We analyzed the datasets of the flow fields at a pedestrian level around a 1:1:2 isolated block model obtained by a large eddy simulation. The purpose was to understand the effect of the block on the probability density distributions of each velocity component and wind speed, and to propose a reasonable model to predict the percentile values of wind speed (exceeding wind speeds) for the pedestrian level. The probability density distributions were skewed, especially near the block side, whereas other vicinities of the front and wake of the block did not cause significant change in the distributions. Consequently, the probability density distributions were standardized using mean and standard deviations to compare with the normal distribution. Clearly, rare wind events had an occurrence frequency of less than 10%, which shows large discrepancies from the normal distribution. Accordingly, the exceeding wind speeds for each velocity component and magnitude were determined. The exceeding wind speeds of each velocity component were poorly estimated by the mean wind speed. Nonetheless, better prediction of the exceeding wind speed of each velocity component is possible by using the peak factor. By contrast, the exceeding wind speed of the velocity magnitude is clearly proportional to the mean wind speed.
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