Reference publications

NBSIR 85-3229

Estimating Interroom

Contaminant Movements

AlllDb 034154

George N. Walton

U.S. DEPARTMENT OF COMMERCE

National Bureau of Standards

National Engineering Laboratory

Center for Building Technology

Gaithersburg, MD 20899

August 1985

Issued November 1 985

Prepared for: *ce of Buildings and Community Systems

-QC . Department of Energy

100 shington, DC 20585

. U56

85-3229

1985

NBSIR 85-3229

BESSAEC:-!

CEi'rr?.

ESTIMATING INTERROOM

CONTAMINANT MOVEMENTS

George N. Walton

U S. DEPARTMENT OF COMMERCE

National Bureau of Standards

National Engineering Laboratory

Center for Building Technology

Gaithersburg, MD 20899

August 1985

Issued November 1985

Prepared for: Office of Buildings and Community Systems

U.S. Department of Energy

Washington, DC 20585

U.S. DEPARTMENT OF COMMERCE, Malcolm Baldrige, Secretary

NATIONAL BUREAU OF STANDARDS, Ernest Ambler. Director

ABSTRACT

Development of infiltration and interroom airflow calculation methods, driven

by a concern for indoor air quality have led to a computer simulation of

interroom contaminant movement. The model, which assumes fully mixed room

air, shows that open doorways provide rapid mixing between rooms in buildings

using forced air heating. It also confirms that it is most energy efficient

to remove the contaminant nearest its source. Detailed modeling of the

variations in contaminant concentration within a room is not presently

feasible. The concept of ventilation effectiveness should provide sufficient

accuracy and reasonable computing speed to be added to some existing energy

analysis programs. Current energy analysis programs with long timesteps tend

to run into convergence problems when solving the system performance and

interroom airflows simultaneously. Short timestep simulation may be required.

The need for computer modeling is demonstrated by the subtle behavior of a very simple system which removes contaminants by forced ventilation.

i
PREFACE

This report is one of a series documenting NBS research and analysis

efforts in developing energy and cost data to support the Department of

Energy/Nat ional Bureau of Standards Measurements Program. It was prepared

by the Thermal Analysis Group, Building Physics Division, Center for

Building Technology, National Engineering Laboratory, National Bureau of

Standards (NBS). This work was jointly sponsored by the Building Systems

Division, Office of Buildings and Community Systems, U.S. Department of

Energy, and by NBS. The development of multi-room airflow modeling was

conducted under the DoE/NBS research project entitled,

"Infiltration/Ventilation — Large Buildings, and was supported by DoE/NBS

Task Order 008 under Interagency Agreement Number DE-AI01-76PR06010. This

report describes calculations and a computer program which were written as part of an effort to develop a comprehensive modeling technique for

predicting the simultaneous transfer of heat, moisture, air, and

contaminants in and through multi-room buildings.

11
TABLE OF CONTENTS

Page

Abstract i

Preface . ii

List of Tables iv

List of Figures v

Introduction 1

Contaminants 1

Multiple Room, Single Zone Model 2

Sample Calculations 3

Two Zone Intra-Room Model 5

System Interactions 5

Summary and Conclusions 9

References 10

in
LIST OF TABLES

Table 1. Sample Calculation for Contaminant Migration

Pggje

11

iv
LIST OF FIGURES

gage

Figure 1. Floor plan of example house 12

Figure 2. Contaminant concentrations for three levels of house

leakiness 13

Figure 3. Contaminant concentrations in three rooms of one house

(case 3) 14

Figure 4. Infiltration response for a building with only upwind

and downwind openings 13

Figure 3. Infiltration response for a building with openings on four 8 ides 16

Figure 6. Infiltration response for various wind directions 17

v

INTRODUCTION

The removal of odors and contaminants and the provision of adequate amounts of

fresh air is a requirement for any occupied space. Buildings without

mechanical ventilation systems do this by natural infiltration, but

uncontrolled infiltration leads to many hours with excessive infiltration

which results in a large energy cost. Therefore, it is usually recommended

that infiltration be minimized and ventilation be done mechanically as required. However, even mechanical ventilation systems may not be performing

well. A recent study [1] found that most of the buildings studied operated at near or below the recommended ventilation rate. These low ventilation rates

occured during periods of extreme weather when ventilation was reduced to

conserve energy. Further gains in energy efficiency without sacrificing

comfort or endangering health will require analysis of the migration of

contaminants in buildings. This paper will look at some of the modeling

requirements for estimating contaminant movements within the context of a building energy analysis computer program.

CONTAMINANTS

There are many contaminants potentially present as gasses and particulates in rooms. Among the contaminants of interest [2] are:

radon - a radioactive gas from the earth and some masonry products,

formaldehyde - principally from pressed wood products,

carbon monoxide (CO), carbon dioxide (CO2 ), and nitrous oxides (NO, N0 2

) - from combustion processes,

tobacco smoke - both gasseB and particulates,

particulates - including biomaterials and allergens, and

volatile organic compounds * such as cleaning materials.

The important common characteristic of these different contaminants is that

they mix well with air and are transported through a building primarily by air

movement (rather than diffusion).

Moisture can also be considered a contaminant. Except in dry climates,

accurate analysis of night ventilation must account for the storage and

release of moisture from the building and its furnishings. The behavior of some contaminants may be influenced by humidity. Only the most preliminary

work has been done on determining appropriate absorption coefficients for common building materials and furnishings [3].

The time dependent behavior of a contaminant which is perfectly mixed with the

air in a single room is described by a simple ordinary differential equation.

By perfect mixing it is meant that any gasses or pollutants entering the room mix instantaneously and uniformly. If the contaminant generation and loss

rates are known, there is a simple solution to the equation. Real world

complexities limit the accuracy of such a simple solution. The contaminant

may not be well mixed with the room air. Concentrations are highest at the source and contaminants may preferrential ly drift to certain areas of the

room. Generation and absorption rates may be complex functions of conditions

such as temperature and humidity in the room. The outdoor air ventilation

rate can be difficult to determine, especially for natural ventilation, and

the outdoor air may not mix well with the room air. Buildings contain many

rooms with all processes occuring simultaneously. Such factors make detailed

analysis very difficult.

1
MULTIPLE ROOM . SINGLE ZONE MODEL

Prediction of the time-varying concentration of a contaminant in each room of

a building begins with a mass balance on the airflows into and out of the room

under assumed quai-steady conditions:

2>i + Fs - LFo

+ Fe

(!)

where

= air flow rates into room n (kg/s),

F

s = air handling system supply air flow rate (kg/s),

F

Q = air flow rates out of room n (kg/s),

F

g = air handling system exhaust air flow rate (kg/s).

There is also a mass balance for each contaminant species: the rate of change

of the total mass of a contaminant in a room is equal to the total gains into

the room minus the losses from the room. The contaminant gains may be due to

flows through doors or cracks from other rooms, from air introduced by the air

handling system, and from generation of the contaminant within the room. The

contaminant is removed from the room air by airflows out of the room including

HVAC return air. It may also be removed by various mechanical or natural

absorption and chemical conversion processes. These latter removal mechanisms

may be mathematically combined with the generation mechanism into a single

term in the contaminant mass balance equation — the net generation rate.

Assuming that (1) the contaminant mixes well with the room air (one zone per

room), (2) the contaminant follows the airflows through the building and (3)

the mass of contaminant is very small compared to the mass of room air leads

to the following contaminant mass balance equation:

dC

P nVn W* = 2>iCi + FS CS + Gn

- Cn (^F0 + Fe ) (2)

= room air density (kg/nr*)> = volume of room n (nr*), = contaminant concentration in room n (kg/kg),

= contaminant concentration of incoming air (kg/kg),

= contaminant concentration in the system supply air (kg/kg),

= contaminant net generation rate (kg/s).

There is one contaminant equation per room per contaminant species. The

equations for each species tend to be independent of each other (unless one contaminant strongly influences the net generation rate of another, e.g.,

humidity and formaldehyde). The equations for multiple rooms for a single

species tend to be simultaneous (unless there is no airflow between rooms).

It is relatively easy to add this calculation to a building simulation program

if the program computes the interroom air flow rates. The TARP computer

program [4] computes the interroom airflows by considering the openings in the

walls between rooms and the pressure differences across those openings. The mass flows through the openings are computed by a modified Newton's method

which solves a simultaneous mass balance in all rooms of the building [5].

where

C.l

n

2
Equation (2) is an ordinary differential equation which can be solved by

many methods. The Euler (standard explicit), improved Euler, and fourth-order

Runge-Kutta methods [6] were tested. For a single room interacting with the

outside air, the improved Euler method required the least amount of

computation to achieve a given level of accuracy. However, for multiple rooms interacting with each other, the simple Euler method proved best because any

method which normally allows a longer time step between function evaluations

is using values of which have been updated less recently than if a short

timestep were used. The accuracy was evaluated by considering step changes in

the contaminant generation rate or in the supply air flow rate while other

parameters were held constant. These conditions lead to simple exponential

increases or decreases in the contaminant concentration to some new level.

The new level and the exponential rates can be determined analytically. Time

steps considerably shorter than one hour are required to model rapidly

changing conditions. Time steps of one minute gave concentrations accurate to

within 0.1 percent of the analytic values but required about 40 percent of the

total simulation time. Five minute timesteps used only about 10 percent of

the simulation time with an accuracy of four percent in the transient

solution. The long timestep gives essentially the same result as the short

timestep at the end of one hour. Therefore, programs which are primarily

concerned with houly variations for computing long term average concentrations

can use timesteps of about five minutes.

SAMPLE CALCULATION

The following sample calculation was made to test and demonstrate the

multiroom contaminant calculation combined with the airflow and heat balance

calculations in TARP. A typical ranch style house [7] was chosen for the

study. Figure 1 shows the floor plan of the house which consisted of six rooms and an attic. The six rooms are the dining room, living room and

hallway (D/L) , the kitchen (K), the bath (B), the master bedroom (MB), the

second bedroom (B2), and the third bedroom (B3). Doorways between rooms were

simulated by pairs of openings which allow mixing of air between the rooms. The dining/ living room is heated to 72F. The other rooms are heated only by

natural convection through the doorways. This was done because TARP does not

yet have an air handler model which would distribute air through ducts when

the furnace is on. If the rooms were all controlled to the same temperature,

there would be no mixing between the rooms. The model is therefore

conservative in comparison to an actual forced air system with a central

return in the hallway because the forced air system would have higher flow

rates and more even temperature and contaminant distribution through the

house. Three different combinations of openings in the envelope of the house

were simulated to represent leaky, average, and tight construction (cases 1,

2, and 3, respectively).

Two weather patterns were used. One consisted of values measured on February 22, 1982 at Gaithersburg, Md. The average outdoor air temperature was 37. 3F, the wind speed 5.2 mph, and the wind direction was from the

northwest. The other pattern used constant values (the above averages) of

temperature, wind speed, and wind direction in order to give nearly constant

infiltration. The infiltration causes a drift of air through the house from

the northwest to the southeast. This drift is combined with the interroom

mixing by the mass balance algorithm.

3
In the sample calculation a contaminant is released into the kitchen

three times per day at hours 6, 12, and 18. Infiltration is the only

contaminant removal mechanism. Figure 2 shows the relative hourly contaminant

concentrations in the kitchen for the three envelope leakage areas. The house

with the highest infiltration has the lowest average contaminant concentration

and vice versa as expected. The units of contaminant concentration require

some explanation. Concentration is computed in (kg contaminant /kg air) for

simple implementation in equation (2) and easy conversion to English units.

In the simulation the contaminant is released at a rate of one pound per hour

for one hour. (English units were used in the TARP input because the sample

house is described [6] in English units). Therefore, an average concentration

of 0.001 in figure 2 really means a concentration of that value times the

contaminant generation rate, whatever its value.

Figure 3 shows the contaminant concentration in more detail for case 3

for two hours. The highest concentrations occur in the kitchen — the source

room. The kitchen air mixes primarily with the dining/ living room air because

of the arrangement of the doorways. The other rooms then mix with the

dining/ living room. They all have very similar concentrations. The

concentrations start out nearly identical and the contaminant is released

during the hour between 18 and 19. As contaminant generation begins, the

concentration in the kitchen increases very rapidly. The D/L concentration

increases slowly. The MB concentration increases even more slowly as the

contaminant must mix from the kitchen through the dining/ living room before

mixing with the bedroom. When contaminant generation stops at hour 19, the

kitchen concentration decreases very rapidly as the contaminant mixes

throughout the house. After a few minutes all zones are at essentially the same contaminant concentration. This concentration decays exponentially as infiltration slowly clears the air in all rooms. The rapid mixing is caused

by a temperature difference of about 5F between the dining/ living room and the

other rooms. On a mild day, when the rooms and outside air are all at about

the same temperature and heating or cooling is not needed, there would be very

little airflow between rooms causing contaminant concentrations to be much

higher, especially in the kitchen.

The results of the simulations are summarized in Table 1. As the

infiltration decreases, the heating load decreases, but the average

contaminant concentrations increase. From case 2 to case 3 the infiltration

decreases 48%; the heating load decreases 22% and the average contaminant

concentration increases 87%. Further reductions in infiltration will produce

less reduction in the heating load while greatly increasing the average

concentration. The heating load would be 10.5 kBtu/h even if there were no infiltration. The differences between the constant weather and the variable

weather are not significant. A fourth case is presented where a fan is on in

the kitchen during the hours when the contaminant is produced. This fan

removed air from the kitchen at a rate of four kitchen volumes per hour (64

cfm) . Otherwise, the house is identical to case 3. The heating load is

reduced 18% relative to case 2 while the average contaminant concentration is

increased only 37%. This sample calculation shows that it is energy efficient

to remove the contaminant nearest its source. In fact, this predicted

contaminant concentration is a very conservative value because the contaminant

fully mixes with the kitchen air before the mixture is removed. In actual

practice the fan should be located near the contaminant before it mixes

throughout the room.

4
TWO ZONE INTRA-ROOM MODEL

The discussion on the use of an exhaust fan indicates that the fully mixed

room model is too simple for evaluating ventilation performance. However, a detailed model of the motion of air within a room requires numerical solution

of the turbulent Navier-Stokes equation together with the energy and mass

diffusion equations such as demonstrated by Ishizu and Kaneki [8]. This is a very time consuming calculation. The concept of ventilation efficiency has

been developed as a simple model for the simulation of room air flow [9,10].

In these references it is shown that ventilation for cooling is much more

effective when outdoor air is introduced at low velocity near the floor and

removed near the ceiling. This ventilation strategy is more effective than if

the room and ventilation air are uniformly mixed. Both cases are much more

effective than situations in which the ventilation air travels directly from

inlet to exhaust leaving stagnant air in much of the room. Experimental

studies [9,10] have confirmed that air movement within a room can often be

modeled as two fully mixed zones, upper and lower, when given appropriate

values for inflow, outflow, and a mixing coefficient between the zones. Study

is needed for recommending appropriate mixing values.

Equation (2) can be used with the two zone problem by applying it to each

zone. The subscripts which referred to rooms will now refer to the upper and

lower zones in each room. The flows between zones in the same room will

usually be much greater than the flows between rooms. It is therefore best

that the pair of equations for the two zones in a single room be solved

simultaneously (i.e. an algebraic solution rather than iterative) at each

timestep as part of the Euler solution for all rooms of the building. This

calculation was tested and found to have no numerical problems such as convergence, and it gave correct results for the limiting cases of very high

and very low mixing between the two zones of one room.

The calculation of the room air temperature should also be modified to

compute the temperatures of both zones. This is one method of simplified

stratification modeling. Again the temperatures of the upper and lower zones

of one room should be calculated simultaneously. There are significant

questions as to how the zones interact convectively with the room surfaces.

It is not as simple as having convective heat and mass transfer between the zone and the surface. For example, there is a strong tendency in still air

for the air that is near a warm vertical surface to rise in a boundary layer

along the surface and mix only with the air in the upper zone. Convective

gains from warm objects in the room may behave similarly with plumes of warm

air carrying heat (and contaminants) predominantly into the upper zone. There

is not yet enough information on the coefficients which would describe such

processes to justify the major modifications that would be required to

incorporate these effects into TARP.

SYSTEM INTERACTIONS

The operation of the air distribution system will normally be the primary

influence on the distribution of contaminants. The following two studies

indicate that the requirement for system simulation will have a significant

impact on the overall building/contaminant simulation program.

5
Most building energy analysis programs do not perform the detailed mass

balance to estimate infiltration. They use simple correlations involving

temperatures and wind speed such as developed by Coblenz and Achenbach [11].

How should forced ventilation flows be combined with the naturally occurring

infiltration? The requirement of a mass balance in each room and in the whole

building must be used in developing a simplified correlation. Based on a study of combustion systems which draw air from the conditioned space, chapter

22 of the ASHRAE Handbook [12] indicates that 70% of the exhaust flow is from

increased infiltration with the remaining 30% from decreased exfiltration.

Another study [13], which considered the effects of electric clothes dryers

vented to the outside, recommended the following correlation.

Iv “ In + Fv e (In/Fv) (3)

where

Iv 9 the infiltration rate with forced ventilation,

In » the infiltration rate with no forced ventilation,

Fv » the forced ventilation rate.

The rather low regression coefficient (0.65) for this correlation and the

great difference from the first correlation raise the question of the

appropriateness of either. The detailed mass balance technique allows a theoretical/numerical study of the effect of forced ventilation on house

infiltration as presented below.

Again consider the empirical equation for flow through a small opening:

F

i - Ki(Pi-Ph) Xi < 4>

the flow rate (m3 /8) through opening i

(positive ° into house; negative out of house),

airflow conductance,

the total pressure (Pa) due to wind and stack effects at the

outside of the opening,

the total pressure at the inside of the opening—the house pressure,

flow exponent, between 0.5 and 1, usually near 0.65 for

leakage openings.

First consider a house where:

all cracks are consolidated into two openings, the first on the upwind

side of the house and the second on the downwind side,

all air flows in at the upwind side Fj = K^P^-P^) , all air flows out at the downwind side F

2 = K 2 (P2-Ph) * the openings are at the same height (no net stack effect),

and let x^ B = 1 and Kj * K2 * K for ease of analytical solution.

A mass balance on the house, which is treated as a single room, requires that

the inward flow through the first opening equal the outward flow through the

second when there is no forced ventilation. Therefore, the house pressure is

given by

where

x. >

l

Ph

" (P

1 + p2)/ 2 (5)

6
Next consider a forced exhaust ventilation rate, Fv. A mass balance leads to

a new house pressure during ventilation, P^

} given by

P

H - (P x + P2 - Fv/K)/2 (6)

which reduces to

P

H = Ph " Fv/(2K) (7)

The natural infiltration rate is

In = K(P

X - Ph

) (8)

The total infiltration with ventilation is

Iv = K(P

X - ph

) (9)

Therefore, the increase in infiltration is given by

Iv - In - Fv/2 (10)

This simply means that the airflow into the zone (the infiltration) has been

increased by one half the forced ventilation rate while the airflow out of the zone (the natural exfiltration) has been increased (made less negative) by the same amount. This is true as long as p

x > pH

> P

2

» If the ventilation rate

i6 large enough, then p

x > P2 > PTM and there is infiltration at the downwind

side of the house also. The total infiltration is then equal to the forced

ventilation rate.

These ideas were tested numerically in a small computer program [3] which

uses equation (4) and the mass balance requirement to compute the airflows

through all openings in the bulding envelope. Figure 4 shows the results for

the house with only two identical openings. The figure relates the relative

increase in infiltration, (Iv-In)/Fv, to the relative infiltration rate,

In/Fv. Three values of the flow exponent, x, are considered: 1.0, 0.65, and

0.5 . Results discussed above (x=l) correspond to a diagonal line where Iv

Fv and a horizontal line where Iv - In = Fv/2. For x=.65 and .5, the relative

increase in infiltration still approaches 0.5 at large In/Fv. These exponents

are more characteristic of actual openings, but an exact solution is

difficult. Levins' correlation [13] is shown for comparative purposes.

One may then consider a house with openings on four sides. Theoretical

considerations similar to those above indicate that the flow through each

opening in the house will increase by Fv/ 4 if the openings are identical and

x=l . A test case is considered with identical openings on walls facing north,

east, south, and west. A wind is assumed to blow from the north. A simplfied

model of the wind effects predicts pressures of 8.47 Pa on the north side,

-3.39 Pa on the east and west sides, and -1.69 Pa on the south side. Figure 5 shows the relative increase of infiltration for three flow exponents. For

x=l , the relative increase is equal to Fv/4 when In/Fv > 1.25, that is, when

there is an inward flow on only the north surface. When In/Fv is less than

0.61, air flows in through all four surfaces, and between 0.61 and 1.25, it

flows in through the north and south walls and out through the east and west

walls. For x=0.65, there is inward flow through only one wall when In/Fv > 2.36, with a relative infiltration increase of about 0.14 . For x-0.5, inward

7
flow through only one wall is not achieved until In/Fv > 5 (beyond the range

of figure 5) with a relative infiltration increase of about 0.07 .

Now consider the effects of wind direction on the simple four-sided

building. The pressure effects of a wind blowing from due north and 15, 30,

and 45 degrees east of north were simulated with the simple model and the

results are summarized in figure 6. For the wind at 45 degrees there are two

surfaces upwind with identical positive pressures and two surfaces downwind

with identical negative pressures effectively recreating the two surface case shown in figure 4. For the due north wind, the conditions are the same as in

figure 5. The response for the wind at 15 degrees resembles the north wind,

and the response for 30 degrees resembles the northeast wind.

This simple analysis could be conducted for more complex building

configurations, but the complex nature of the effect of forced ventilation on infiltration is already apparent. It is dependent on the relative areas for

inward and outward airflow and the degree to which forced ventilation reverses

the outward flows. For simplified analysis, the performance shown in figure 6

may be approximately represented by

for In/Fv < 0.7, Iv - Fv (11a)

for In/Fv >0.7, Iv = In + 0.3 Fv (11b)

This correlation also is a reasonable representation of the data presented in

reference [13] and could be used in energy analysis programs which cannot

compute the detailed mass balance. However, the great variability in total

infiltration indicates that the detailed mass balance is the preferred

simulation approach.

The development of a simultaneous simulation of equipment performance and room heat transfer ran into convergence problems which are still unresolved in

TARP. A mechanical ventilation model was developed to move a specified volume

of air from one room to another based on relative temperatures in the two rooms. One of the "rooms" could be the outside. This model worked whenever

one of the two control temperatures was the outside temperature which is

constant during the timestep. This allowed simulation of common arrangements

such as an exhaust fan or a whole house fan which exhausts from the house into

the attic. However, when the fan was arranged to mix the air between two rooms (by blowing between them and having a large opening for a return air

flow as might be used with a sunspace room) , there were times when the heat

balance iterations would not converge. This problem appears to be inherent in

the long timestep (one hour), implicit heat balance method used in TARP. The

method implements the implicit solution by iteration:

(1) compute the outside surface temperatures using a heat balance based on the

most recent estimate of inside temperatures;

(2) compute the inside surface temperatures using the outside temperatures and

most recent estimate of the room air tempreatures

;

(3) compute the airflows based on room air temperatures;

(4) compute new room air temperatures and heating or cooling loads based on

the new inside surface temperatures and airflows;

(5) if successive values of room temperature or load have not converged,

return to (1)

;

(6) after convergence, use the airflows to compute contaminant concentrations.

8
There are occasions when successive room temperatures during the iterations

causes the fan to switch on and off repeatedly. Each such cycle often takes

several iterations. Two potential solutions to this problem are (1) use of a direct, rather than iterative, solution of the simultaneous equations or (2) use of an explicit solution. An explicit solution would be easiest to

implement, but could be very time consuming because it would require a much

shorter timestep — probably similar to the timestep used in solving the

contaminant concentration equations. The short timestep would have the

advantages of allowing contaminant concentration to control the operation of

the ventilation system and easily simulating system devices which operate for

only part of the hour. This would be very useful for modeling the typical

residential forced air furnace which operates by cycling on and off and whose

fan also cycles, but on a delayed basis. The nature of interroom contaminant

migration is completely different during different parts of the hour depending

on whether the fan is on or off.

SUMMARY AND CONCLUSIONS

Development of infiltration and interroom airflow calculation methods and

concern for indoor air quality have led to a computer simulation of interroom

contaminant movements. Calculation of interroom contaminant migration is

mathematically quite simple if it can be assumed that the air in each room is

well mixed. It can be expressed by an ordinary differential equation

describing the contaminant mass balance. However, computer implementation of

the contaminant mass balance equations can be rather time consuming compared

to the rest of the building thermal simulation. Detailed modeling of the

concentration variations within a room is too time consuming to be considered

for long term transient analysis of multiple room buildings. Employing the

concept of ventilation effectiveness may provide a solution with sufficient

accuracy and speed. It could be added to some existing energy analysis

programs. The simple fully mixed room model showed that open doorways provide

rapid mixing between rooms in building using forced air heating. It also

confirmed that it is most energy efficient to remove the contaminant nearest

its source.

The HVAC system can dominate contaminant migration and needs to be

considered in modeling. Current simulation codes with long (one hour)

timesteps tend to run into convergence problems when solving the system

performance and interroom airflows simultaneously. It may be necessary to

model with smaller timesteps with the consequent increase in computation time.

Calculation of the increase of outside air brought into a house by a fan

showed that even simple systems can have subtle behavior. Until such

interactions are well understood, there is no substitute for detailed

modeling.

9
REFERENCES

[1] Perisly, A. K. , and Grot, R. A., "Ventilation Measurements in Large

Office Buildings", AS11RAE Transact ions. Vol 91, Part 2, 1985.

[2] McNall, P. E., "Indoor Air Quality Status Report", Proceedings of the

World Congress on Heating, Ventilating, and Air Conditioning, Copenhagen,

Denmark, August 25-30, 1985.

[3] Kusuda, T. , "Indoor Humidity Calculation", ASHRAE Transactions . Vol 89,

Part 2, 1983.

[4] Walton, G. N. , "Thermal Analysis Research Program Reference Manual",

Nat. Bur. Stand. (U.S.) NBSIR 83-2655 (NTIS number PB83-194225)

,

Washington DC, 1983.

[5] Walton, G. N. , 'A Computer Algorithm for Estimating Infiltration and

Inter-Room Air Flows', Nat. Bur. Stand. (U.S.) (NBSIR) 83-2635, February

1983.

[6] Kreyszig, E. , Advanced Engineering Mathematics . third edition, Wiley, New

York, 1978, pp 661-666.

[7] Hastings, S. R. , "Three Proposed Typical House Designs For Energy

Conservation Research", Nat. Bur. Stand. (U.S.) NBSIR 77-1309, Washington

DC, October 1977.

[8] Ishizu, Y. and Kaneki, K. , ’'Evaluation of Ventilation Systems Through

Numerical Calculation and Presentation of a New Ventilation Model",

Transa ctions of the Society of Heating . Air Conditioning and Sani tary

Engineers of Japan . Vol 24, Feb 1984.

[9] Sandberg, M. , "What is Ventilation Efficiency?", Buildings and

Environment, Vol 16, No 2, 1981, pp 123-135.

[10] Skaret, E. , and Mathisen, H. M. , "Ventilation Efficiency — A Guide to

Efficient Ventilation", ASHRAE Transactions . Vol 89, Part 2, 1983.

[11] Coblenz, C. W. , and Achenbach, P. R. , "Field Measurements of Ten

Electrically-Heated Houses", ASHRAE Transactions . 1963.

[12] ASHRAE Handbook - 1981 Fundamentals , p 22.6

[13] Levins, W. P. , "Measured Effect of Forced Ventilation on House

Infiltration Rate". Proceedings of the ASHRAE/DOE Conference Thermal

Performance of the Exterior Envelopes of Buildings II, 1982 Dec 6-9, Las

Vegas, NV, ASHRAE SP 38, 1983, pp 407-421.

10
TABLE 1:

SAMPLE CALCULATION FOR CONTAMINANT MIGRATION.

ONE POUND OF 'CONTAMINANT' RELEASED DURING

HOURS 6, 12, AND 18.

Constant weather case case case case T=37.3F W=5.2mph 1 2 3 3+fan

Infiltration (h

-

^) .572 .305 .160 .184

Avg load (kBtu/h) 26.3 18.4 14.4 15.1

K 3.47 6.16 11.51 8.46

Daily

Average D/L 3.05 5.56 10.92 7.92

Contaminant

Concentrations B3 3.02 5.61 10.86 7.87

xlOOO

B2 2.90 5.48 10.73 7.76

MB 2.83 5.41 10.65 7.72

B 3.05 6.65 10.92 7.92

Variable weather

Infiltration (h‘0 .609 .314 .160 .181

Avg load (kBtu/h) 26.0 18.1 14.2 14.9

K 3.30 6.04 11.52 8.45

Daily

Average D/L 2.87 5.52 10.92 7.92

Contaminant

Concentrations B3 2.84 5.49 10.88 7.88

xlOOO

B2 2.73 5.36 10.73 7.76

MB 2.65 5.27 10.64 7.70

B 2.87 5.52 10.92 7.92

11
Wind

Figure 1. Floor plan of example house

12
30 r —Case 1

Case 2

Case 3

Highest infiltration

Losest infiltration

Figure 2. Contaminant concentrations for three

levels of house leakiness

13
25

20

15

10

5

0

18 19 20

TIME

Figure 3. Contaminant concentrations in three rooms of one house (case 3)

14
Wind

o

tjAj/(U|-A|)

Figure 4. Infiltration response for a building with

only upwind and downwind openings

15

In/Fv
o

Figure 5. Infiltration response for a building

with openings on four sides

16

In/Fv
Wind

o

Ad/(U|-A|)

Figure 6. Infiltration response for various wind directions

17

In/Fv
FORM NBS-1 14A (REV. 1 1-84)

U.3. DEPT. OF COMM. 1. PUBLICATION OR 2. Performing Organ. Report No. 3- Publication Date BIBLIOGRAPHIC DATA

REPORT NO. SHEET (See Instructions) NBSIR 85-3229 NOVEMBER 1985

4. TITLE AND SUBTITLE

Estimating Interroom Contaminant Movements

5. AUTHOR(S)

George N» Walton

6. PERFORMING ORGANIZATION (If Joint or other than NS S, see in structlon $)

NATIONAL BUREAU OP STANDARDS

U.S. DEPARTMENT OP COMMERCE

GAITHERSBURG, MD 20899

7. Centraet/Grant No.

8. Type of Report & Period Covered

9. SPONSORING ORGANIZATION NAME AND COMPLETE ADDRESS (Street. City. State. ZIP)

10. SUPPLEMENTARY NOTES

Document describes a computer program; SF-185, FlPS Software Summary, is attached.

11. ABSTRACT (A 200-word or less factual summary of most significant information. If document includes a significant

bibliography or literature survey, mention it here) Development of infiltration and interrom airflow calculation methods, driven by a concern for indoor air quality have led to a computer simulation of interrom

contaminant movement. The model, which assumes fully mixed room air, shows that

open doorways provide rapid mixing between rooms in buildings using forced air

heating. It also confirms that it is most energy efficient to remove the contaminant nearest its source. Detailed modeling of the variations in contaminant

concentration within a room is not presently feasible. The concept of ventilation

effectiveness should provide sufficient accuracy and reasonable computing speed

to be added to some existing energy analysis programs. Current energy analysis

programs with long timesteps tend to run into convergence problems when solving

the system performance and interroom airflows simultaneously. Short timestep

simulation may be required. The need for computer modeling is demonstrated by

the subtle behavior of a very simple system which removes contaminants by forced

ventilation.

12. KEY WORDS (Six to twelve entries; alphabetical order; capitalize only proper names; and separate key words by semicolon s) Indoor pollution; ventilation; interroom airflow; computer modeling;

building energy analysis

13. AVAILABILITY

[~X] Unl imited

| | For Official Distribution. Do Not Release to NTIS

Order From Superintendent of Documents, U.S. Government Printing Office, Washington,

20402.

14. NO. OF

PRINTED PAGES

DC

25

15. Price

[X] Order From National Technical Information Service (NTIS), Springfield, VA 22161 $9.95

USCOMM OC 85-6004