comparison between measured and simulated long term variation of

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Figure 1. Plan of the house and corresponding sketchpads for CONTAM simulation input .... symbols denote results of a two-zone analysis of tracer gas measurements. Figure 6. .... (http://www.fire.nist.gov/bfrlpubs/build03/PDF/b03064.pdf). 4.
COMPARISON BETWEEN MEASURED AND SIMULATED LONG TERM VARIATION OF VENTILATION IN AN EXTRACT VENTILATED HOUSE Hans Stymne1†, Gunnel Emenius2, CarlAxel Boman3, and Claes Blomqvist1 1

Department of Technology and Built Environment, University of Gävle, Gävle, Sweden 2 Department of Public Health Sciences, Karolinska Inst., Stockholm, Sweden 3 Pentiaq AB, Gävle, Sweden

ABSTRACT Using a passive tracer gas technique, 1 and 2 week averages of local mean ages of air have been estimated in an occupied detached single family house in mid-Sweden during one year. In this paper the measurement result is compared with the result of transient simulation of ventilation using the CONTAM program. The simulation shows that the whole-house air change rate is dominated by the infiltration due to mechanically created pressure difference as long as the outdoor temperature difference exceeds approx. 10 °C. At lower outdoor temperature, the natural driving force becomes increasingly more important increasing the local air change rate (local ACH) in the basement. However, the local ACH on the ground floor is almost independent of indoor-outdoor temperature difference and completely dominated by the mechanical extract. The result from the simulation can reproduce the result of the measurement in satisfactory detail without using wind pressure data.

KEYWORDS Ventilation, Passive tracer gas, Local mean age of air, Simulation, CONTAM

INTRODUCTION Ventilation may vary considerably with time, especially in naturally ventilated dwellings, due to the variation in the ventilation driving forces as induced by the indoor/outdoor temperature difference and wind pressure. However, the influence from the occupants’ behavior may also be an important factor. If the ventilation varies greatly in an unpredictable manner as a function of time, it is very difficult to draw any conclusions about the ”normal” or long term average ventilation from ventilation measurements performed during a short period. The problem becomes crucial when the measurements are a part of large epidemiological studies of possible health effects from insufficient quality of the indoor environment. In large scale field studies it is very difficult or even impossible to measure the average ventilation during one or several years. For practical and economic reasons ventilation and other indoor environment factors cannot be measured simultaneously for all dwellings and they must be measured during relatively short periods in each dwelling. For the statistical analysis and interpretation of a possible correlation between health and indoor environment it is essential to have knowledge about the expected range of variation of ventilation. It would also be of great value if the variation or at least a major part of it could be attributed to variations of the outdoor temperature and wind velocity as this would allow for certain corrections for the influences of weather. Several computer programs have been developed for simulating ventilation and air flows in buildings. There seem however to be few publications on measurements of building ventilation variations during varying weather conditions and comparison with computer simulation. Haghighat and Megri (1996) carried out a validation of COMIS and CONTAM and found good agreement between predicted and †

Corresponding Author: Tel: + 46 26 64 81 40, Fax: + 46 26 64 81 81 E-mail address: [email protected]

measured air flow and contaminant dispersal in a controlled environment, and in a residential building using tracer gas measurement. Extended validation efforts of COMIS are presented within the IEA-ECB Annex 23 project (Warren 2000, Fürbringer et al. 1996). Blomsterberg et al. (1999) presented a comparison between simulated (using the multi-zone computer program COMIS) and measured ventilation performance during three different periods, each lasting 1–6 days, in 9 dwellings. They concluded that the simulated and measured average total outdoor ventilation rates agree reasonably well, but the hourly variations often disagree. For individual rooms the simulated and tracer gas measured ventilation rate could be very different. Emmerich (2001) reviewed 10 validation efforts of CONTAM or COMIS simulation with experimental data. He concluded that most of them focus on predictions of whole building air change rates with a few also considering the prediction of individual zone air change rates or specific airflows. Only a few reports included limited statistical evaluations. Emmerich et al. (2003) have presented an extended comparison, including statistical analysis, between measured tracer gas measurement and prediction using CONTAM in a town house. They concluded that average tracer concentrations agree very well, but agreement is less good for individual zones. A long term study of ventilation variation has been performed in an airtight, extract ventilated occupied detached house during one year using a passive tracer gas technique (Stymne et al. 2006). In the present paper the ventilation during the same year is simulated using the CONTAM computer program (NIST 2005) and the result compared with the experimental data. The aim of this study is to draw conclusions about the range of ventilation variations and to test to what extent the variations can be predicted by the weather variations.

DESCRIPTION OF THE OBJECT AND METHOD OF EXPERIMENT AND SIMULATION Building construction

Figure 1. Plan of the house and corresponding sketchpads for CONTAM simulation input

The investigated house was constructed 1977 in Gävle, 180 km north of Stockholm. The underground basement has walls of hollow concrete blocks, while the rest of the building is a brick faced wooden 2 3 construction. The ground floor has an area of 144 m (V=346 m ) and the underground basement 144 2 3 m (V= 330 m ). The ground floor and basement are connected by an open stairway. The house has a central extract fan running continuously. The extract channel is connected to the kitchen hood and the wet rooms (bathroom, WCs and laundry). The fan speed is occasionally forced when cooking. The plan of the house is displayed in Figure 1, together with the sketch-pads for input to the simulation program. Parameterization of simulation program The house is divided into 17 rooms, each room constituting one zone (Figure 1). The building characteristics are given in Table 1. The leakage area of the house is estimated from an assumption of -1 a total infiltration rate of 1 h at 50 Pa pressure difference. The specific leak area on the ground floor is 2 therefore set to 2.5 cm per square meter of external wall area using a power law model for infiltration flow (discharge coefficient=0.6 at 10 Pa reference pressure, flow exponent=0.65). Due to the construction of the basement envelope the leakage area in the basement is set to zero.

doors

extract l/s

Wall ventilator

Room temp

wall area

2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1

Room volume

level

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Room description

Room number

Table 1. Description of the parameter input for the simulation

living room 101.1 42.2 22 2 M1 2 Bedroom 2 29.3 17.3 22.5 1+(1) Bedroom 1 26.1 6.7 22.4 1 kitchen 94.2 18.2 22.3 10 5+(1) hall 27.7 6 22.1 2+(1) WC 2 5.3 22.6 5 (2) bathroom 34.9 8.6 22.7 5 (2) WC 1 4.5 2.3 22.2 10 (1) Bedroom 3 34.9 18.2 22.2 1 M1 2 WC 5 20.1 1 M2 10 (1) store 1 60.7 20.2 1 M2 1 laundry 28 20.2 1 M2 10 1 bedroom 24.3 20.1 1 sauna 16.9 20.1 1 M2 10 1 lower hall 77 20.1 1 M2 3* store 2 52.3 20.2 1 M2 1 TV-room 89.3 20 4* stairway connecting rooms 4 and 15 * the opening between room 15 and 17 is a portal W=2m

There are two types (M1 and M2) of wall ventilators for air inlet. The M1 ventilators, used on the ground floor are fully opened (10 mm) “Fresh100” ventilators, whilst the M2 ventilators, used in the basement, are of type CRT 160 (from Rec Indovent) opened 5 mm. Both types are placed 1.8 m above the floor. The flow characteristics of both ventilators are modeled using a power law:

q(M1) = 0,00272 ⋅ ∆p

0 , 52

; q (M2) = 0,0026 ⋅ ∆p

0 , 585

where q is the flow in l/s and ∆p is the pressure difference in Pa.

All mechanical air exhaust terminals, also placed at 1.8 m height above the floor, are connected to the common continuously running air extract fan on the roof. The exhaust flow rates are given in table 1. The normally open doors connecting rooms are modeled as two-way flow elements (H=2m, W=0.8 m, discharge coefficient=0.78, flow exponent=0.5), while the normally closed doors are modeled as one-way flow elements using a power law (flow coefficient 0.01, flow exponent=0.5). The number of closed doors is given within parentheses in table 1. The stairwell connecting the two levels has a cross 2 sectional area of 6 m and the flow is modeled using a one-way power law (flow exponent=0.5). Passive tracer gas measurement The ventilation conditions in this house were measured during one year using a passive tracer gas technique known as the homogeneous emission technique. A validation of the method has been presented by Stymne and Boman (1994). Details of the technique are described in a Nordtest Method (Nordtest 1997). In this technique, miniature passive tracer gas sources (Figure 2a) are distributed within the building in such a way that the emission rate of tracer gas is proportional to the room volumes in all parts of the building. With such an arrangement of tracer gas emission rates, the local tracer concentration will be proportional to the “local mean age of air”, i.e. the tracer concentration in a room tells how long the air in that room, on average, has spent within the building. The inverted value of the local mean age of air is equivalent to the commonly used ventilation quantity “local air change rate” (ACHp), i.e. the same quantity which is obtained from a properly designed tracer decay measurement. The house was equipped with 19 (adjusted) sources emitting tracer gas of type A (hexafluorobenzene) evenly distributed on both levels and 10 (adjusted) sources with tracer gas of type B (octafluorobenzene) evenly distributed in only the basement. 30 passive samplers (Figure 2b) were distributed in the house, of which four were switched approximately once a week, four approximately once every second week and 22 approximately once a month. Integrating temperature sensors were used for obtaining time-averaged room temperatures during the measurements periods. Figure 2. a) Capillary tracer gas source, with emission adjustment device. b) Passive sampler with charcoal sorbent.

Some results of the long-term tracer gas measurement of ventilation in this house have been published earlier (Stymne et al. 2006). Below additional results which are compared with the result of the transient simulation are presented. Simulation procedure Transient simulation of air flows is performed using CONTAMW for each hour from 1 April until 25 March the year after with constant values of the parameters given in Table 1. The zone-temperature on the ground floor is set to 22-22.7 °C, which is close to the measured indoor temperature. The temperature in the basement is set to 20 °C. Although local temperatures were not known, small temperature differences between connected zones are assumed as shown in Table 1 in order to allow for simulating certain inter-zonal air exchange through doorways. Outdoor temperature data is taken from a nearby metrological station every 3 hours. Wind effects are neglected in the model. The time steps in the simulation are 0.5 hours. The simulation is performed fully independent of the tracer experiment.

RESULTS Total air change rate (ACH) The daily averages total ACH for the building as obtained from the simulation is displayed in Figure 3 together with the outdoor temperature. It can be observed that the air change rate is predicted to be independent of outdoor temperature above approx. 10 °C.

Figure 3. Result of simulation. Daily averages of total ACH. Lower curve displays the outdoor temperature. Local air change rates The local air change rate (local ACH) is defined from the inverted value of the local mean age of air. In Figure 4a and 4b the local ACH predicted by simulation in the living room on the ground floor and in the TV-room in the basement together with the result of the tracer gas measurement in the same two rooms are displayed. The measured average of indoor-outdoor temperature differences are also displayed in Figure 4b.

Figure 4. Simulated and experimental result of local ACH in a) the living room at the ground floor and b) the TV-room in the basement. Unfilled square and circle symbols denote experimental results. The lower curve in b) connects measured indoor-outdoor temperature differences. Two-zone flows The primary results from the tracer gas measurement are the local mean ages of air at the measurement positions averaged over the measurement time. True averages of airflow values can however not be calculated, because a bias is introduced due to flow variations (Sherman and Wilson 1986). In the present case an additional tracer type (type B) was distributed in the basement, in order to be able to estimate the air exchange between the two levels. However, true averages of the airflows

between ground floor and basement cannot be calculated from the tracer gas measurement, because this would require a complete mixing of air within each of the two levels in addition to the requirement of constant flows. In spite of these shortcomings the tracer gas measurements are analyzed using a simple two-zone model. The measurements show that the tracer gases are rather evenly distributed within each of the two levels and the flow variations may be limited within each measurement period. The results of the two-zone calculations of flows at the two levels are displayed in Figure 5 and Figure 6 and compared with the result of simulation. Observe that no downflow of air through the stairwell (Figure 5b) can be simulated, due to the assumption of constant temperature difference between the levels and the stairwell model used.

Figure 5. a) Simulated and experimental result of the upward airflow through the stairwell between basement and ground floor. b) Measured downflow of air between the two storey levels. The square symbols denote results of a two-zone analysis of tracer gas measurements.

Figure 6. Display of simulated and measured air exchange between outdoor and the two storey levels. The square symbols denote results of a two-zone analysis of tracer gas measurements.

DISCUSSION The overall agreement between the results of simulation and tracer gas experiment is surprisingly good except at the ground floor during the summer months July – September. The reason is probably that windows and the terrace door are often opened on warm summer days, a matter which is not included in the simulation. Total air change rate The simulation predicts a constant whole building air change rate when the average outdoor temperature exceeds approximately 10 °C (Figure 3). The ventilation air flow is fully controlled by the exhaust fan and the infiltration induced by the stack effect is negligible under these circumstances. However, it is also during these periods that window airing is occasionally used, increasing the ventilation. At ambient temperature below 10 °C the predicted varying total ACH directly reflects the variation in temperature. Local air change rate The distribution of ventilation air is not even in this house. While the local ACH (computed from the inverted value of the local mean age of air) at the ground floor (Figure 4a) is predicted to be fairly -1 -1 constant during the year (0.2-0.3 h ), it varies considerably in the basement (0.25-0.6 h ). The variation of local ACH in the basement can be attributed to the stack effect as illustrated by the close parallelism between ACH and the inside-outside temperature difference (Figure 4b). The stack effect creates airflow from the basement to the ground floor. With the exception of the summer months at the ground floor, the agreement between simulation and tracer gas measurement is very good. Flows between levels The stack effect is further illustrated in the result of simulation and measurements presented in Figure 5. In Figure 5a the upward flow between the two levels is displayed. This flow is predicted to be as low as 3 3 10-25 m /h during summer, but as high as 100-150 m /h during winter. During the coldest winter periods almost all air to the ground floor emanates from the basement. Due to the rather evenly distributed tracer concentrations within both of the two levels and the reasonably constant circumstances during each tracer gas measurement period, a two-zone calculation of the airflows to, from and between the two levels is justifiable. Figure 5a illustrates the close agreement between prediction and measurement of inter-zonal flow. However, due to the limitation of the flow model for the stairwell and the assumed constant temperature difference between the two levels, the downward flow (Figure 5b) cannot be simulated. Air exchange with ambient air From the output from the CONTAM simulation the sum of all inflow of ambient air to and the sum of all outflow of air from the two levels can be calculated. The result is displayed in Figure 6. It is predicted that the ground floor has essentially no inflow of air during winter and an increased outflow of air during the coldest period. Under the rest of the year the simulation predicts an outflow of air equal to the mechanical exhaust. The basement is predicted to get a strongly increased inflow during winter and an outflow which is totally controlled by the mechanical exhaust on that level. The measurement shows 3 that the inflow to the ground floor is under-estimated by approximately 50 m /h by the simulation and the inflow to the basement is over-estimated by the same amount. Excluding for the summer period with window airing, the agreement between simulation and experiment is otherwise good.

CONCLUSIONS The comparison between simulated and measured ventilation performance of this occupied house during a whole year shows on the whole a surprisingly good agreement. An exception is during the summer months July – September. This exception can be explained by airing via window and terrace door during warm weather. Both measurement and simulation shows a strongly uneven distribution of the ventilation air, with appreciably more air entering the basement. Most of the air to the ground floor comes from the basement during winter. Reasons for the good agreement between experiment and simulation are probably a reliable measurement technique and the relative air-tightness of the house. The ventilation conditions in leaky, wholly naturally ventilated houses will probably be more difficult to simulate correctly. The close agreement between theory and experiment increases the possibility to finding a reliable technique to make predictions of ventilation performance in extract ventilated houses during different weather conditions using measurement data obtained during other weather conditions.

ACKNOWLEDGEMENTS The authors would like to thank Mathias Cehlin, Hans Wigö and Ulf Larsson, who performed part of the computational work. The Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (FORMAS) is gratefully acknowledged for financial support of this study.

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