An Experimental Study of Non-Gaussian Properties of Tornado-like Loads on a Low-Rise Building Model

This paper focuses on the non-Gaussian properties of tornado pressure loading on a Texas Tech University (TTU) building model. External pressures of the model were measured at multiple radial positions in a two-celled tornado-like vortex generated by a tornado-like vortex simulator. High-order statistical moments of pressure coefficients were studied. The spatial distributions of non-Gaussian zones were presented and compared with the figure for boundary layer wind. Four exponential models were used to fit the probability density of tornado pressures. The peak factors obtained by five methods were also investigated. Results indicate that non-Gaussian regions of a low-rise building in a tornado-like vortex significantly differ from that in boundary layer wind. The peak pressure coefficients exhibit a maximum value near the end of windward eaves when the model is located at a tornadic core radius. The probability density of tornado pressure time series cannot be fitted by a single exponential distribution. The gamma distribution and generalized extreme value (GEV) distribution can describe the probabilistic behavior of pressure coefficients at the most unfavorable load position. Compared with other methods, the skewness-dependent peak factor method exhibits the advantages of reliable results, easy calculation, and wide applicability.

Automated summary

This paper investigates the non-Gaussian characteristics of tornado pressure loading on a Texas Tech University building model. Measurements of external pressures were taken at multiple radial positions in a tornado-like vortex generated by a simulator. High-order statistical moments of pressure coefficients were studied and compared with the figure for boundary layer wind. Four exponential models were used to fit the probability density of tornado pressures. Results show that non-Gaussian regions of a low-rise building in a tornado-like vortex differ significantly from that in boundary layer wind. The probability density of tornado pressure time series cannot be fitted by a single exponential distribution.