Shape optimization of tall buildings cross‐section: Balancing profit and aeroelastic performance

Abstract

Shape optimization is an effective tool to improve the aerodynamic performance of tall buildings by introducing minor modifications to the original project. Nevertheless, economic criteria demand efficient cross sections aiming at maximizing the building's profitability. These two contradictory criteria are commonly handled by adopting multi‐objective optimization approaches seeking the definition of Pareto fronts. However, the aerodynamic nonlinear features of low‐aspect‐ratio cross sections typically adopted in architectural practice can cause wind‐induced acceleration response surfaces over the considered design domain with multiple local minima that eventually lead to discontinuous Pareto fronts with non‐convex regions. This study delves into this problem and proposes a design framework that effectively combines the reduced basis method with multi‐objective optimization techniques to carry out the aerodynamic shape optimization using surrogates trained with CFD simulations. The ability of the optimization strategy to properly define the non‐convex regions of discontinuous Pareto fronts is successfully leveraged by adopting the weighted min–max method.