Multivariate Stochastic Simulation of Wind Pressure over Low-Rise Structures through Linear Model Interpolation

Abstract eng:
The prescriptive measures for the design of structures to resist wind loads are under continual refinement as wind-tunnel, full-scale, and computational methods improve our understanding of windstructure interaction. The database assisted design (DAD) concept now under development will offer an online database of wind load time histories, and has the potential to further enhance load definitions. Several university-affiliated wind tunnel facilities have been contracted to generate an extensive library of such time histories for a large variety of building shapes and terrains. These physical testing efforts will be complimented by computational load generating methodologies including computational fluid dynamics and stochastic simulation. The intent is to use these means to extend existing records, and extrapolate between shapes tested in the tunnels. This study investigates the efficacy of interpolation techniques to infer the spectral and probabilistic descriptors of non-Gaussian correlated variables representing pressure coefficients based on those measured from wind tunnel tests on comparable but not identical building shapes. A standard multivariate non-Gaussian simulation method is used to generate time histories based on the interpolated models. Comparisons of peak aggregate uplift statistics from the simulated loads favorably compare with experimental results.

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