Investigation on the Aerodynamic Parameters of the Triangle Shape of Tall Buildings by Using of CFD Method

Wind loading in large buildings has always been a major challenge for civilian engineers. For this purpose, presenting the optimum exterior forms of a building exposed to the wind flow and analyzing aerodynamic forces, including resistance force, bending, and twisting moments, are challenging issues for designers. Nowadays, by combining various numerical calculation methods, like neural networks, genetic algorithms, and other methods, by changing some parameters, they optimize the external form of the building based on aerodynamic parameters. In this research, three optimized triangular models will be investigated using the computational fluid dynamics method. For wind flow, a velocity profile is used in the three simulations, and Reynolds’ Navier–Stokes average equations are used to solve momentum relationships. Additionally, the κ-ε method was used to calculate Reynolds stresses. The results show that the optimized N3 model is in the most optimal condition possible in terms of aerodynamic parameters such as drag, torsion moment, and vortices behind the building. Nowadays, the neural network algorithm is one of the most famous numerical methods for optimizing hull shapes. However, this approach cannot improve aerodynamic parameters either. Hence, computational fluid dynamics is used to deeply analyze. This research is one step forward to assess the optimized hull shapes of tall buildings. All tests are conducted using STAR CCM+.