Shape optimization of a corner‐recessed square tall building to reduce mean wind pressure using a multi‐objective genetic algorithm

Abstract

The current study aims to determine how the corner recession affects tall buildings with square plans. A series of numerical simulations have been conducted to find the parametric models' wind pressure. Visualization tools, such as contour plots and streamlines, present the wind flow near the buildings. Numerical simulations are conducted using RANS k‐ℇ turbulence models considering a length scale of 1:300. Subsequently, a shape optimization study has been carried out to propose a suitable percentage of corner recession, which should minimize the wind pressure on different faces of the building. As design factors, the amount of corner recession (S) and the wind incidence angle (Ø) are taken, along with the mean pressure coefficients (Cp) on the various building faces. Due to the eight axes symmetry of the building configuration, the random sampling technique is used for the Design of Experiment while accounting for the 0°–45° wind angle of attack. The Response Surface Approximation (RSA) is used to construct surrogate models of the objective functions. The RSA models are validated with wind tunnel test results presented in previously published articles. The optimization study is carried out using the multi‐objective genetic algorithm technique.