. The

assumption of 1 air change per hour resulted in an increase of 0.7 in the comfort vote at 75°F (23.9°C). Based on these results, it is felt that 1 air change per hour should be

used as the base assumption in establishing the criteria.

The "thermal performance" of the apartment was, of course, expected to change if the

pertinent building characteristics were changed. Hour by hour calculations were made for

the summer of 1949 when the large picture window facing west was changed from double pane

with a white opaque roller shade (S.C. = 0.22) to single pane with a medium colored Venetian

blind (S.C. = 0.64). Figure 44 shows the effect of this change on the resulting correlation

"line" (an increase of 0.5 in the comfort vote at an average outdoor temperature of 75°F

(23.9°C))and Figure 45 shows the relationship between the new line and the previously determined

corridor.

A simulation was done for the summer of 1949 when the originally defined building is simply reoriented so that the exposed wall and large picture window now face north. Figure

46 shows the relationship between the correlation "line" determined for this configuration

and the previously determined corridor. Calculations were also done for the summer of 1949

when the above two changes (modified window and 90° rotation) were combined. In addition,

computer runs were made for the summer of 1954 where the same configuration cha^.^es were

made. Table 10 shows that with the configuration changes described, the correlation with

the average outside dry-bulb temperature continued to be good.

The given building considered to this point had only 1 external surface (the west facing

wall) . Figure 47 shows the effect of first making all the walls exposed to the outside en- vironment and then finally the walls and the roof. Compared to the originally defined apartment, the comfort vote is increased by 0.5 at an average outdoor ' temperature of 75°F (23.9°C)

when all surfaces are exposed to the outside.

It is felt that from observing results similar to those of Figures 43 through 46, that

the window specifications, building orientation, and the number of exposed surfaces in the

external structure are all parameters that must be considered independent variables in the

matrix of the air conditioning criterion.

One of the most important factors to determine during the latter part of this feasibility

study was to what extent the good correlation with outside average dry-bulb temperature would

hold when the relative weight or massiveness of the structure was changed and /or the weather

conditions or locality.

Another building was selected for simulation from the plans of the various Housing

System Producers in the Operation BREAKTHROUGH Program. Since the first apartment simulated

was a rather heavyweight one, it was decided to select one with very light weight construction elements. As shown in Table 11, the weight of the walls was only 4 lb/ft2 (20 kg/m^)

compared to 81 lb/ft2 (395 kg/m^) for the first one.

A more detailed description of the building and individual apartment simulated is as follows

:

1. The apartment building is a 5-story, two-level structure, with windows facing

north and south. The first level consists of 3-story, 4-bedroom dwelling

units, and the second level of a mix of 2-story, 2-bedroom and 1-story, 1- bedroom units. The two levels are separated by 18-gage steel deck on a 1.33

inches (3.38 cm) thick concrete channel structure. The space chosen for

simulation was one located at the third floor on level 1 and is part of a 3-story, 4-bedroom unit. No building shadow was us3d and the adjacent spaces were assumed to always be at the same temperature as the chosen space.

17
2. The exposed wall (north and south) is constructed of 0.5 inches (1.3 cm)

of gypsum sheathing and 0.5 inches (1.3 cm) of gypsum wall board, with 4 inches (10.2 cm) of -air space in between. The overall exterior wall area facing south is 112 ft^ (10.4 m ), and contains 48 ft^ (4.5 m ) of opaque

surface and 54 ft^ (5.9 m^) of single pane,- 1/8 inch (0.32 cm) window

glass. The exterior wall facing north has the same composition.

3. The floor is composed of carpet on 5/8 inch (.16 cm) pljwood which is over an 8 inch (20.3 cm) air space, 5/8 inch (.16 cm) plywood, 6 inches

(15.2 cm) air space, and 1/2 inch (1.3 cm) gypsum ceiling board. The

ceiling is composed of 5/8 inch (.16 cm) plywood on 18-gage steel deck

on 1.33 inch (3.38 cm) concrete channel structure and 3/8 inch (0.95 cm^

plywood on 1/2 inch gypsum ceiling board with 6 Inches (15.2 cm) air

space in between the plywood and ceiling board. The floor to ceiling height

is 8 ft (2.4 m) and the total floor area, is 482 ft2 (44.8 m^)

.

4. The partitioned walls are composed of 1/2 inch (1.3 cm) gypsum wall board

and 3/8 inch (0.95 cm) plywood with 4 inches (10.2 cm) of air space in

between.

5. The maximum number of occupants is 3, the maximum equipment load is 1/2

W/ft2 (5.4 W/m2), and the maximum lighting load is 1 W/ft^ (10.8 W/m^)

.

6. The infiltration or natural ventilation rate was simulated as 1 air change/

hour constant.

The hour by hour simulation was again repeated for this apartment in Jersey City, New

Jersey. Figure 48 is a correlation plot of the maximum value of the KSU index inside and

the average ^outside dry-bulb temperature, the same variables that correlated well for the

first apartment simulated. As can be seen, the correlation again was quite good, which

was encouraging due to the "shortcut" technique that could possibly be used in establishing

the criterion. Figure 49 indicates that for the same month in the same locality, the maxi- mum comfort vote in the same apartment would be approximately 0.5 higher for a given average

outdoor dry-bulb temperature. The effect of making more of the apartment exposed to the

outside was examined here as before. Figure 50 shows that the effect on this lightweight

building was even more pronounced than with the heavyweight one. When all four walls plus

the, roof were exposed and an additional window was added in the wall facing west (to make

a more realistic unit) the comfort vote increased by 1.0 at an average outdoor dry-bulb

temperature of 75°F (23.9°C).

Additional factors that were not examined in any previous calculations, were the effect

of amount of floor area and relative shape of the floor. This, of course, affects the surface to volume ratio of the space and could in turn be expected to affect the resulting

indoor conditions. Figure 51 shows the results of simulating the lightweight apartment in

New Jersey with the maxiijum amount of exposure and then changing the shape of the floor area to square (22 ft (6.7 m) by 22 ft (6.7 m) instead of 14 ft (4.3 m) by 35 ft (10.7 m)) and

then in turn reducing the floor area by a factor of three. As can be seen, the effect was minimal which should indicate that these variables' not necessarily be included as independent parameters in the criterion matrix.

The only remaining factor to be examined in the feasibility study was the effect of

moving to a different climate. Several additional hour by hour calculations or simulations were performed to investigate the effect of changing this parameter.

The heavyweight apartment was simulated on a hour by hour basis in Macon, Georgia for

the year 1954. Table 12 indicates that for this apartment, a good correlation was still

obtained with the average outside dry-bulb temperature. In fact, an entire corridor was established for Macon for the ten-year period 1949 to 1958 similar to that was done for

New Jersey. The corridor is shown in Figure 52.

18
A disturbing fact was observed at this point. If one overlays the corridor of Figure 52. on that of Figure 38 (see Figure 57), he discovers that for a given average outdoor drybulb temperature, the comfort vote in Macon would be approximately 0.25 higher. This indicates that other factors such as incident solar radiation and frequency and duration of

hot conditions affect the resulting indoor environment. Also, it gave an indication to the fact that it might not be possible to establish the correlation "line" under one set

of environmental conditions and assume that it is valid for all others.

To examine this latter fact closer, some specific results will be cited. Figure 53 shows the effect of simulating the heavyweight building in three different localities. As can be seen, the correlation "line" for this apartment is almost 1.0 comfort vote higher

at an average outdoor dry-bulb temperature of 75°F (23.9°C) in Phoenix, Arizona than in

Jersey City. Although the effect of climate appeared to be less pronounced for the lightweight apartment (Figure 54) it was observed to be just as pronounced once all the surfaces were assumed exposed (Figure 55)

.

At this point in the study, it became obvious that at least a small number of hour-byhour simulations would have to be done in each identified climatic zone. In additon, Table

13 indicates that the correlation with average outside dry-bulb temperature did not turn out

to be the "best" of the limited number of variables that were examined as the building con- figuration and/or climatic zone was changed. Consequently, when this project was discontinued,

it was felt that hour by hour simulations in conjunction vith the histogram routines used to construct the data for Figures 25 and 26 would be the most desirable tools to use to complete

the establishment of the criterion tables. Therefore, it was tentatively decided to abandon

the concept of getting the final tabular values by a "shortcut", correlation "line" approach.

As noted previously, this will probably be an expensive (significant amounts of computer

time are needed) and time consuming task to undertake because of the large number of variables

to be accounted for. It appears that one "conservative" alternative is available. This

alternative is as follows: Consider the apartment, building, or room in question exposed

to the hot "design-day" conditions that air conditioning engineers use in sizing cooling

equipment. The space would be exposed to this day's weather data for 4 to 7 consecutive days

(until a steady periodic condition existed where the indoor environmental conditions were

repeated from one day to the next) . The peak value of one of the comfort indices would then

be used to "grade" the environment either acceptable or not. The authors feel this approach

should be studied only if the alternative would be to discontinue the work altogether.

To determine if this latter approach gives truly "conservative" results, additional

calculations were carried out. The 1% design values of outdoor dry-bulb and wet-bulb temp- erature presented in the ASHRAE Handbook of Fundamentals [15] for several selected cities

(see Table 14) were used in conjunction with the dimensionless daily temperature cycle of

Figure 56 (determined from surveying actual weather tapes) to produce a design day cycle for

these cities. The heavyweight apartment was then subjected to this design day cycle (in the

computer program) for seven straight days using the actual solar radiation in these localities

and assuming zero cloud cover. Shown in Figure 57 are the results of the calculations where

the maximum value of the KSU index in the apartment during the second and fifth day are plotted

for each city. There was no noticeable change after the fifth day. As can be seen, the

data points lie on the upper side of the previously determined corridor. Using this type

of calculation approach, the decision to air conditioning the various cities would be made

entirely on what ordinate value on this plot (or value of comfort index) was deemed acceptable.

7. Conclusions and Recommendations

Based upon the preliminary study described in this paper, the following conclusions

have been drawn:

1. The computer program "NBSLD" and the modifications and routines that were

made or added to it during this study, can be used to supply all information

necessary to the establishment of an air conditioning criterion on a sound

technical base.

19
2. The degree to which a space or building would remain acceptable without the

addition of mechanical cooling cannot be determined by the use of the "state

of-the-art", "steady-state" comfort indices alone. Other factors such as frequency and duration of hot conditions and consideration of the situations

under which people are "uncomfortable" should be taken into account.

3. A criterion can be established in the form of tables that would specify

whether or not mechanical cooling should be installed. The parameters

that should be considered as independent variables in the tabular matrix are

a. weight per unit area of the building enclosure,

b. number of exposed surfaces of the building enclosure,

c. degree of shading for the windows,

d. shape of roof if exposed (peaked or flat),

e. orientation of the building, and

f. geographical location

Other possible independent parameters might be

a. air infiltration rate,

b. percent of the exposed surface area that is glass,

c. aspect ratio of the floor, and

d. floor area

4. On the basis of weight per unit area of a building enclosure, the following

classification can be used:

Lightweight Structure: less than 20 Ib/ft^ (98 kg/m^)

Medium Weight Structure: 20 (98) to 59 Ib/ft^ (244 kg/m^)

Heavyweight Structure: greater than 50 Ib/ft^ (244 kg/m^)

The following recommendations are made, based upon the study described:

1. A research contract should be given to some organization or individual

doing physiology or related research work to establish both the definition

and acceptable limits of the Predicted Indoor Habitability Index as introduced in this paper.

2. A separate research task should be undertaken to divide the United States

into a sufficiently large number of climatic regions with typical hour-byhour summer weather data for June, July, and August established for each

region.

3. Based upon the information within this paper and elsewhere, a sufficient

number of "typical buildings" should be defined for simulation taking into

account the pertinent independent variables in 3. above.

4. In light of the "Energy Problem" in the United States today, this study

should be continued to completion so that the results could be used for

showing those situations where mechanical cooling are unnecessary.

20
8. References

1. "Engineering Weather Data", Chapter 6, Air Force Manual 88-8, June 15, 1967.

2. "Guide Criteria for the Evaluation of Operation BREAKTHROUGH Housing Systems", Volume

1 - Multifamily High Rise, PB 212055; Volume 2 - Multifamily Low Rise, PB 212056;

Volume 3 - Single Family Attached, PB 212057; Volume 4 - Single Family Detached,

PB 212058, 1970. (Available through NTIS, Springfield, Virginia 22151).

3. J. F. van Straaten, Thermal Performance of Buildings , Elsevier Publishing Company,

1967.

4. B. A. Peavy, D. M. Burch and F, J. Powell, "Thermal Performance of an Experimental

Masonry Building", NBS Building Science Series 45 , 1973

5. ASHRAE Standard 55-74, "Thermal Environmental Conditions for Human Occupancy", ASHEAE,

345 East 47th Street, New York, New York 10017, 1966.

6. B. Givoni, Man, Climate, and Architecture , Elsevier Publishing Company, 1967.

7. V. Olgay, Design with Climate , Princeton University Press, New Jersey, p. 185, 1963.

8. A. G. Loudon, "Summertime Temperatures in Buildings", Paper 47/68, Building Research

Station of England, 1968.

9. J. Anquez, J. C. Borel, and M. Croiset, "La Protection Solaire des Bales Vitrees",

Cahiers du Centre Scientiflque et Technique du Batlment No. 72, Paris, France, 1965.

10. T. Kusuda and F. J. Powell, "Use of Modern Computer Programs to Evaluate Dynamic Heat Transfer and Energy Use Processes in Buildings", National Bureau of Standards Special

Publication 361, Volume 1: Performance Concept in Buildings ; Proceedings of the Joint

RILEM-ASTM-CIB Symposium, Philadelphia, Pennsylvania (Issued March 1972).

11. T. Kusuda, "NBSLD, Heating and Cooling Load Calculation Program", APEC Journal , Volume

III, No. 6, Winter 1973/74.

12. T. Kusuda, "NBSLD, Computer Program for Heating and Cooling Loads in Buildings, NBS

Report NBSIR 74-574, November 1974.

13. "Procedures for Determining Heating and Cooling Loads for Computerized Energy Calculations", The Task Group on Energy Requirements for Heating and Cooling, ASHRAE, 345 East 47th Street, New York, 1971.

14. B. A. Peavy, D. M. Burch, and F. J. Powell, "Thermal Performance of a Four Bedroom

Wood-Frame Townhouse", NBS Building Science Series 57 , 1974.

15. ASHRAE Handbook of Fundamentals , ASHRAE, 345 East 47th Street, New York, New York 10017,

1972.

16. C. H. Sprague, and P. E. McNall, Jr., "The Effects of Fluctuating Temperature and Relative

Humidity on the Thermal Sensation (Thermal Comfort) of Sedentary Subject", ASHRAE Transactions , "Vol. 76, Part 1, 1970.

17. D. P. Wyon and I. Holmberg, "Systematic Observation of Classroom Behaviour During

Moderate Heat Stress", Proceedings of the CIB (W 45) Symposium on Thermal Comfort

and Moderate Heat Stress , London, 1972.

18. P. E. McNall and J. Schlegel, "The Effect of Asymmetric Radiation on the Thermal and

Comfort Sensations of Sedentary Subjects", ASHRAE Transactions , Vol. 74, p. 144, 1968.

19. P. E. McNall and R. E. Biddison, "Thermal and Comfort Sensations of Sedentary Persons

Exposed to Asymmetric Radiant Fields", ASHRAE Transactions , Vol. 76, Part I, pp. 123-

136, 1970.

21
20. R. G. Nevins, K. B. Michaels, and A. M. Feyerherm, "The Effect of Floor Surface Temperature

on Comfort: Part I, College-Age Males; Part II, College-Age Females", ASHRAE Transactions , Vol 70, pp. 29-43, 1964.

21. W. E. Springer, R. G. Nevins, A. M. Feyerherm, and K. B. Michaels, "The Effect of Floor

Surface Temperature on Comfort: Part III, The Elderly", ASHRAE Transactions , Vol. 72, Part I, pp. 292-300, 1966.

22. R. G. Nevins and A. M. Feyerherm, "Effect of Floor Surface Temperature on Comfort, Part

IV: Cold Floors", ASHRAE Transactions , Vol. 73, Part II, III. 2. 1-2. 8, 1967.

23. J. Anquez, and M. Croiset, "Thermal Comfort Requirement Adjacent to Cold Walls - Application to Glazed Opening", NBS Technical Note 710-4 , 1972.

24. R. G. Nevins, F. H. Rohles , W. Springer, and A. M. Feyerherm, "A Temperature-Humidity

Chart for Thermal Comfort of Seated Persons, ASHRAE Transactions , Vol. 72, Part I, pp. 283-291, 1966.

25. F. H. Rohles and M. S. Johnson, "Thermal Comfort in the Elderly", ASHRAE Transactions , Vol. 78, Part I, 1972.

26. P. 0. Fanger, "Thermal Environments Preferred by Man", Build International , Vol. 6, No. 1, pp. 127-141, 1973.

27. S. Olesen and P. 0. Fanger, "Can Man be Adapted to Prefer a Lower Ambient Temperature?",

5th International Congress for Heating, Ventilating and Air Conditioning, Part I, pp. 27-40, Copenhagen, 1971.

28. P. E. McNall, P. Ryan, and J. Joax, "Seasonal Variation in Comfort Conditions for

College-Age Persons in the Middle West, ASHRAE Transactions , Vol. 74, Part I, 1968.

29. R. G. Nevins, personal communications, 1974.

30. M. G. Natrella, Experimental Statistics, NBS Handbook 91, 1963.

31. "Instructions for Climatological Observers Circular B", U.S. Weather Bureau Publication,

January 1962.

32. C. W. Coblentz and P. R. Achenbach, "Field Measurements of Air Infiltration in Ten

Electrically-Heated Houses", ASHRAE Transactions , Vol. 69, 1963.

33. D. R. Bahnfleth et. al. , "Measurement of Infiltration into Residences", ASHRAE Transactions , Vol. 63, pp. 439-452, 1957.

22
Weather Data Fron.

the Selected

Climatic Zone

Simulation of the Building

Responding to the Climatic

Conditions (computer

program)

Building Data From

a Selected Class of

Buildings

Specification of Indoor

Conditions

Determination of the Value

of PIHI

t

Comparison with PIHI Limits

to Determine if Air Conditioning is Required

Figure 1 Concept of Determining the Need for Air Conditioning

23
building cycle

room cycle

day cycle

hour cycle

CONDUCTION TRANSFER FUNCTIONS

!i BUILDING DATA

II ROOF SURFACE DATA

HTTM"::::

INTERIOR SURFACE HEAT TRANSFER COEFFICIENTS

INTERIOR SURFACE RADIATION EXCHANGE FACTORS

11^ WEATHER_DATA_

HOLIDAY, WEEKENDS DETERMINATION

DAYLIGHT SAVING TIME INDICATOR

CLOUDLESS SKY SOLAR RADIATION

SUN-LIT AREA DETERMINATION ^

CLOUD COVER MODIFICATION

ON SOLAR HEAT GAIN AND SOLAR INTENSITY

AIR INFILTRATION

OUTSIDE SURFACE HEAT TRANSFER COEFFICIENT

OUTSIDE SURFACE TEMPERATURE AND HEAT FLOW

ATTIC TEMPERATURE

COOLING LOAD OR THE ROOM TEMPERATURE

OUTPUT TABLE

INSIDE SURFACE TEMPERATURE AND HEAT FLOW

Figure 2 NBSLD Calculation Sequence

24
120-

110-

100-

90-

80-

°C = (°F -32)- |.

6Ch

50-

I A OUTSIDE flIR D MEASURED

O CflLCULflTED

40-

12 15 18 21 TIME - HOURS

NO INSULATION,NO WINDOWS, INTERNAL MASS.

24

Figure 3 Comparison of Predicted and Measured Indoor Air Temperature for

a 20 ft (6.1 m) by 20 ft (6.1 m) by 10 ft (3.1 m) Experimental

Masonry Building

25
EXTERIOR WALL

-| r "I—I—I—

r

"1 r 1 r

1—I—

r

1 Btu/(ft2.°F) = 2.04 X lO'^ j/(ni2.''C)

1 Ib/ft'^ = 4.88 kg/m^

J I L 2 2.5 3 5 6 7 8 9 10 2.5 3 5 6 7 8 9 10' WEIGHT / AREA ~ LB / FT^

Figure A Relation of Thermal Mass to Weight for Selected Exterior

Wall Constructions

26
1 h = 3600 s 1 lb/ft2 =4.88 kg/m^

®

®

®

® ®

®

®

EXTERIOR WALL ® ®

®®

®

®

®

®

®

®

®

®

® ®

®

J L J ! I I I L J I I I L

7 8 9 10 WEIGHT/AREA ~ LB/FT^7 8 9 lO"

Figure 5 Relation of Thermal Time Constant to Weight for Selected

Exterior Wall Constructions

27
®

1 h = 3600 s

1 Ib/ft^ =4.88 kg/m^

ROOF/ CEILING

®

®

®

®

®

®

®

®

®

® %

®

J I L J I 1 L

7 8 9 10 WEIGHT/AREA7 8 9 10'' LQ/FV

Figure 6 Relation of Thermal Time Constant to Weight for Selected

Roof/Ceiling Constructions

28
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Heavyweight Apartment

Jersey City; June 28, 1949

1 Air Change Per Hour , Constant

TIME (HOURS FROM MIDNIGHT)

Inside Air Temperature

Mean Radiant Temperature (Center of Room)

Mean Radiant Temperature (2 ft (0.6 m) From the Window)

Inside Wall Surface Temperatures

Figure 39A . Comparison of Mean Radiant Temperature Calculation Results

for a Heavyweight Apartment, June 28, 1949, Jersey City, N.J.

61 " -
Heavyweight Apartment

Jersey City; June 28, 1949

1 Air Change Per Hour, Constant

TIME (HOURS FROM MIDNIGHT)

Figure 39B Comparison of Mean Radiant Temperature Calculation Results

for a Heavyweight Apartment, June 28, 1949, Jersey City, N.J;

62
63
74

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70

(°F - 32)

;— 1 Air Change Per Hour,

Day; 6, Night

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2 Ft From the Window; 1 Air Change Per Hour

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J I L 6

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IE (HOURS FROM MIDNIGHT)

Figure 41 Comparison of Indoor Dry -bulb Temperature Profiles With

Different Air Infiltration Assumptions for a Heavyweight

Apartment, June 28, 1949, Jersey City, w'.J.

64
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78

76

74

72 —

HEAVY-WEIGHT APAFTMBff

JffiSEY CriY; JUNE 28, 1949

A« CHANGE. COBLEWTZ AND ACHENBACH

1 CHANGE PER HOUR, CONSTANT

1 AIR CHANGE PER HOUR DAY; 6. NIGHT

1 A« CHANGE PER HOUR, IDB < 75; 6, IDB > 81

°C = ("F - 32) . ^

6 10 14 18 TIME (HOURS FROM MIDNIGHT )

22

Figure 42 Comparison of Indoor Wet-Bulb Temperature Profiles With

Different Air Infiltration Assumptions for a Heavyweight

Apartment, June 28, 1949, Jersey City, N.j.

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Table 2

Required Building Data for the "NBSLD" Calculations

Individual room length, width, and height

Occupant : number and hourly schedule

Summer and winter design air infiltration rates

For each exposure: (1) type (roof, wall, etc.)

(2) type or response factor to be used

or specified U-value

(3 ) area

(4) orientation

(5) absorptivity to solar radiation (if

opaque surface)

(6) shading coefficient (if transparent

surface)

Properties of all building materials

82
The abbreviations used in Tables 3-6, besides those that are clearly

defined, are:

E. Wall : Exterior wall

I. Wall : Interior wall or partition

P. Wall : Party wall

nD . Floor ' Basement floor

B. Wall : Basement wall

I. Door : Interior door

E. Door : Exterior door

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92
Table 7

Summary of Simulation Results for a Heavyweight Apartment In Jersey City, New Jersey

Outdoor Conditions |I Indoor Conditions

Percent oi Month

and Year

1949 June July August September

1950 June July August September

1951 June July Augus t September

1952 June July August September

1953 June July

August

September

1954 June

July

August

September

1955 June July

August September

1956 June

July August September

1957 June July

August September

1958 June July Augus t September

Total No. of Hours Total No. of Hours Percent of Percent of Percent of Time PMV Percent

in 4 Months in 4 Months Time New Time New Time KSU 2 1 Time

u 1,. 2 80 °F ET a 81 ET a 85 2 5 (0.25 clo)/

/

HSI 2 1 dry-bu lb wet-bu lb

(26.7''C) (19.4''C) /

613 1 Q OT

11 n 8.

1

7.9 0.0 U .0 ZZ .4 20 6 0.5

11 "7 ft 7 8.2 0.0

0 0 0.0 0.0 0.0 431 822 ~11.7 n Q u.o nw« 7/ 0,

0

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1

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0.

8

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1

6 .

0

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1

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1

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- 24.3 5.7 4.0 3 .6 U.U

- 42.5 16.5 11 .

7

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1

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8.7 1.0 1.0 1.1 U.U

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17.5 4.6 3.2 3.5 0.0

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3.7 0.0 0.0 0.0 0.0

40

93
Table 8

Correlation Coefficients for the Maximum KSU (Inside)

and Daily Average T^ry-bulb (Outside) for a Heavyweight

Apartment, Jersey City

Month-Year Correlation Coefficient

June 1949 0. 96

July 1949 0. 94

Aueust 1949 0 95

September 1949 0. 92

June 1953 0. 96

July 1953 0. 94

Aueust 19S3 0

Spntpmhpr c p t. CUll-'C J- 1jl^j^ QS'^ n Q7

Junp 19 "54 July 1954 0. 96

August 1954 0. 88

September 1954 0. 97

June 1955 0. 96

July 1955 0. 93

August 1955 0. 97

September 1955 0. 95

June 1956 0. 95

July 1956 0. 91

August 1956 0. 94

September 1956 0. 96

94
Table 9

Frequency Distribution o£ Average Outside

Dry-bulb Temperature, Jersey City, 1949

vlFRSEY CITY» 19^9

TFMPERATURE FRFQUFMCY T/VBLF

TEMPrF F^EO FPro FPFO FPFO

0. 25. 362 50, 228 75. 62

1. 26. 361 51. 220 76. 55

2. 365 27. 360 52. 214 77. 45

3. 365 28. 356 53. 214 78. 38

<+. ^65 29. 350 54. 204 79. 32

5. 365 30. 346 55. 1Q7 80, • 25

6. 365 31. 340 56. 191 . 81 ,

' 23

7. 365 32. 337 57. 185 82. 18

8 • ^65 33 • Tp9 58. 1 f^n 83. 16

9. 365 34. 320 59. 169 84. 13

10. ^65 35. 314 60. 163 85. 9

11; 365 . 36. 308 61. 153 86. 7

12. 365 37. 301 62. 143 87. 6

13. 365 38. 298 63. 1 33 88. 3

11^. 365 39. 2"3 64. 1 ''Q 8Q, I 15. 365 40. 287 65. 122 ' 90, 0

16. ^65 41. 283 66. 116 91, 0

17. 365 42. 276 67. 1 13 92, 0

18. ^65 43. 272 68. 1 OQ 93. 0

19. 365 44. 267 . 69. 101 94, 0

20. 365 45. 264 70. 97 95, 0

21. 365 46. 255 71, 90 06. 0

22. 365 47. 247 72. 86 97, 0

23. 365 48, 238 73, 79 98. 0

2H. 364 49, 231 74, 0

"C = CT - 32) • f

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98
Table 12

Correlation Coefficients for the Maximum KSU (Inside)

and Daily Average T^ry-bulb (Outside)

for a Heavyweight Apartment, Macon, Georgia

Month-Year Correlation Coefficients

June 1951 0. 92

July 1951 0. 96

August lyji u

.

OO

0 -/J

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July 1952 0. 94

0 Q3

0. 91

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July 1953 0. 93

Auffust 1953 0. 96

September 1953 0. 95

June 1954 0. 93

July 1954 0. 94

0. 84

Sentember 1954 0. 91

June 1955 0. 93

July 1955 0. 70

August. i.VjJ

0 89

0. 94

July 1956 0. 77

August 1956 0. 89

September 1956 0. 95

June 1957 0. 93

July 1957 0. 91

August 1957 0. 92 September 1957 0. 98

June 1958 0. 86

July 1958 0. 84

August 1958 0. 92

September 1958 0. 96

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•H 3 U "-3 ^ X

<u c c

CO

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0) « x: S Pu

a

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60

x:

60 s

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cd

cd 3

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C3N \o o o o

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00 00 ON ON ON onI ON d o o o d o d| o d

d

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00 r-l o o o

CM

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d

d

d

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ON<f ^

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r-<mON

d) /—\ 1—1 t3 CM 3 m 4J

•-J ON CO N-' ,-H 3

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<U 3

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<u cd x:

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toc

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cd

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<u cd a 4J

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d) c

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4-1 o

(U •>

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x: o S -c

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--I

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1—1 <uu <u Cd xs

cd o

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100
Table 14

ASHRAE 1% Design Weather Condltipns for Selected Cities

Location T^^, °F Range, °F

Portland, Maine 88.0 22.0

Concord, N. H. 91.0 26.0

Hartford, Conn. 90.0 22.0

West Chester, Pa. 92.0 20.0

New York, N. Y. 91.0 16.0

(Kennedy

)

Jersey City, N. J. 94.0 ' 20.0

Washington, D. C. 94.0 18,0

New York, N. Y. 94.0 17.0

(Central Park)

°C = (°F - 32) • I

Average Outside

Dry Bulb Temperature, °F

_ Range - ^db 2

77.0

78 oO

79.0

82.0

83,0

84.0

' 85.0

85.5

101

Appendix A

Derivation of the Equations to Calculate

the Mean Radiant Temperature Within NBSLD

,

la
In analyzing radiation heat transfer processes where completely diffuse exchange is

taking place between two or more gray bodies, the governing equations can be put in a form

similar to those governing the behavior of electrical networks. Consequently, the electric

analogue is quite often used in solving the problems. Such is the case in this Appendix.

The mean radiant temperature in relation to a person in a given body posture and clothing

placed at a given point in a room, is defined as that uniform temperature of the surroundings

(considered a black body) which will give the same radiant heat transfer to or from a person

as the actual case under study.

Figure Al is the electric analog of the situation in which a person is exchanging

radiation with the surfaces of a room in which it is broken down into only four separate

isothermal surfaces. All radiation is assumed to be diffuse, the person is assumed not

to exchange radiation with himself, and the following definition of terms applies:

o = Stefan-Boltzmann constant

p = surface reflectivity

A = surface area

e = surface emissivity

a = surface absorptivity

T = temperature (absolute)

J = radiosity (flow rate of radiant energy per unit area)

F, . = radiation view factor from surface i to surface j

.Q. = flow rate of energy exchange occurring by radiation from surface i

~' to surface j

Subscripts

cl = outer layer of the person's clothing

p = person

1,...,4 = surface 1,...,4

e = environment

MRT = mean radiant temperature

Using Ohm's law, the flow through the left-most leg of the electric circuit is given

by:

Q = 0(t/-J)^ p e cl P P

or since

p = l- a = l"'e

P P P

p

Q

e = (a Tcl/

A £ P P

(1)

2a
Applying Kirchoff's law* at node :

Q = (J - JJ A F , + (J - J^) A F ^ p e ^ p 1 p pi p 2 p p2

+ (J - J„) A F „ + (J - J.) A F p3pp3p4pp4, (2)

From the definition of the mean radiant temperature:

pe 1-e , 1 '1-E

A e A F A e P P y P P6 e e

Q = A£ a(T/ - T_^^) ' (3) p^e p p ^ cl MRT ^

Equating equations (1) and (3)

cl "p "p' "MRT

J = a T / £ (1 - £ ) o

^

Equating equations (2) and (3) and utilizing the derived expression for (equation (4)):

W= k ^ J2^p2 ^ ^3^3

In order to use equation ,(5) for calculating mean radiant temperature, the radiosities

J^, J2> ^3* J4 must be determined. Most building materials have a high emittance, and for

the calculation, it is often an acceptable approximation to disregard the reflections, i.e.,

to assume that all the surfaces in the room are black. Equation (5) is thus simplified to:

= t/f , + T„^F „ + T.'^F » + t/f , (6) MRT 1 pi 2 p2 3 p3 4 p4

As the sum of the angle factors is unity, the fourth power of the mean radiant temperature

is seen to be equal to the mean value of the surrounding surface temperatures to the fourth

power, weighted according to the size of the respective angle factors.

If there are only relatively small temperature differences between the surfaces of the

enclosure, equation (6) can be further simplified by linearizing, ,

T,^^ = T^F , + T^ F „ + T^F „ + T.F , (7) MRT 1 pi 2 p2 3 p3 4 p4 ^

'

In other words, the mean radiant temperature is calculated as the mean value of the surrounding temperatures weighted according to the magnitude of the respective angle factors. Fanger

[1]^ has shown that the error in using equation (7) compared to equation (6) is less than

0.2 °C for most realistic building applications.

In calculating the mean radiant temperature using equation (7) , it is necessary to know the angle factors between persons and typical surfaces. These are sometimes difficult

to calculate and therefore an additional rough approximation has often been used. The mean

radiant temperature is calculated as the mean temperature of all the surfaces in the

enclosure

:

T^A, + T-A- + T-A_ + T.A.

T =^ ^ ^ ^(8) MRT A, + A^ + A^ + A,

^Reference numbers refer to references listed at the end of this Appendix.

3a
This is equivalent to assuming:

pi + + + A^

^2

"p2 A^ + A^ + A^ + A^

The authors compared the results of calculating T^-^j using equations (7) and (8) for a person

located in the center of the masonry building apartment described in section 6. and the re- sults were different by less than 0.1°C.

References

1. P. 0. Fanger, Thermal Comfort

,

Danish Technical Press, Copenhagen, 1970.

2. E. M. Sparrow and R. D. Cess, Radiation Heat Transfer, Wadworth Publishing Company,

Belmont, California, 1970.

4a
6a

Appendix B

A Review of Comfort and Physiological Indices

lb
In this Appendix, the methods of computation for several of the analytically determined

comfort indices are discussed. The expressions for heat transfer rate between the subject

and environment by convection, radiation, etc., are given at the end of each section where

appropriate. Unless otherwise specified, the following nomenclature applies to the various

relations

:

2

Aj^y = body surface area, m

a = coefficient related to the transfer of energy from clothing by convection

(approximately 11.6 for 0.6 clo standard clothing)

f^^ = ratio of the surface area of the clothed body to the nude body (= 1.1 for

0.6 clo standard clothing)

F^^ = a factor that measures the efficiency for the passage of dry heat from the

skin surface through the clothing to the environment (= .58 for 0.6 clo

clothing)

f^^^ = the ratio of the effective radiation area of the clothed body to the surface

area of the clothed body (0.65 for seated position and 0.75 for standing)

F ^ = permeation efficiency factor for water vapor evaporated from the skin

^ surface through clothing to the ambient air (= 0.82 for 0.6 clo clothing)

h = covention coefficient, kcal/(h.m • °C)

c h = radiation coefficient, W/fc^ °-C), = 5.23 in the ET* model

r I^^ = conduction resistance value for clothing, clo

M = metabolic heat production, kcal/h

P = clothing coefficient (approximately 13.0 for standard clothing)

= vapor pressure in ambient air, mm Hg

P , = saturated vapor pressure corresponding to skin temperature, mm Hg

S K, = ambient air temperature, °C

T^-j^ = clothing surface temperature, °C

^cr

" °^ deep body temperature, °C

T,^„ = mean radiant temperature, °C MRT

T^j^ = skin surface temperature, °C

v = air velocity, m/s

Old Effective Temperature (ET)

Undoubtedly the most familiar of all comfort indices is the American Society of Heating,

Refrigerating and Air Conditioning Engineers' Effective Temperature. The scale was first

established in the 1920's by Houghten and Yaglou [1]^. Subjects wearing clothing having an unspecified insulation value^ were passed between test chambers in which the temperature, air

Reference numbers refer to references listed at the end of this Appendix.

^At the time this particular index was developed, the analysis of human comfort had not progressed to the point that insulation values for clothing ensembles were being given.

2b
velocity, and humidity were maintained at specified levels and were asked to describe their

feeling immediately upon entering the new environment . The results are shown in Figure Bl

where lines of constant thermal sensation are shown plotted on a standard psychrometric chart.

The experiments were conducted for a large range of air velocities; however, the data shown

here is for an air velocity of less than 20 fpm^ (0.1 m/s) . The lines of constant thermal

sensation were arbitrarily given numerical values corresponding to the dry-bulb temperature

at which the line intersected the saturation curve (100% relative humidity) . If the drybulb temperature were a sole indicator of thermal comfort according to this scale, the lines

would run vertically. The data therefore indicates that as the relative humidity is increased, the temperature has to be decreased to maintain the same feeling. This is natural

since cooling by sweat evaporation is restricted somewhat as the relative humidity increases.

This scale originally did not take into account the effect of radiation to or from room

walls where the walls' temperature is maintained at values quite different from the room air.

However, a correction was proposed later [2] in order to account for this effect. The ET scale continues to be accepted as valid in the very hot region where man's cooling rate depends almost entirely on his sweat evaporation but has been abandoned as inaccurate in the

comfort region or the region of most interest to this study.

As a result of the apparent disagreement between field tests and the lines of constant thermal sensation or effective temperature at the moderate temperatures, ASHRAE undertook an additional study at their research laboratory in 1960 and the results are shown in Figure B2. In this study [3], subjects wore light indoor clothing and were seated at rest. Room sur- faces were held at the same temperature as the room air in all tests, and the air motion in

the space was 20 fpm (0.1 m/s) or less. The thermal sensation votes used in analyzing the test data were those which were cast in the chamber at the end of the three hour occupancy

period. These lines show the conditions under which subjects cast votes of 3, 4, 5, or 6,

indicating sensations of slightly cool, comfortable, slightly warm, and warm respectively.

It is evident from Figures Bl and B2 that the old effective temperature index predicts a considerably greater effect of relative humidity on the thermal sensation feeling than do

the lines determined by Koch, Jennings, and Humphreys [3]. In defense of the old effective

temperature, it may be explained that the two groups of data apply to different conditions.

The effective temperature lines indicate a person's feeling immediately after entering the

conditioned space, while the lines of Figure B2 are for people who have been in the conditioned space for approximately three hours and are in equilibrium with their environment.

Resultant Temperature

In 1948, Missenard [4] proposed an index called the resultant temperature. Its development was motivated by the fact that the effective temperature was not based on experiments

where thermal equilibrium was achieved between the human body and the environment . The ex- periments on which the resultant temperature was based were conducted with about six subjects

in a psychrometric chamber with a duration of exposure greater than was used in the experiments for the effective temperature. The resultant temperature is identical in structure

with the effective temperature and is shown in Figure B3 for clothed subjects exposed to an

air velocity of 0.1 m/s (20 fpm). The resultant temperature shows that thermal sensation is

much less dependent on humidity than it was with effective temperature. However, the results

still indicate more of a dependence of humidity in the moderate temperature range than do the

comfort votes of Koch, et. al.

Kansas State Index

Perhaps the most definitive experimental study on thermal comfort is one conducted on over 1600 college students at Kansas State University over the past several years [5, 6].

The students were exposed (over a 3 hour period) to a uniformly heated or cooled environment

(wall temperatures identical to the air temperature) with moderate air velocities and asked

to vote on a scale from 1 to 7 which ranged from cold to hot:

For purposes of this study, the data for all the indices described will be for very nominal

air velocities (i.e., 20 fpm or 0.1 m/s) since higher velocities very rarely occur in

residences.
1

.

coici

o/ . cool

-5 . slightly cool

4

.

ir D . slightly warm

6. warm

7. hot

All subje.cts, males and females alike, were clothed in cotton twill shirts and trousers.

The shirts were worn outside of the trousers. The subjects wore the underwear they had on when reporting for this test, which usually consisted of cotton undershorts or jockey shorts

for the men and brassieres and underpants for the women. All other clothing, including T- shirts, girdles, slips, etc., were removed. The subjects wore cotton sweat socks without

shoes. The net insulating value for the clothing ensemble, as computed by means of an electrically heated copper manikin [7] has been determined to be 0.6 clo^ which has be^n

generally accepted as the standard clothing for thermal comfort studies.

Even though the results are available for men and women separately and also for the

votes taken at each half an hour for the entire 3 hours of exposure, the data shown in

Figure B4 is an average for the votes of men and women taken together at the end of the

3 hours

.

Until very recently, the results of comfort studies were represented as lines on a pyschrometric chart as done above. As Rohles of Kansas State University pointed out in

1969 [8], "from a purely operational point of view this [type of representation] is totally

impractical since there is nothing in the way of a range or plus or minus limit about the

line. Moreover, the requirement for limits of this type becomes more apparent when we con- sider the data used in the construction of the line itself are based on value judgments of

unknown reliability". As an alternative, Rohles [9, 10] proposed zones or envelopes of the

thermal comfort.

The Modal Comfort Envelope (MCE) was derived purely by trial and error from the distribution of thermal sensations from the above-mentioned study with 1600 subjects. The set of

15 conditions which has been identified as the MCE are: 80 °F (26.7 °C) at 15, 25, 35, and

45% RH; 78 °F (25.6 °C) at 15, 25, 35, 45, 55 and 65% RH; and 76 °F (24.4 °C) at 45, 55, 65, 75 and 85% RH. The distribution of thermal sensations within this envelope after an exposure

of 3 hours showed that none of the subjects voted hot or cold; approximately 3% were warm

and cool and 94% reported a sensation of slightly cool, comfortable, or slightly warm. The mean sensation was 4.0 or "comfortable" with a standard deviation of 0.72.

Besides defining the thermal environment in which sedentary man is comfortable, the MCE

forms a prescribed set of temperature-humidity conditions that can be used for studying the

thermal senstion as a function of such factors as age, clothing, activity, radiant temperature, air movement, color of the surroundings, and illumination level. As such, it replaces

the traditional approach to studies in this area which arbitrarily select temperatures which

are equally spaced physically yet totally unequal from the standpoint of the thermal sensation.

1 clo represents a measured resistance to heat transfer of the clothing ensembled of 0.18

(m2 • h • °C) cal (0.88 (ft^ • h . ''F)/Btu or equivalent of an overall heat transfer

coefficient = 1.13 Btu/(h • ft2 • "F)).

4b
The Modal Comfort Envelope has been used in two studies to determine the independence

of the environmental consistuents that affect the thermal sensation. In the first application, the thermal sensations of elderly subjects were compared to those of college students'

[11], and in the second study the MCE was used to determine the influence of clothing and

temperature on sedentary comfort' [12]

.

The MCE was also used as a reference in defining the KSU-ASHRAE Comfort Envelope in the

1972 ASHRAE Handbook of Fundamentals [13]. This envelope is represented in Figure B5 as the

quadrilateral having its points at 80 °F (26.7 °C) 45% RH; 80 °F (26.7 °C) 15% RH; 76 °F (24,4 °C) 85% RH; and 76 °F (24,4 °C) 45% RH.'

For purposes of comparison, the shaded envelope on the chart defines the limits of the

conditions prescribed in ASHRAE Standard 55-74 [14]. Whereas the KSU-ASHRAE Comfort Envelope

applies to subjects wearing clothing whose insulation value is 0,6 clo, the ASHRAE Comfort

Standard applies to subjects wearing 0.8 to 1,0 clo. In addition, the KSU-ASHRAE Comfort

Envelope applies to sedentary activity whereas the ASHRAE Standard applied to office work

which is slightly greater than sedentary. The differences in activity level and clothing

account for the differences in the two envelopes. The area where the two envelopes overlap

is recommended as the "design conditions for comfort" [15],

Predicted Mean Vote and Predicted Percentage of Dissatisfied

One of the most significant attempts to predict analytically the thermal interaction

between man and his environment is presented by P, 0. Fanger of the Technical University of

Denmark in* his recent book Thermal Comfort [16]. He begins by pointing out the most important variables which influence the condition of thermal comfort:

1, activity level (heat production in the body)

2, thermal resistance of the clothing (clo-value)

3, air temperature (dry-bulb)

4, mean radiant temperature

5, relative air velocity ,

6, water vapor pressure in ambient air

The basis of his analysis in the so-called general comfort equation which defines all com- binations of the variables which will create thermal comfort. Its specific form is as follows

:

dxf f E -D = K = R+ C res

(1)

where

M =

^diff

Esw

Eres

D

the internal heat production in the human body

the energy loss by water vapor diffusion through the skin

the energy loss by evaporation of sweat from the surface of

the skin

the latent respiration heat loss

the dry respiration loss

5b
K = the heat transfer from the skin to the outer surface of the

clothed body (conduction through the clothing)^

R = the heat loss by radiation from the outer surface of the clothed

body

C = the heat loss by convection from the outer surface of the clothed

body

The double equation expresses that the internal heat production M minus the heat loss

by evaporation from the skin (Ej^ff + Eg^) and by respiration (Ej.gg + D) is equal to the

heat conducted through the clothing K and dissipated at the outer surface of the clothing

by radiation and convection (R + C) . It is assumed that the evaporation corresponding to Eg^ and E^jj^jj takes place at (or underneath) the skin surface.

After formulating expressions for each component in the above equation (see the end

of this section) and substituting them into equation (1) , two algebraic equations result

in the following 9 unknowns:

(defined previously)

skin surface temperature

water vapor pressure in the ambient air

(defined previously)

ambient air dry-bulb temperature

clothing surface temperature

insulation value of the clothing mean radiant temperature of. the environment

the relative air velocity

Six of the unknowns (M, P^, T^, T-^^.' ^' ^MRT^ considered as controllable or specified for any particular subject —environment situation. Two of the remaining unknowns

are eliminated by what may be considered Fanger's most questionable assumption. During

studies at Kansas State University on college students, data was obtained for mean skin

temperature and evaporative heat loss of the subjects while they reported being comfortable

conducting various activities (different M's). Eg^ and Tg were plotted individually as a function of the metabolic production and even though the data was rather widely scattered,

linear equations

= f (M) (2)

and

F = f (M) (3) sw were determined by regression analysis. The procedure then used was to specify 5 of the 6 controllable or specified quantities (M, P^^, T^, I^Ij v, and Tj^r^) , and use the 4 equations

(1, 2, and 3) to determine the remaining four unknowns, one of which is the sixth of the

controllable parameters that would give thermal comfort. The results are presented in the

form of comfort charts.

T

-

s

P

- w

"sw

T

-

cl

^cl

^MRT

V

The resistance value for the clothing is determined in such a way that it accounts for

the heat transfer from the nude portion of the body as well.

6b
Having determined the conditions for optimum thermal comfort, Fanger recognized the need

for being able to evaluate an existing room climate and quantify its deviation from the comfort condition. A similar scale to the one used in the Kansas State studies were chosen:

-3 cold

— Z cool

-1 slightly cool

0 neutral

+1 slightly warm

+2 warm

+3 hot

The numerical values however are lower by 4. A scale is thus obtained which is easier to remember, as it is symmetrical around the zero point, so that a positive value corresponds

to the warm side and a negative value to the cold side of neutral. He then proposed that th

thermal sensation values, to be called the Predicted Mean Vote (PMV) , would be a function

of the thermal load of the body, defined as the difference between the internal heat production and the heat loss to the actual environment for a man hypothetically kept at the

comfort values of the mean skin temperature and the sweat secretion of the actual activity

level.

PMV = f (M - .^^ - E - E - D - R - C) (4) diff sw res The nature of equation (4) enabled Fanger to use the same component expressions as in the

general comfort equation. The particular form of the function was determined from analyzing

the Kansas State studies once again as well as similar experiments conducted at the Technica

University of Denmark.

Values of the predicted mean vote (PMV) are shown on the psychrometric chart in Figure

B6. The data was calculated assuming a resting metabolic rate (M = 50 kcal/h.m^) , an air

velocity of 0.1 m/s, a mean radiant temperature equal to the ambient air temperature, and

a clothing insulation value of 0.6 clo. In Figure B7 the results are compared with the

experimentally determined KSU comfort vote. As can be seen the agreement is excellent for

the comfort line (KSU = 0, PMV = 4) but not so good for environmental conditions outside

of the comfort range.

An advantage of an analytical model such as this is the capability of observing the

effect of one of the six controllable parameters without having to conduct extensive ex- periments. For example, it may be unrealistic to determine air conditioning criteria using

subjects that wear the standard 0.6 clo clothing ensemble. Certainly in hot weather people

would be more inclined to wear lighter clothing such as shorts and an open neck shirt with

short sleeves. Data for this type of clothing ensemble (clo = 0.25) is shown in Figure B8

and compared with the standard Kansas State clothing ensemble in Figure B9. The comparison

shows what one might intuitively expect. With lighter clothing, subjects would report comfort at 4 or 5 °F (2.2 or 2.8 °C) warmer temperature. It would be expected that they would

vote cool at a somewhat higher temperature also (approximately 6 °F or 3.3 °C) . However,

both subjects would vote hot at approximately the same temperature and relative humidity.

Instead of just giving the predicted mean vote as an expression for the thermal environ

ment, Fanger felt it might be even more meaningful to state what percent of persons can be

expected to be decidedly dissatisfied since this can readily be interpreted by both the

engineer and the layman. This same concept has been proposed more recently by Nevins and

McNall [17]. After choosing the limits of -2 and +2 for being dissatisfied on the cold and

hot side respectively, the American and Danish experiments already mentioned were again

analyzed to determine the percent of the subjects voting cool or below and warm or above

at each envirotiment condition. The same relationship was assumed to hold between PMV and

the new factor, predicted percentage of dissatisfied (PPD) . The exact relation is given

below.

7b
The relevant mathematical relations used by Fanger in his work were:

Rate of Heat Loss by Convection (C)

:

C = A f , h (T ^ - T ) kcal/h

DU cl c cl a

h = 2.05 (T , - T )°*^^ for 2.05 (T , - T

)*^"^^

> 10.4

c cl a cl a = 10.4 /vT for 2.05 (T , - T )°*^^ < 10.4 /v~ cl a

Rate of Heat Loss by Radiation (R)

:

R = 4.8 X 10"^ f^^ f^^^ [(T^^ + 273)"^ - (T^^ + 273)^] kcal/h

Rate of "Dry" Heat Loss in Respiratory Passages (D)

:

D = .0014 M (34 - T ) kcal/h

a

Rate of Energy Loss Due to Evaporative Cooling in Respiratory Passages (E^^g) '

E = .0023 M (44 - P ) kcal/h

res a

Rate of Energy Loss Due to Evaporative Cooling, Normal Skin Diffusion (E^^££)

:

^diff = .35 (43 - 0.061 - P ) kcal/h

Rate of Energy Loss Due to Evaporative Cooling, Regulatory Sweat Production (E^^)

:

^sw = V ^4 " ^'"'^"^

Rate of Heat Conduction Through Clothing (K)

:

^sk - '^cl ^ = ^l8 I^ ^"^^'^

cl

Relation Between PMV and Body Heat Load (L)

:

PMV = [.352 e"*^^^ + .032] L

Relation for PPD:

A second order equation was fit to the tabular data given by Fanger' for the Predicted

Percentage of Dissatisfied (due to heat only) as a function of PMV:

PPD = 1.63 + 10.98 (PMV) + 13.41 (PMV)^

New Effective Temperature (ET*)

The other major analytical contribution to the field of thermal comfort to be mentioned

in this paper is a transient heat transfer model presented by Gagge, Stolwijk, and Nishi [18].

The model differs most significantly from Fanger 's in the fact that physiological responses

have included the effect of vascular restrictions and dilation on the blood flow to the skin

and regulatory sweating proportional to a deep body temperature deviation from some predetermined set point. The human body is pictured as composed of two distinct parts; a central core

and skin shell. An energy balance is written for each part:

8b
the rate of

energy in- crease of the

skin shell

and

the rate

of energy

increase

of the

central

core

or in equation form

M , C dT

the net rate

of energy

transfer from

the core to the skin

the rate

of energy

generation

(metabolic

production

in the core

sk

sk^sk dt ^con

''^ %1 "diff

the net rate

of energy

transfer from

the skin to the core

E - R rsw

the net rate

of energy

transfer from

the environment to the

skin

the net rate of

energy transfer

from the environ- ment to thB core

(3)

and

dT

M C cr cr dT = M (6)

where

^sk

=

'sk

sk

Ediff

Ersw

mass of the skin shell

specific heat of the skin shell

temperature of the skin shell

mass of the central core

specific heat of the central core

temperature of the central core

time ~

= heat transferred by conduction from the core to the skin

(a function of T and T , ) cr sk

= energy transferred by blood flow from the core to the skin

(a function of T and T , ) cr sk

= the energy loss by water vapor diffusion through the skin

= the energy loss by evaporation as a result of regulatory sweat production (a function of T^^ and T^^^)

R = the heat loss by radiation from the skin to the environment

C = heat loss by convection from the skin to the environment

cr

T

^bl

This particular component is extremely important in the performance of the model yet th

expression doesn't agree with all physiological observations reported in the literature

A discussion of this discrepancy is given in Appendix C.

9b
M = metabolic heat production in the core

E = the latent respiration loss from the lungs

res . °

The form of the differential equation implies a lumped capacity analysis or in other words

5

the temperature of the skin and core are assumed' uniform throughout at every instant. The

model is no doubt unrealistic in this respect, since the temperature can and does often vary

widely within the body. Recently another dynamic model [19] has been developed in which 25

nodes (instead of 2 in the present model) are used to represent the thermal characteristics

of the body, with four nodes each representing the head, trunk, arms, hands, legs and feet.

The twenty-fifth node represents the central blood,

After formulating expressions for the various energy components and choosing appropriate

numerical values for the various parameters (see below) , the two differential equations are solved simultaneously (numerically ' on a digital computer) to predict the time variation of

the core and skin temperatures when the controllable parameters mentioned previously are specified. The model predicts a response that levels off at the end of approximately one

hour. Once T and T have been determined, it is possible to work back through the analysis

and calculate 'ihe regulatory sweat production (at the end of one hour) , associated with the

given environmental-human conditions. Mass transfer theory is then used to calculate the

maximum possible evaporation cooling for given skin temperature and ambient temperature and

vapor pressure. The ratio of calculated regulatory sweat evaporation to the maximum possible

is given the notation of skin wettedness. It is then postulated (3.3 a result of experimental

observation) that in warm environments, various conditions giving the same skin wettedness

will also cause the same thermal sensation or feeling of warmth or coolness. This particular

point is debatable and is the subject of discussion in Appendix C.

Lines of constant skin wettedness at the end of one hour's exposure are shown in Figure

BlO for a testing subject (58.2 W/m^) with the standard clothing (0.6 clo) subjected to a small air velocity. This model has been proposed to ASHRAE and accepted as properly predicting the lines of constant thermal sensation. Consequently the lines in Figure BIO are labelled

as lines of New Effective Temperature (ET*) . Actually the model predicts zero regulatory

sweating at 77 °F (25 °C) and 50% R.H. or in other words, the 77 ET* lines correspond to a skin wettedness of 0. Effective temperature lines below this temperature are simply drawn as parallel to the 77 ET* line. The numerical values associated with the lines were determined

by using the dry-bulb temperature at the intersection of the constant skin wettedness line

and the 5Q% relative humidity curve. This in contrast to the original effective temperature

where experimentally determine lines of constant thermal sensation were given numerical values

corresponding to the dry-bulb temperature where the lines intersected the saturation or 100%

relative humidity eurve. The labelling 'of the new effective temperature seems more reasonable

since the values will more closely correspond to dry-bulb temperatures experienced in everyday living. However, the confusion that results from the two effective temperature scales can

be seen by observing Figure Bll. The numerical values of the two scales are very widely

separated. Since the old effective temperature was considered standard for almost 50 years,

many guidelines and comfort limits will have to be reevaluated in terms of the new scale.

By observing the new scale, one sees that the dependence of thermal sensation on relative

humidity at the higher temperatures is approximately the same as with the old effective temperature. This is quite acceptable since the old effective temperature scale was considered

accurate at these temperatures. However, at temperatures near the comfort zone, the new model

predicts a much less dependence on relative humidity which is in good agreement with the most

recent studies. These two factors no doubt contributed significantly to the new scale's

acceptance by ASHRAE.

The component expression used by Gagge, et . al. are as follows:

Rate of Heat Loss by Convection (C)

:

C = h (T , - T ) F ^ W/m^

c sk a cl

h^ = 11.6 v°"^ W/(m^.°C)

10b
Rate of Heat Loss by Radiation (R)

:

R = h (T , - T ) F , W/m^

r sk a cl

Rate of Energy Loss Due to Evaporative Cooling in Respiratory Passage (E :

E = .0023 M (44 - P ) W/m^

res a

2 M = metabolic heat production, W/m

Rate of Energy Loss Due to Evaporative Cooling, Normal Skin Diffusion (E.^^^): dltr

E, 0.06 • 2.2 h (P , - P ) F , W/m^ diff c sk a pel

h = convection coefficient given in the previous

^ section, W/(m2.°C)

Rate of Energy Loss Due to Evaporative Cooling, Regulatory Sweat Production (E^^^)

:

E = 70 (T - 36.6) (T , - 34.1) W/m^

rsw cr sk

for T > 36.6 °C and T , > 34.1 °C cr — sk —

E = 0.0 rsw

for T < 36.6 °C or T , < 34.1 °C cr sk

Maximum Evapotative Cooling Rate Possible (E )

:

max

E =2.2h (P,-P)F , W/m^ max c sk a pel

h = convection coefficient given in the previous

section, W/(in2.°C)

Heat Stress Index

The heat stress index was developed by fielding and Hatch at the University of Pittsburgh

and first published in 1955 [20]. The postulation that forms the basis of their index is as follows: the metabolic production of the body minus the energy that can be given off by

radiation and convection to the surroundings equals a quantity of energy that must be given

off by sweat evaporation in order to maintain thermal equilibrium with the environment. Consequently the expression for the required evaporative cooling (E^^^) is

E = M - R - C (7)

req

As mentioned previously, for a given skin temperature and ambient air temperature and vapor

pressure, mass transfer theory can be used to calculate the maximum evaporative cooling possible. The heat stress index is defined as being equal to the ratio of the two quantities

^req/^max multiplied by 10. fielding and Hatch assumed a constant skin temperature of 35 °C and used the most up-to-date (at that time) expressions for radiation and convection heat

loss from the body to calculate values of the index and present them in nomographs as functions

of the metabolic production and environmental conditions. In addition, physiological and

hygienic implications of 8 hour exposures to various heat stresses were given and are shown

in Table fil. lib
Calculations have been made using the original expressions for radiation and convection

losses and maximum evaporative cooling from the body for a resting person subjected to a uniform environment with an air velocity of 20 fpm (0.1 m/s). The results are shown in

Figure B12 in the form of lines of constant heat stress index. Notice that using these ex- pressions sweat evaporation to maintain body equilibrium is not required until the environment reaches approximately 82 °F (27.8 °C) . This is in definite contrast to Gagge's

effective temperature model which shows regulatory sweat production starting at approximately

5 °F (2.2 °C) lower. The expressions were reevaluated and updated in 1966 by McKarns and

Brief [21]. ASHRAE recommends in their 1972 Handbook of Fundamentals [13] the calculation

of the index using the same expressions for R, C and Em^x that were used in the new effective

temperature model. In addition, expressions for dry and latent heat losses from the lung

passages have been subtracted from the right side of equation (7) and the results of new

calculations are shown in Figure B13 and compared with the original lines of constant heat

stress in Figure B14. The latest computations seem to be reasonable since the evaporative

cooling as a result of sweat production is seen to be necessary at a temperature as low as

74 °F (23.3 °C).

In retrospect, it can be seen that the quantity called skin wettedness in the new effective temperature model is very similar to a heat stress index. Instead of dividing the maximum

possible evaporative cooling rate into a required evaporative cooling rate, the maximum value

is divided into a sweat cooling rate that is predicted from known physiological responses.

As stated above, the expressions for C, R, E^^ , E^^^^, and E^g^^ used in computing the

heat stress index according to ASHRAE [13] are identical with those used in computing ET*.

In addition, the expression for D was:

D = .0014 M (34 - Tg) W/m^

2 M = metabolic heat production, W/m

The component equations used in calculating HSI (original) are as follows:

Rate of Heat Loss by Convection (C)

:

C = 2 v*^*^ (95. - T ) Btu/h

a where

v = air velocity, fpm

T^ = ambient air temperature, °F

Rate of Heat Loss by Radiation (R)

:

R = 22 (95 - T^^) Btu/h

T = mean radiant temperature, °F MRi

Maximum Evaporative Cooling Rate Possible (E )

:

max

E = 10 v-'^ (P , - P ) Btu/h max sk a V = air velocity, fpm

Thermal Comfort VJhen Equilibrium is Maintained by Sweating

Before publishing a new effective temperature model, Gagge and his associates published

still another model for indicating thermal comfort [22] that is very similar to the heat

stress index. The cooling due to evaporation of sweat production necessary to maintain body

thermal equilibrium is determined by subtracting the body heat loss by radiation, convection,

latent loss from the lung passages and the loss due to evaporation of moisture diffusing

12b
through the skin from the metabolic heat production. The resulting required evaporative

cooling is divided by the maximum possible and then multiplied by 100 to give a factor

"percentage of wettedness".

The main difference between this model and the two previous ones mentioned is that the

skin temperature is not held constant as in the case of heat stress index or predicted from

known physiological responses as with the new effective temperature model, but rather assumed

to be a polynomial function of the environment temperature (see below) . The function was determined by fitting an equation (by regression analysis) to experimental data that was determined at the John B. Pierce Foundation. Computations were made using the model and

the results are shown in Figure B15 for a resting person with the standard clothing (0.6 clo)

subjected to a uniform environment with an air velocity of 20 fpm (0.1 m/s)

.

The equations used in computing the values of C, R, Ej-gg. and E^^^^ were identical to those used in computing ET* . In addition, the following two expressions were used:

Rate of Energy Loss Due to Evaporative Cooling, Normal Skin Diffusion (E^^^^)

=

E, .^^ = .35 (P . - P ) F , W/m^ • diff sk a pel

Relation for Skin Temperature as a Function of Ambient Air Temperature;

T , = 25.49 + .249 T °F sk a

Index of Thermal Stress

Givoni [23, 24] has done extensive work over the past few years on measuring and evaluating heat stress. Having compared actual response with the predictions of many models and

found much disagreement, he developed his own "index of thermal stress" (ITS) which according

to additional extensive experiments conducted by Givoni correctly predicts the physiological

strain imposed on resting and working people by metabolic and environmental factors. The

index is structured exactly like the heat stress index with two important differences. An expression has been included for the radiant heat load due to solar radiation so that the

index can predict responses for people working or resting outdoors. This is not directly

applicable to this study but certainly makes a useful addition to the field of heat stress evaluation. The other difference is a factor called cooling efficiency of sweating (f) and

is included in the equation as follows:

E = [M - R - C] ^ (8) req f The concept is that v/here other indices assume all the sweat produced or required is evaporated

and provides cooling for the body, this may not be true. For example, some of the evaporation

could occur in the clothing and not result directly in cooling for the body. Calculations

using Givoni 's expressions have been made and are shown in Figure B16 . The data used was for

a resting person _ 100 kcal ^ subjected to a uniform environment with an air velocity of

.1 m/s. The clothing ensemble chosen (affects the radiation and convection , expression) was

very similar to the Kansas State standard clothing. It should be noted that the upper limit

for comfort (according to Givoni) is associated with an evaporative loss of 60 g/h and

that distinct thermal discomfort is experienced progressively as the sweat rate is elevated

above 100 g/h.

Even though Givoni states that the model predicts a sweat rate that is in agreement with

experimentally measured rates, the results shown in Figure B16 appear questionable. Sweating

is seen necessary at approximately 64 °F (17.8 °C) . The index does show small dependence on relative humidity at the lower temperatures and somewhat more dependence at the higher temperature which agrees with the new effective temperature model. However, it should be remembered

that what is shown in the figure is sweat rate and not the ratio between the sweat rate and some maximum possible.

13b
The equations used to calculate the values of ITS are as follows

:

Rate of Heat Loss by Convection (C)

:

C = a v°*^ (35 - T ) kcal/h - a

Rate of Heat Loss by Radiation (R)

:

accounted for in the convection term by replacing *^ T by T,^„ ^ a •' MRT

Maximum Evaporative Cooling Rate Possible (E^^) •

E = P v"^ (42 - P ) kcal/h max a

Relation for Sweating Efficiency:

1 0.6 (E /E - 0.12)

J

= e req max

Predicted Four Hour Sweat Rate

The P4SR index was developed by McArdle and his colleagues during World War II at the

Royal Naval Research Establishment [25]. Sweat rate was measured for fit, young men dressed

in shorts only or overall and shorts when subjected to many different combinations of temperature, humidity, and air velocities for four hour periods. The results were presented in

the form of nomographs and have been adapted to a psychrometric' chart as shown in Figure B17.

The particular conditions for this chart are a metabolic production of 54 kcal/ (m • h) , a uniform radiation environment (mean radiant temperature equal to air temperature) , and an

air velocity of 10 fpm (0,05 m/s). As was the case with the original heat stress index, sweat production is shown to start only after the temperature has reached approximately

80 *F (26.7 °C) . Based on the experiments, a limit of 3.0 was established as the upper

tolerable limit for dally exposure.

Wet-Dry Index

In 1957 Lind and Hellon [26] proposed the use of the Oxford Index or wet-dry index

to assess the severity of hot climates. It is simply a combination of the wet-bulb and

dry-bulb temperatures (°F) according to

WD = 0.85 T , + 0.15 T,, wb db

The extreme dependence on relative humidity is obvious and is shown in Figure BIS. Due to its simplicity it has been used quite often in setting limits or correlating data in extremely

hot and wet conditions where there is no radiant stress and very low air velocity.

Temperature-Humidity Index

Another index very similar to the Oxford Index is one called the temperature-humidity

index defined by

THI = 0.4 (T,, + T , ) + 4.8 db wb

where all values are in °C. This index like the last, attempts to combine the effect of

temperature and humidity in environments where radiant stress and air velocity are not

important. Figure B19 shows that the THI index is much less dependent on humidity than the

14b
W-D index was. As an example of its use, Bridger and Half and [27] correlated death rates during the 1966 heat^ wave in St . Louis and found that when the 24 hour average of the THI was greater than 81 °F (27 -"C) , there was an usually large number of deaths due to heat

stroke.

Table B2 has been included here as a summary to give the range of application of the

various indices that have been discussed.

15b
References

1. F. C. Houghten and C. P. Yaglou, "Determination of the Comfort Zone", ASHVE Transactions , Vol. 29, p. 361, 1923.

2. T. Bedford, "Environmental Warmth and Its Measurement", MRC War Memorandum No. 17, HMSO,

London, 1946.

3. N. Koch, B. H. Jennings and C. M. Humphreys, "Sensation Responses to Temperature and

Humidity Under Still Air Conditions in the Comfort Range", ASHRAE Transactions , Vol. 66,

p. 264, 1960.

4. H. Missenard, "Equivalences thermiques des ambiences; equivalences de passage; equivalences

de sejour", Chaleur et Industrie , July-August, 1948.

5. R. G. Nevins, F. H. Rohles, W. E. Springer, and A. M. Feyerherm, "A Temperature Humidity

Chart for Thermal Comfort of Seated Persons", ASHRAE Transactions , Vol. 72, Part 1,

1966.

6. R. G. Nevins and F. H. Rohles, "The Nature of Thermal Comfort for Sedentary Man", ASHRAE

Transactions, Vol. 77, Part 1, 1971.

7. 0. Seppanen, P. E. McNall, D. M. Munson, and C. H. Sprague, "Thermal Insulating Values

for Typical Clothing Ensembles", ASHRAE Transactions , Vol. 78, Part 1, 1972.

8. F. H. Rohles, "Psychological Aspects of Thermal Comfort", ASHRAE Journal, Vol. 13, pp. 86-90, 1971.

9. F. H. Rohles, "The Modal Comfort Envelope - A New Approach Toward Defining the Thermal

Environment in Which Sedentary Man is Comfortable", ASHRAE Transactions , Vol. 76, pp. 2.1-2.8, 1970.

10. F. H. Rohles, "The Revised Modal Comfort Envelope", ASHRAE Transactions , 1973.

11. F. H. Rohles and M. A. Johnson, "Thermal Comfort in the Elderly", ASHRAE Transactions , Vol. 78, pp. 131-137, 1972.

12. F. H. Rohles, J. E. Woods, and R. G. Nevins, "The Influence of Clothing and Temperature

on Sedentary Comfort", ASHRAE Transactions , 1973.

13. ASHRAE Handbook of Fundamentals , ASHRAE, 345 East 47th Street, New York, New York 10017,

1972.

14. ASHRAE Standard 55-74, "Thermal Environmental Conditions for Human Occupancy", ASHRAE,

345 East 47th Street, New York, New York 10017, 1966.

15. F. H. Rohles and R. G. Nevins, "Thermal Comfort: New Directions and Standards",

Aerospace Medicine , Vol. 44, Part 7, pp. 730-738, 1973.

16. P. 0. Fanger, Thermal Comfort , Danish Technical Press, Copenhagen, 1970.

17. R. G. Nevins and P. E. McNall, Jr., "Proposed Classification of Human Response to the

Environment", ASHRAE Journal , pp. 44-47, June 1971.

18. A. P. Gagge, J. A, J. Stolwijk, and Y. Nishi, "An Effective Temperature Scale Based on

a Simple Model of Human Physiological Regulatory Response", ASHRAE Transactions , Vol. 77, Part 1, 1971.

19. J. A. J. Stolwijk, "A Mathematical Model of Physiological Temperature Regulation in Man",

NASA Report CR-1855, August 1971.

20. H. S. Belding and T. F. Hatch, "Index for Evaluating Heat Stress in Terms of Resulting

Physiological Strain", Heating, Piping, Air Conditioning , VoL27, p. 129, 1955.

16b
21. J. S. McKarns, and R. & Brief, "Nomographs Give Refined Estimates of Heat Stress Index",

Heating, Piping and Air Conditioning, Vol. 38, p. 113, 1966.

22. A. P. Gagge, J. A. J. Stolwijk, and Y. Nishi, "The Prediction of Thermal Comfort When

Equilibrium is Maintained by Sweating", ASHRAE Transactions , Vol. 75, Part II, p. 108,

1969.

23. B. Givoni, Man, Climate, and Architecture , Elsevier Publishing Company, 1969.

24. B. Givoni, "Estimation of the Effect of Climate on Man: Development of a New Thermal

Index", Research Report to UNESCO, Building Research Station, Technion, Haifa, Israel,

1963.

25. B. McArdle, W. Durham, H. E. Holling, W. S. S. Ladell, J. W. Scott, M. L. Thomson,

and J. S. Weiner, "The Prediction of the Physiological Effects of Warm and Hot Environments", MCR R. N. P., Vol. 47, p. 391, 1947.

26. A. R. Lind, and R. F. Hellon, "Assessment of Physiological Severity of Hot Climates",

Journal of Applied Physiology , Vol. II, p. 35, 1957.

27. C. A. Bridger and L. A. Halfand, "Mortality From Heat During July 1966 in Illinois",

Int . Jour . Biomet . , Vol. 12, p. 51, 1968.

17b
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Tabl^ Bl Evaluation of Index of Heat Stress

Index of

Heat

Stress

Physiological and Hygienic Implications of 8-Hr Exposures to Various Heat Stresses

No thermal strain

Mild to moderate heat strain. Where a job involves

higher intellectual functions, dexterity, or alertness, subtle to substantial decrements in perform- ance may be expected. In performance of heavy physical work, little decrement expected unless ability of

individuals to perform such work under no thermal

stress is marginal.

Severe heat strain, involving a threat to health

unless men are physically fit. Break-in period

required for men not previously acclimatized. Some

decrement in performance of physical work is to be

expected. Medical selection of personnel desirable , because- these conditions are unsuitable for those

with cardiovascular or respiratory impairment or with

chronic dermatitis. These working conditions are also unsuitable for activities requiring sustained

mental effort.

Very severe heat strain. Only a small percentage of

the population may be expected to qualify for this

work. Personnel should be selected (a) by medical

examination and (b) by trial on the job (after

acclimatization). Special measures are needed to

assure adequate water and salt intake. Amelioration

of working conditions by any feasible means is highly

desirable, and may be expected to decrease the health

hazard while increasing efficiency on the job. Slight

"indisposition" which in roost jobs would be insufficient

to affect performance may render workers unfit for this

exposure

.

The maximum strain tolerated daily by fit, acclimatized

young men.

37b
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38b
Appendlk C

Discussion of Regulatory Sweating Models

Ic
In Appendix B it was noted that the component expression for regulatory sweating in the new effective temperature model contributed significantly to the response of the model. As given in Appendix B, the component expression is

E = 70 (T - 36.6) (T , - 34.1) W/m^ rsw cr sk

for T > 36.6 °C and

cr —

T , > 34.1 °C sk —

E = 0 if T < 36.6 °C or rsw cr

T^j^ < 34.1 °C

The interpretation of this expression is that sweat production is caused by signals from

both the skin and the deep body. If the temperature in either one of the regions rises above

the normal value, then the body secretes sweat for the purpose of evaporative cooling. Thi6

sweating model is in definite contrast to the results of experiments conducted by

Dr. T. H. Benzinger of the Naval Medical Research Institute [1, 2]^. Dr. Benzinger concludes

as a result of his studies, that the signal for sweat secretion is a sole function of the

temperature in the anterior portion of the hypothalamus region of the brain. When this

temperature rises above a sharply determined set point, warm sensitive neurons begin to fire and excite sweating such that the rate of sweat production is directly proportional to deviation beyond the set point.

The skin temperature does play a role in the evaporative cooling process; however, in

contrast to the interpretation of Hardy and Stolwijk [3, 4] (which has been adapted for the new effective temperature model) , Benzinger concludes that the effect is one of inhibition.

Whenever the skin temperature drops below approximately 33 °C the rate of sweat production

begins to decrease below its normal value (given a hypothalamus temperature above the set point) and the amount of decrease is proportional to the deviation of skin temperature below

33 °C. A comparison between these two distinctly different interpretations is shown in

Figure CI. The rate of evaporative cooling is plotted against the deviation of skin temperature from 33 °C. As can be seen, Gagge's model simulates zero cooling by sweat evaporation

as long as the skin temperature is below 34.1 °C and is directly proportional to (Tgj^ - 34.1)

• (T^^ - 36.6) above this point. Benzinger 's data indicates a constant rate of sweat production whenever the skin temperature is above 33 °C (the value of the rate dependent on

(T(,j. - 36.6)) and a progressively decreasing rate as the skin temperature drops below 33 °C.

The importance of the evaporative cooling in the model can be seen in Figure C2 where

new effective temperature lines are plotted that have been calculated using Benzinger 's results for sweat production. Since his data generally gives larger values of evaporative

cooling for specified core and skin temperatures, it would be expected that this modified

scale would show more dependence on humidity than the standard new effective temperature

lines and this can be seen in Figure C3. It is not recommended that the new data be used

in the simulation of the body response since the experiments used to generate them were very

special in nature. Men were enclosed in a gradient calorimeter [5] such that all sweat evaporated could be instantly carried away. This may not be true in ordinary environments,

particularly where the humidity of the ambient air is high. However, it should be obvious

that much more study and refinement is needed before an accurate simulation of human response

to an environment can be accomplished.

The interpretation that lines of equivalent thermal comfort are identical with lines of constant sweat ratio could be adjusted in light of Dr. Benzinger 's findings. The feeling of

thermal comfort is no doubt linked to the necessity for sweat secretion when subjected to warm environments. However, as a result of his studies this is in turn linked directly to the

hypothalamus temperature or deep body temperature since this is the sole source of the sweating signal. The reasoning is substantiated by an additional experiment conducted by him.

Reference numbers refer to references listed at the end of this Appendix.

2c
A subject was cooled in a tank of cold water until the hypothalamus temperature was well

below the individual's set point. He was then put into a very hot bath where the skin

temperature and hypothalamus temperature were monitored with time. Even though the skin

temperature went to a relatively high value almost immediately, the subject did not report

discomfort until the hypothalamus temperature began to rise above his set point.

References

1. T. H. Benzinger, "Clinical Temperature, New Physiological Basis", Journal of the

American Medical Association , Vol. 209, pp. 1200-1206, 1969.

2. T. H. Benzinger, "Peripheral Cold Reception and Central Warm Reception, Sensory

Mechanisms of Behavioral and Autonomic Thermostasis" , Physiological and Behavioral

Temperature Regulation, Chapter 56, Charles C. Thomas, Springfield, Illinois, 1970.

3. J. D. Hardy and J. A. J. Stolwijk, "Partitional Calorimetry Studies of Man During

Exposure to Thermal Transients", Journal of Applied Physiology , Vol. 21, pp. 1799-1806,

1966.

4. J. A. J. Stolwijk and J. D. Hardy, "Temperature Regulation in Man - A Theoretical

Study", Pflugers Archiev. , Vol. 291, pp. 129-162, 1966.

5. T. H. Benzinger and C. Kitzinger, "Gradient Layer Calorimetry and Human Calorimetry",

Temperature - Its Measurement and Control in Science and Industry. Vol 3, Part 3,

Reinhold Publishing Corp., N.Y., N.Y., 1963.

3c
O OOOOOOOOOOl

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5c
6c
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NBS-114A (REV. 7-73)

U.S. DEPT. OF COMM. BIBLIOGRAPHIC DATA

SHEET

1. PDHI.K A riON OK KI-.POK r NO. NBS BSS 71

2. (lov't Accc'S.sion No.

4. TITLE AND SLIinTl Li- A Proposed Concept for Determining the Need for Air Conditioning

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7. AUTHOR(S)

J. E. Hill, T. Kusuda, S. T. Liu, and F. J. Powell

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Department of Housing and Urban Development

451 Seventh Street, S.W.

Washington, D. C. 20410

13. 1 ype of Report & Period Covered fi^^Ll " June

1971 - December 1974

14. Sponsoring Agency Code

15. SUPPLEMENTARY NOTES

Library of Congress Catalog Card Number: 75-619194

16. ABSTRACT (A 200-word or less factual summary of most significant information. If document includes a significant

bibliography or literature survey, mention it here.) Determining the need for air conditioning can be based on a wide variety of factors. To

date, the only criteria that have been written and can be referenced are those of several federal organizations and many are not really criteria in the true sense of the word

They are guidelines to be used in the determination of fund allocation; in other words,

provisions are made to air condition federal facilities in specific geographical locations if pertinent weather characteristics of that locality meet certain requirements.

This paper presents the concept that a true criteria can be established based both on weather characteristics of the locality as well as characteristics of the building or structure under consideration.

The paper gives the details of a study showing the feasibility of such a scheme. A sim

ulation was made of two proposed residences in several geographical localities. For the

simulation, actual hour-by-hour weather data was used in conjunction with a sophisticated

computer program. The results revealed for the non air-conditioned spaces, the extent

and duration of undesirable indoor conditions based upon generally accepted comfort indices. The concept of a new "comfort" or "discomfort" index called Predicted Indoor Hab

itability Index (PIHI) is introduced. The authors indicate the way in which a criterion

could be established that would be in the form of tables, indicating for a given specified building and geographical locality, whether mechanical cooling should or should not

be installed.

17. KEY WORDS (six to twelve entries; alphabetical order; capitalize only the first letter of the first key word unless a proper name; separated by semicolons

)

Air conditioning criteria; building thermal response; comfort indices; human comfort;

predicted indoor habitability index

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