Electronic Thesis and Dissertation Repository


Doctor of Philosophy


Civil and Environmental Engineering


Gregory A. Kopp


The effects of turbulence in the atmospheric boundary layer (ABL) on surface pressures of a typical low-rise building roof are investigated in this thesis. A 1/50 geometrically-scaled model of the Texas Tech University Wind Engineering Field Research Lab (WERFL) building model is used for pressure measurements in wind tunnel experiments. ABL wind turbulence intensities ranging from about 10% to 30%, and length scales ranging from 6 to 12 times of the building height (H) are generated. The effects of ABL turbulence on the mean roof pressures within the separated flow are explained from the time-averaged Navier-Stokes equations. The pressure fields are reconstructed by integrating the pressure gradients using an analytic interpolation approach. For high turbulence intensity levels, the maximum suction coefficient on the roof surface was found to be increased. Such increasing magnitudes are directly related to reduced sizes of mean separation bubbles, more rapid variation of the velocity magnitude near the leading edge and enhanced variation of the turbulence stresses. On the other hand, higher surface pressure recovery found in the leeward portion of the separation bubble is mainly due to the more rapid variation of the turbulence stresses. The effects of ABL turbulences on the fluctuating roof surface pressures are explained by the quasi-steady (QS) theory. Basically, the QS model assumes that the instantaneous roof surface pressure is induced by a modified local mean flow field. The selection of the mean flow pattern and the amplification of the velocity magnitudes are determined so that the resulted instantaneous velocity vector is matched to the measurement at the reference location, i.e., 1H above the roof leading edge in this thesis. The QS model is found to explain the effects of large length scale turbulences very well. Better QS-predictions are observed if vertical component of the velocities are included. A statistical method for estimating the surface pressure probability distribution, based on the assumptions from the QS model, is derived and validated. This method relates the pdf of building surface pressures to the joint pdf of wind speed, azimuth angle, and elevation angle.