Comparison and Uncertainty Quantification of Roof Pressure Measurements using the NIST and TPU Aerodynamic Databases

Document Type


Publication Date


Publication Title

Journal of Wind Engineering and Industrial Aerodynamics


The pressure coefficient of a low-rise building in the ASCE wind load design provision is usually obtained from boundary-layer wind-tunnel tests. Although these tests tend to be standardized, inconsistent results from different facilities have been acknowledged as a long-standing issue. This work compares roof pressure for a low-rise building model archived in the National Institute of Standards and Technology (NIST) aerodynamic database and the Tokyo Polytechnic University database, followed by quantifying the measurement and data reduction uncertainties of the NIST datasets. The Monte Carlo simulation propagates four elemental uncertainties to the mean (C-p) over bar, standard deviation C-p' and peak pressure coefficient C-p,C-peak. Results indicate that pronounced differences in the roof pressure from two datasets are attributed to different inflow characteristics (including the Jensen number variation) and the inherent measurement uncertainties. High measurement uncertainties of (C-p) over bar and C-p,C-peak are strongly correlated with vortical flow structures, either separated flow or conical vortices at the roof corner and windward edges. Two dominant measurement uncertainty sources are distinguished: the dynamic pressure ratio uncertainty and the surface pressure tap uncertainty. Alternative flow and pressure measurement techniques are noted to potentially reduce the two dominant uncertainty sources. This work is intended to clarify measurement uncertainty sources of obtaining pressure coefficients in wind-tunnel model tests and shed lights on why large differences exist from different tests.


E. Shelley and E. Hubbard acknowledge the generous support of Ohio Space Grant Consortium (OSGC) , United States of America Internship program and the Master's OSGC Fellowship, United States of America. W. Zhang acknowledges the support of the National Science Foundation (NSF), United States of America CAREER grant (Award# 1944776) and the CSU Faculty Research Development Funds, United States of America.