Transient prediction of contaminant distribution by introducing energy load
calculations into multi-zone modeling
Jinchao Yuan
Jelena Srebric, Ph.D.
The Pennsylvania State University
ABSTRACT
Multi-zone models are widely used to predict the contaminant distribution within whole buildings.
However, typically multi-zone models do not incorporate energy equations to consider building
heat transfer. An ordinary practice is to assume an isothermal condition or assign a pre-described
temperature profile for the simulated zones. However, this practice is a challenging task even for
experienced users, because guessing a correct temperature distribution is difficult and multi-zone
simulations can be very sensitive to the temperature distribution, especially in simulations of large
openings.
The motivation of current research is to enhance the performance of multi-zone model accuracy
in prediction of species concentration by including the calculation of the temperature distribution
within zones. This temperature distribution is especially important for poorly mixed spaces or
displacement ventilation. This paper first demonstrates a simple case of the multi-zone sensitivity
to temperature distribution. Furthermore, an algorithm is presented to introduce energy load
calculations into a multi-zone model. The study provides temperature prediction by combining the
airflow modeling from a multi-zone program and the load calculation from an energy program.
The combined model predicts the indoor contaminant distribution with calculated temperature
distribution.
The new enhanced multi-zone method was applied to a cubicle floor in an office building for a 24hour dynamic simulation. A full-scale transient Computational Fluid Dynamics (CFD) simulation
was also conducted for the validation of contaminant distribution results obtained from a multizone model. The results show that the enhanced multi-zone-energy method provides better
prediction of contaminant distribution than the multi-zone model alone, especially in a variable
load situation with variable air volume system. In addition, the combined method demands much
less computational time than CFD method. The calculation time savings of the multi-zone model
compared to CFD is particularly evident for dynamics simulation cases. When appropriately
applied in building simulations, the combined multi-zone-energy simulation method can
accurately predict contaminant distribution without prior knowledge of temperature distribution.
INTRODUCTION
Multi-zone modeling is a popular simulation method for evaluation of contaminant distribution
within entire buildings. Heat transfer and thermal phenomena within a building are of great
importance for the accuracy of multi-zone modeling. Several studies developed coupling
algorithms for energy calculations and multi-zone modeling to address the interdependence of
heat transfer and airflow phenomena in indoor spaces.
Axley (2001) developed an algorithm to solve energy equations in a test version of a multi-zone
program called CONTAM R97. In this study, building thermal dynamics was modeled with heat
transfer through walls, windows and internal sources, as well as thermal storage effect of building
materials. In a later study (Axley, 2002), several natural ventilation cases were simulated to test
the program. Four procedures were proposed as guidelines for the natural ventilation design with
ContamR97. However, the program algorithm does not always provide a stable solution probably
due to numerical problems encountered in natural ventilation simulations indicating possible
multiple solution existence. This stability problem has to be solved in order to have the program
widely accepted.
A few powerful energy programs have incorporated airflow models into energy calculations. An
energy simulation program, ESP-r (ERUS Manual, 2002), integrated a heat transfer and airflow
modules. Thermal simulation module and multi-zone airflow simulation module are integrated in
ESP-r to calculate the surface temperatures, energy flows, and air flows throughout a building.
Another energy program, EnergyPlus (DOE, 2003), has also successfully incorporated the multizone airflow model into the energy calculations. The program couples the multi-zone model
COMIS (Feustel and Smith, 1997) into the energy calculations as an option. However, in both
ESP-r and EnergyPlus, the airflow modules are considered as a part that takes into account the
infiltration or inter-zonal air movement to make energy program calculations more accurate. The
energy program is the main focus, and the airflow models cannot be run without the energy
options.
Chen and Griffith (2002) incorporated single room nodal airflow models into single space energy
calculations. The EnergyPlus engine calculates the surface temperatures, thus providing
boundary conditions for the nodal models. Several different nodal models are incorporated into
single space energy calculations to allow flexibility in selection of airflow modeling. This coupling
effort was to enhance the accuracy of single space airflow modeling and could be extended to
multi-zone spaces to couple energy and airflow models. However, since nodal model is a singlespace model which is different from multi-zone model, nodal model coupling cannot be directly
applied to multi-zone model and energy program coupling.
PRELIMINARY STUDIES
Importance of temperature distribution in airflow modeling
Although most of the multi-zone models do not solve the heat transfer equations, temperature
distribution in the multi-zone model is still very important for the airflow distribution and
contaminant transport predictions. Previous studies (Ren and Stewart, 2002) found that airflow
and contaminant distributions are very sensitive to zone temperatures. One of our preliminary
o
studies has shown that a temperature difference of 1-2 C could significantly change the interzonal airflow rates or even reverse the direction of the airflow when large openings exist in multizone simulation.
A simple simulation case is developed with CONTAMW (Stuart and Walton, 2002), a widely used
multi-zone airflow model, to illustrate how the temperature difference can influence the interzonal airflow rates. This simulation includes three connected zones and a simple HVAC system.
Figure 1 shows the configuration of the test case.
Zone C
4
Zone A
5
Diffuser
Zone B
3
2
1
Figure 1. Configuration of the test case (1, 2, 3, 4 and 5 are flow paths)
In this simple case, zone A, zone B, and zone C are connected to each other by flow path 3, 4,
and 5. Zone B and zone C are connected to the ambient environment by flow path 1 and 2
respectively. A simple air handling unit blows air into zone A at a rate of 0.31kg/s (540 cfm).
Therefore, the air supplied to zone A moves into zone B and zone C and is exhausted to the
surrounding environment through opening 1 and 2. The flow paths 1 to 5 are all large openings
1
stands for typical opened doors or opened windows in a building. For example, the typical
2
parameters for a fully opened window are an area of 1.5 m and a discharge coefficient of 0.8.
Different zone temperatures are set to test the effect of temperature variation on airflow
o
o
movement. Zone A has a fixed temperature of 18 C and zone B has a temperature of 20 C, while
o
zone C has a series of temperature varying from 20 to 22 C. The airflow rates through paths1, 2,
3, and 4, are recorded during the zone C temperature variations. The obtained results are listed
in Table 1:
Table 1. Flow rate through different flow paths with different zone C temperatures
Flow Rate (kg/s)
Percentage (%)
Temperature
o
( C) in zone C
Path 1 (kg/s)
Path 2 (kg/s)
Path 1 (%)
Path 2 (%)
20
0.1534
0.1534
50%
50%
20.1
0.1342
0.1726
44%
56%
20.2
0.1203
0.1865
39%
61%
20.5
0.08868
0.2182
29%
71%
20.8
0.06395
0.2429
21%
79%
21.0
0.04961
0.2572
16%
84%
21.5
0.01843
0.2884
6%
94%
22.0
-0.008266
0.3151
-
-
According to the mass balance, the sum of flow rates through path 1 and 2 is equal to the flow
rate through the air handling unit. However, the distribution of air flow between paths 1 and 2
varies greatly when temperature of zone C changes. The flow rates through paths 1 and 2 are
equal when the temperatures of zone B and zone C are the same. The distribution between path
1 and 2 becomes more and more uneven as the temperature difference between B and C
o
increases. Finally, when the difference reaches 2 C, the flow rate through flow path 1 reverses its
direction (shaded field in the table).
Therefore, temperature distribution can significantly change the airflow pattern in multi-zone
modeling. Since airflow patterns are critically important for contaminant transport, an accurate
temperature distribution is essential for correct multi-zone contaminant transport modeling.
Principles and assumptions for solving temperature distribution
The transport equation for solving temperature distribution is similar to the contaminant transport
equation in the multi-zone model. Consequently, the solver for temperature distribution has the
same algorithm as the one used for calculation of concentration distribution.
The energy transport equation within a zone states:
dEi n
= ∑ qij + ∑ qsource i + ∑ q sin k i
dt
j =1
Ei = mi hi = ρ iVi hi
(1)
(2)
If only sensible heat is considered,
Ei = ρ iVi C p iTi
(3)
where
Ei , mi , Vi = Total thermal energy, mass, and volume the air in zone i
2
ρ i , hi , Ti = Density, enthalpy, and temperature of the air in zone i
C p i = Specific heat of the air in zone i
qij = Heat transfer rate from zone j to zone i
q sourcei , qsin ki = Heat source and sink in zone i
For energy equation (1), the source/sink equation terms representing heating/cooling loads can
be obtained directly by solving the system of equations or indirectly by taking the load values from
a load calculation program. Accurate source and sink terms are the key for a correct calculation
of the temperature distribution. These two terms are the lump sums of all forms of heat transfer
that add or remove heat from a zone. All the three heat transfer mechanisms, conduction,
convection and radiation, contribute to the source and sink terms. Multi-zone models themselves
can incorporate the heat transfer solution procedures to calculate the source and sink terms
(Axley 2001 and 2002). However, this requires serious heat transfer programming that already
exist in energy or load calculation programs. Therefore, our study is using an existing energy
program, EnergyPlus (DOE, 2003), to perform the necessary load calculations.
COUPLING METHODOLOGY
Multi-zone-Energy coupling algorithm
An energy program can accurately calculate heating/cooling loads for an entire building or
building zones under consideration. The load calculation results are then entered as source/sink
terms in the multi-zone model for airflow, temperature and contaminant calculations. An individual
zone temperature can be obtained by the same solver used for the contaminant calculations.
However, the coupling of load, temperature, concentration and airflow calculations requires a
master algorithm to organize the calculations as illustrated in Figure 2.
Step 1
Energy / Load
model calculates
Start heat gain/losses
Heat gain /
for each zone
zone SA flow
(all time steps)
Step 3
Step 2
Multi-zone
model
calculates C
and T (Tc)
Multi-zone
recalculates
C and T (Tc’)
Tc
(all time steps)
Tc= Tc’
No
If abs (Tc-Tc’) < err
Yes End
(all time steps)
Figure 2. Multi-zone temperature solving strategy
(SA- supply airflow, Tc-old temperature value, Tc’-updated temperature value)
In the algorithm shown in Figure 2, an energy program calculates the heat gain/losses and supply
airflow rate for each zone in the first step. In the next step, the heat gain and zone supply airflow
rates are provided to the multi-zone model to calculate the airflow, temperature and concentration
for each zone. Step 3 represents an iteration procedure that repeats step 2 until convergent
results are obtained. The calculated temperature is sent back to the multi-zone model as a
guessed value and the airflow and concentration are recalculated until convergence criterion is
satisfied. A few iterations may be required to obtain satisfactory convergence. It is important to
notice that the airflow and temperature calculations are coupled because the airflow rate
influences the convective term in equation (1), while the temperature distribution affects the
airflow rates through flow paths. Therefore, a correct airflow pattern and accurate airflow rate is
essential for the Multi-zone-Energy coupling.
Multi-zone-Energy-CFD coupling algorithm
3
Computational Fluid Dynamics (CFD) is capable of predicting accurate micro-scale airflow
patterns, airflow rates and distribution of other indoor air parameters. The accuracy and
informative results are the main advantages of CFD. Therefore, CFD are used for simulation of
critical zones where detailed information is wanted, such as the ones that contain contaminant
sources. In a previous study (Yuan and Srebric, 2002), CFD was used for enhancement of the
multi-zone simulations in highly non-uniform temperature and concentration field. The coupled
Multi-zone-CFD method gave improved results compared to the multi-zone model alone for the
studied displacement ventilation with a point source contaminant. However, CFD models are
much slower than multi-zone models because CFD solves pressure, three velocity components,
temperature, concentration and turbulence properties for thousands of cells in a typical room-size
problem.
As show in the preliminary study, temperature differences may cause major compact to multizone airflow calculation. Therefore, the temperature solving by a third party program can also be
applied to the coupled Multi-zone-CFD module to enhance the performance. As a role of the third
party program, energy program can deal with temperature distribution within an entire building by
simplified heat transfer models. A new fully coupled algorithm that introduces load calculations
into Multi-zone-CFD model is developed to enhance multi-zone model for airflow, temperature
and contaminant predictions in highly non-uniform indoor conditions. In this way, the fully coupled
algorithm integrates Multi-zone, Energy and CFD programs together.
The fully coupled algorithm is shown in Figure 3. In Step 1, a multi-zone simulation provides
boundary conditions for the source zones to be simulated by CFD program module. At the same
time, the energy program determines the heat gains/losses and supply airflow rates from the
mechanical (HVAC) system based on its powerful load calculations features. Therefore, with the
aid of the heat transfer data obtained from energy calculation, the multi-zone model can
calculated the bulk airflow and concentration distribution, which will be input to CFD in Step 2 as
boundary conditions for the source zone. Thereafter, in Step 2, CFD provides detailed values for
pressure, velocities, temperature and contaminant distributions in the source zone that will be
used to specify the boundary conditions in the multi-zone model in Step 3 and 4.
In Step 3, multi-zone model calculates the airflow, temperature and concentration based on the
heat flux provided by the energy program in Step1 and the CFD airflow and concentration
boundary conditions obtained in Step2. Step 4 works together with Step 3 as a temperature
solving procedure demonstrated in Figure 2. Therefore, this fully coupled method integrated CFD
boundaries, HVAC dynamics, and zone temperature into multi-zone model predictions. All of
these integrations are aimed at enhancing the multi-zone model accuracy by providing reliable
boundary conditions.
In summary, the fully coupled method takes the advantage all the three types of models: Multizone model’s effectiveness to calculate the bulk flow and contaminant transport; CFD mode’s
capability to deal with detailed temperature, airflow and contaminant calculation in small domains;
and energy program’s power to for HVAC system modeling and entire-building-level heat transfer
solving.
4
Step 1
Step 2
Flow, pres
CFD
Multi-zone
Concentration modeling for
flow modeling
B.C.
source zone
for the entire
Star
(T, C, flow &
Heat
Energy / Load gain/loss, SA
pressure)
calculation for flow rate
each zones
(all time steps)
Step 3
Multi-zone
generates
C and T(Tc)
T, C, flow &
pres B.C.
(all time steps)
Tc
Step 4
Multi-zone model
recalculates
C and T (Tc’)
Tc= Tc’
No
If abs (Tc-Tc’) < err
Yes
End
(all time steps)
Figure 3. Fully coupled algorithm for Multi-zone-Energy-CFD simulations
(SA - supply airflow, Tc - old temperature value, Tc’ - updated temperature value)
Radiation heat transfer has long been recognized researchers as an important issue in indoor air
simulation. In proposed coupling models, radiation heat transfer can be handled by energy
program, which contains several models to compensate internal radiation effect. CFD model is
also capable of handling the radiation heat transfer in the source zone simulation. However, the
numerical simulation case to be presented here does not consider the radiation heat transfer
since no simulation result is compared with actual experimental data. Further investigation on
radiation models will be conducted in future research when the coupled model results are
compared with experimental data.
SIMULATION CASE
A numerical simulation study is performed using the fully coupled Multi-zone-Energy-CFD method
shown in Figure 3. The simulated case represents a heavily partitioned office previously
simulated by the Multi-zone-CFD method (Yuan and Srebric, 2002). However, in current
simulation, four large wall openings at the ceiling level were artificially closed with solid walls to
reduce the complexity of the large opening simulations. Therefore, this is a virtual simulation case
very similar to the one we used to develop and validate Multi-zone-CFD method.
Building representation
An office of 7.9m long, 6.2m deep and 4.5m high is divided into six cubicles and a hallway by
partitions. Four of the six cubicles each have 2 occupants/cubicle and the other two cubicles have
1 occupant/cubicle. A displacement ventilation diffuser is located against the wall as shown in
Figure 4(a) and 6(b). Displacement ventilation system, floor layout and interior partitions are the
same as in a real office at the Penn State University.
5
Diffuser
Diffuser
(a)
Figure 4. (a) 2D Floor layout (b) 3D Space Layout
(1-18 numbers of the zones in the multi-zone model)
(b)
Simulation setup
In the current study, the space concentrations and temperatures were simulated by CFD alone
(CHAM, 2001), multi-zone model alone (Stuart and Walton, 2002), and the fully coupled Multizone-Energy-CFD model to investigate possible effects of temperature distributions.
A full-scale transient simulation for the entire space with CFD alone was conducted for validation
purposes. The transient CFD calculates the airflow, temperatures and concentrations in the
space for 24 time steps with one hour per step. The entire office is divided into 46×68×31 control
volumes and the RNG k-ε model is used to account for the turbulence. Previous study (Chen et.
al, 1998) has shown that CFD simulations can correctly predict velocity, temperature and
concentration distributions for displacement ventilation. In this case, due to the lack of dynamic
experimental data, we assume that the results of a full-scale CFD simulation accurately predict
contaminant distribution.
The contaminant distribution was also simulated by the multi-zone model alone. This simulation
was a benchmark case to evaluate the difference in results obtained with the fully coupled
simulation.
Finally, a fully coupled transient simulation is performed. First, multi-zone calculations are
conducted to obtain initial contaminant concentration and temperature within the space. The
space is divided into 2 vertical layers and each layer is divided into 9 zones as shown in Figure
4(a). The space airflow, concentration, and temperature are calculated at a time step of 10
minutes with the multi-zone model, while the outputs are based on an hour interval to match CFD
simulations. CFD simulations used one hour as the time step due to its slow calculations.
Therefore, the multi-zone model updated boundary conditions with CFD data in every sixth time
step.
EnergyPlus (DOE, 2003) is the energy program used to provide heating/cooling loads to multizone models for temperature calculations. Time steps can be selected from 10 minutes up to 1
hour. In this simulation, the minimum 10 minutes is used for the calculations to obtain better result
accuracy. However, the loads are averaged on hourly bases to match the CFD input.
The fully coupled algorithm is employed in the combined transient simulation. The coupling of
CFD and multi-zone model is to enhance the accuracy of the airflow and contaminant predictions.
For the CFD simulations, a source zones are selected to include the airflow source (the diffuser)
and the contaminant source. The coupling of multi-zone model with energy program enables the
temperature calculation, rather than assuming set point temperature for a zone.
Energy Program input / output
6
The energy program needs input of the space configurations, building materials, heat sources
values/boundaries, and different schedules for calculations. The space configuration is
represented by envelope surfaces. Building material inputs require properties such as the thermal
conductivity, thermal capacity, and radiation emittance for surface materials. Because the
simulated office is an interior space, the heat source for the simulated office is mainly due to
lighting, equipment and personal activities. The lighting, equipment and personal activities have
different schedules, hour by hour at different period of the day.
Similarly to most energy programs, EnergyPlus is able to automatically size the HVAC system
and determine supply airflow rates based on set point temperatures. In this case, the sizing is
o
based on two set point temperatures that are applied to different periods of the day: 23 C during
o
regular working hours and 25 C for the rest of the day.
EnergyPlus supports various output values such as heat gains/losses, flow rates, temperatures,
and meter readings. According to the temperature calculation method, the heat gain output from
EnergyPlus is the selected output in for this calculation. The output can be controlled to present
instantaneous or averaged loads at different intervals that are equal or greater than the minimum
time step (10 minutes). For our simulation, the output is averaged to produce an hourly-based
profile illustrated in Figure 5.
Load vs. Time
3000
2500
Load (W)
2000
1500
1000
500
0
1
3
5
7
9
11
13
15
17
19
21
23
Time (hr)
Figure 5. Load profile calculated by EnergyPlus for a representative day
(July 21st, Chicago, IL)
RESULTS
Concentration Distributions
In the absence of experimental data, simulations based on CFD alone are assumed to have
produced correct zone temperatures and concentrations. Figure 6 shows the simulation results of
contaminant concentrations in three representative zones among all the eighteen simulated
zones. The comparison indicates that the combined model prediction is much closer to CFD
results than the one obtained by the multi-zone model alone. Also, the trends of the concentration
variations with time in all of the zones agree well with the CFD simulations.
In the three representative zones (8, 9 and 12), several unexpected concentration peaks appear
for the fully coupled model at hour 1(1:00am) and 21(9:00pm) during the day. These peak values
are caused by the change of HVAC operation conditions due to the load change shown in Figure
5. The airflow rate changed dramatically at these points in time because of sudden changes in
space loads. Using a smaller time steps than 1 hour for the averaging of CFD and Energy
program results would provide smother results in the fully coupled method.
7
1
22
19
13
16
7
10
4
1
22
16
19
7
10
13
4
1
0.00E+00
hr
22
1.00E+01
0.00E+00
19
2.00E+01
1.00E+01
16
3.00E+01
2.00E+01
ppm
ppm
ppm
3.00E+01
13
4.00E+01
4.00E+01
9.00E+01
8.00E+01
7.00E+01
6.00E+01
5.00E+01
4.00E+01
3.00E+01
2.00E+01
1.00E+01
0.00E+00
7
5.00E+01
5.00E+01
CFD
Contam
Combined
Zone12
10
6.00E+01
CFD
Contam
Combined
Zone 9
6.00E+01
4
CFD
Contam
Combined
Zone8
hr
hr
Figure 6. The contaminant concentrations for three representative zones for the transient
simulation case
Temperature Results
Figure 7 shows the simulation result of temperature prediction for the three selected zones (zone
8,9, and 12). Similarly to concentration results, the fully coupled model predictions are much
closer to CFD results than the ones obtained by the multi-zone model alone in all zones.
CFD
CFD
Zone 8
Multi-zone
Fully Combined
30
30
25
25
CFD
Zone 12
Multi-zone
Fully Combined
Multi-zone
Fully Combined
40
35
30
T(C
20
T(C)
20
25
20
15
15
hour
23
21
19
17
15
13
11
9
7
23
21
19
17
15
13
11
9
7
5
3
23
21
19
17
15
13
11
9
7
5
3
1
hour
5
10
10
3
10
1
15
1
T(C
Zone 9
hour
Figure 7. Temperatures for three representative zones in transient simulation case
The multi-zone model with energy program method as shown in Figure 2 can catch the trend of
the temperature variation. However, the fully coupled method predicts the trend much better and
provides much closer temperature values to CFD than the multi-zone method because the
introduction of CFD airflow data into the fully coupled method enhances the prediction of thermal
heat fluxes. In the proposed temperature prediction method, the airflow greatly influences the
temperature calculations because the heat gain of the zone is given as a lump sum rather than
being calculated from heat transfer equations within the multi-zone model. Therefore, airflow
pattern strongly influences the temperature prediction and vice versa. Accurate airflow
information is essential for accurate temperature predictions. The combined Multi-zone-CFD
model can predict a more accurate airflow pattern than the multi-zone model alone as
demonstrated in the previous study (Yuan and Srebric, 2002). Therefore, the fully coupled
method assures the accuracy of the airflow calculation and enhances the temperature calculation
consequently.
DISCUSSION
The coupled Multi-zone-CFD method once again demonstrated its strength in concentration
simulations. In addition, temperature calculation is introduced to investigate possible influence of
temperature distribution on the performance of airflow and concentration simulations. This section
discusses important simulation findings from the transient simulation using the fully coupled
algorithm. Several issues that are important for the transient simulations are computational time,
effects of large opening and impacts of temperature distribution on airflow/concentration
simulations.
Computational time
The computational time is not directly compared in this transient case. However, a full CFD
simulation is extremely time consuming because many time steps are to be calculated with input
8
of appropriate transient boundary conditions. Based on the comparisons in the previous study
(Yuan and Srebric, 2002), it was found the coupled simulation requires less than half of the
computational time needed for the full CFD simulation. Therefore, it can be estimated that the
fully coupled simulation spends only 30-50% of time necessary for the CFD simulation of an
entire building under transient conditions. Consequently, the fully coupled method still has great
advantages in simulation when compared to CFD method applied to an entire building.
Effects of large openings
Accurate airflow pattern is essential to obtain accurate concentration predictions. Also, in this
algorithm that solves temperature by external program input, airflow has a very important role in
the temperature solution procedure. Although the exterior large openings are closed to reduce
error and the simulations do benefit from this simplification, the interior large openings are still a
problem for the airflow simulations.
Figure 7 indicates that, compared to CFD results, the pure multi-zone simulation has an error of
o
2 C or higher in temperature prediction in nearly all of the zones. As stated in the preliminary
studies above, the problem lies in the accuracy of airflow rate prediction by multi-zone model.
However, the major difficulties for multi-zone model in airflow prediction are the internal large
openings, where two-way flows and non-uniformed boundary conditions across the openings
usually occur.
Because the simulation is conducted within a space, it has to deal with the inter-zonal large
openings. In general, multi-zone simulations with large openings are very difficult compared to
those with small openings, which is among the reasons why the full coupling method of CFD,
multi-zone, and energy program are applied in this simulation.
Impact of temperature distributions on airflow/contaminant predictions
In the preliminary studies, a simple case is studied to demonstrate the possible impacts of
temperature difference on the airflow prediction. In the current combined simulation, the predicted
concentrations were clearly more accurate with a better prediction in temperature distribution.
These two experiences show that the precise temperature calculations are important for accurate
airflow and contaminant transport simulations.
However, a more comprehensive study is needed to fully investigate the airflow and temperature
interactions. For example, comparative simulations could be conducted to define the effects of
the temperature distribution on airflow calculations in real buildings. A direct comparison of
concentration predictions with and without temperature consideration should be conducted for
this purpose.
In summary, the presented simulation case has several limitations due to the difficulties to
accurately handle the effect of large openings and temperature distributions in multi-zone models.
However, the powerfulness and effectiveness of the proposed coupled methods are still valid in
this “extreme” case. Therefore, the coupled methods are anticipated to have an even better
performance in other non-large-opening-predominated cases, where the large opening
uncertainty is much less than the presented case. Although further studies are still needed to
obtain a solid proof for the anticipation, the advantages in the computational time of the coupled
methods will still make the coupled algorithm attractive to the modelers in both situations.
CONCLUSIONS
The purpose of this transient simulation case is to investigate possible effects of temperature on
the airflow and concentration predictions. A virtual case is simulated based on the configuration of
an internal office, which was previously simulated in a steady-state condition with only assigned
temperature distributions. A variable-air-volume (VAV) HVAC system and temperature calculation
are considered in this transient simulation case.
9
The HVAC dynamics is important for concentration simulations because of the airflow supplied by
the air handling system is usually changing according to the loads in typical U.S. buildings. The
fully coupled method introduced energy program to handle the load calculation and determine the
air supply rate of the HVAC system. Therefore, the contaminant concentration can be simulated
more precisely with better consideration of variable flow rates.
This transient case demonstrated that introduction of temperature calculation contributes to the
airflow and concentration predictions. However, the interactions between airflow and temperature
calculations are not clearly demonstrated in this case. Future studies on direct comparison of
airflow prediction with and without temperature consideration will be conducted to fully
understand these important interactions.
The calculation time of fully coupled method is one of the major advantages when compared to
the calculation time needed by CFD simulation of this entire space. Energy program modeling
indeed increases the difficulties and complexities of the modeling. Nevertheless, fully coupled
methods still cost less time for a building simulation than CFD. Furthermore, an energy program
modeling is usually valuable for designers in sizing, system modeling, and cost analysis.
Therefore, introducing energy program is not a waste of input and computational time.
ACKNOWLEDGEMENTS
This study is supported by the National Institute for Occupational Safety and Health (NIOSH), the
Centers for Disease Control and Prevention (CDC).Grant number 1 K01 OH07445-01.
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