Air infiltration has long been recognized as a significant portion of the total heating orcooling loads in a residence. Infiltration rates are extremely difficult to predict accuratelyfor a residence because of the numerous variables that are involved, the complexities ofinteractions among the variables and the inability to exactly determine the magnitude of thevariables. In order to improve residential energy prediction procedures, a detailed investigationwas conducted by Ohio State University under EPRI sponsorship to obtain measured dataat nine research residences in Columbus.

The objective of this investigation was to develop a generalized computer simulation modelto predict hourly air infiltration rates into a residence. The model should account for thesuspected parameters that influence air infiltration, such as weather, orientation, crack sizes,combustion processes, exhaust fan operation, and window and dooi openings.