A review of the worldwide data base on distribution of pressure coefficients (C_p) on building surfaces yielded usable data from eight different investigators for low-rise buildings and one source for high-rise buildings. It was found that average surface pressure coefficients for low rise buildings were adequate, and local data were assimilated as 544 average surface C_p. A nonlinear regression with wind incidence angle and building side ratio as variables was found to predict these data with a correlation coefficient of 0.80. Local pressure coefficients rather than average surface C_p were used for high rise buildings. More than 5,000 data points were fitted with another nonlinear regression involving the earlier variables plus the location coordinates.

Building pressure coefficient correlations developed in this paper can be useful for infiltration and indoor air quality studies as well as for natural ventilation airflow calculations.

A structured procedure for calculating wind-driven natural ventilation rates is given in appendix A. This procedure is an enhanced version of the Vickery (1983) algorithm for calculating airflow through buildings.

Units: I-P