Investigating Scale Effects on Analytical Methods of Predicting Peak Wind Loads on Buildings
Large-scale testing of low-rise buildings or components of tall buildings is essential as it provides more representative information about the realistic wind effects than the typical small scale studies, but as the model size increases, relatively less large-scale turbulence in the upcoming flow can be generated. This results in a turbulence power spectrum lacking low-frequency turbulence content. This deficiency is known to have significant effects on the estimated peak wind loads. To overcome these limitations, the method of Partial Turbulence Simulation (PTS) has been developed recently in the FIU Wall of Wind lab to analytically compensate for the effects of the missing low-frequency content of the spectrum. This method requires post-test analysis procedures and is based on the quasi-steady assumptions. The current study was an effort to enhance that technique by investigating the effect of scaling and the range of applicability of the method by considering the limitations risen from the underlying theory, and to simplify the 2DPTS (includes both in-plane components of the turbulence) by proposing a weighted average method. Investigating the effect of Reynolds number on peak aerodynamic pressures was another objective of the study. The results from five tested building models show as the model size was increased, PTS results showed a better agreement with the available field data from TTU building. Although for the smaller models (i.e., 1:100,1:50) almost a full range of turbulence spectrum was present, the highest peaks observed at full-scale were not reproduced, which apparently was because of the Reynolds number effect. The most accurate results were obtained when the PTS was used in the case with highest Reynolds number, which was the1:6 scale model with a less than 5% blockage and a xLum/bm ratio of 0.78. Besides that, the results showed that the weighted average PTS method can be used in lieu of the 2DPTS approach. So to achieve the most accurate results, a large-scale test followed by a PTS peak estimation method deemed to be the desirable approach which also allows the xLum/b m values much smaller than the ASCE recommended numbers.
Moravej, Mohammadtaghi, "Investigating Scale Effects on Analytical Methods of Predicting Peak Wind Loads on Buildings" (2018). ProQuest ETD Collection for FIU. AAI13805811.