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Development of an Infiltration and Ventilation Model for Predicting Airflow Rates within Buildings
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 Title & Authors
Development of an Infiltration and Ventilation Model for Predicting Airflow Rates within Buildings
Cho, Seok-Ho;
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 Abstract
A ventilation model was developed for predicting the air change per hour(ACH) in buildings and the airflow rates between zones of a multi-room building. In this model, the important parameters used in the calculation of airflow are wind velocity, wind direction, terrain effect, shielding effect by surrounding buildings, the effect of the window type and insect screening, etc. Also, the resulting set of mass balance equations required for the process of calculation of airflow rates are solved using a Conte-De Boor method. When this model was applied to the building which had been tested by Chandra et al.(1983), the comparison of predicted results by this study with measured results by Chandra et al. indicated that their variations were within -10%~+12%. Also, this model was applied to a building with five zones. As a result, when the wind velocity and direction did not change, terrain characteristics influenced the largest and window types influenced the least on building ventilation among terrain characteristics, local shieldings, and window types. Except for easterly and westerly winds, the ACH increased depending on wind velocity. The wind direction had influence on the airflow rates and directions through openings in building. Thus, this model can be available for predicting the airflow rates within buildings, and the results of this study can be useful for the quantification of airflow that is essential to the research of indoor air quality(temperature, humidity, or contaminant concentration) as well as to the design of building with high energy efficiency.
 Keywords
Infiltration and ventilation model;ACH(Air changes per hour);Airflow rate;
 Language
Korean
 Cited by
 References
1.
Chandra, S., Houston, M., Fairey, P., Kerestecioglu, A., 1983, Wing Walls to improve natural ventilation : Full scale results and design strategies, Proceedings of ASES Eighth National Passive Conference, Glorieta, NM., 1-10.

2.
Cho, S. H., 2006, Development of an integtated multizone model for indoor air environment prediction, Journal of the Environmental Sciences, 17(9), 993-1003.

3.
Chung, K. C., 1996, Development and validation of a multizone model for overall indoor air environment prediction, HVAC & R Research, 2(4), 376-385. crossref(new window)

4.
Conte, S. D., De Boor, C., 1972, Elementary numerical analysis, an algorithmic approach, McGraw-Hill, 88.

5.
Deru, M., Burns, P., 2003, Infiltration and natural ventilation model for whole-building energy simulation of residential buildings., NREL, CP-550-33698, 1-17.

6.
Haghighat, F., Brohus, H., Rao, J., 2000, Modelling air infiltration due to wind fluctuations - a review, Building and Environment, 35, 377-385. crossref(new window)

7.
Swami, M. V., Chandra, S., 1988, Correlations for pressure distribution on buildings and calculation of naturalventilation airflow, ASHRAE Transaction 94, 243-266.

8.
Sherman, M. H., Grimsrud, D. T., 1980, Infiltrationpressurization correlation : Simplified physical modeling, ASHRAE Transaction 86, 778-806.

9.
Walton, G. N., 1982, Airflow and multiroom thermal analysis, ASHRAE Transactions, 88(2), 78-91.

10.
Walton, G. N., 1984, A computer algorithm for prediction infiltration and interoom airflows, ASHRAE Transactions, 90(1B), 601-610.

11.
Walton, G. N., 1989, Airflow network models for elementbased building airflow modeling, ASHRAE Transactions, 95(2), 611-620.

12.
Zhang, J. S., 2005, Combined heat, air, moisture, and pollutants transport in building environmental systems, JSME International Journal, Series B, 48(2), 182-190. crossref(new window)