Forecasting Aerodynamic Coefficients of Bi-Axial Symmetric C Plan-Shaped Tall Buildings Using ANFIS.

This study addressed the challenge of forecasting the critical Angle of Attack (AOA) for tall buildings, which can significantly affect wind forces. Extensive assessments are needed to optimise the wind force on a tall building, either by wind tunnel testing or computational fluid dynamics (CFD), using various combinations of AOA and corner cut (CC). This process is time-consuming and complex. This study aims to develop an Adaptive Neuro-Fuzzy Interface System (ANFIS) approach for rapidly and effectively obtaining aerodynamic coefficients. Hence, two symmetrical C-shaped tall buildings, subjected to AOAs ranging from 0° to 90° and different CC modifications, are numerically simulated using CFD, and the outcomes (force coefficient (C_F) and moment coefficient (C_M)) are used to train and test ANFIS model. The validation showed that the maximum error is less than 4%, indicating its excellent predictability. Furthermore, it is observed that for models A1 (C_F = 0.66 and C_M = 0.76) and A2 (C_F = 0.68 and C_M = 0.75), the minimum C_F and C_M at 90° AOA with a 30% CC are much lower, i.e., 45.4% and 38.7%, 43.3% and 41.4%, respectively than the maximum values at 0° AOA with 0% CC. This ANFIS model can predict aerodynamic coefficients for various combinations of CC and AOAs. [ABSTRACT FROM AUTHOR]