Application of artificial neural network for predicting dynamic along‐wind response of tall buildings

Summary This paper presents the simplified approach based on the artificial neural network (ANN) for predictions of the dynamic along‐wind response in the context of the Indian Wind Standard IS 875 (Part 3): 2015. This standard provides direct guidelines for the specific aspect ratio of buildings (h/b ratio as 3, 5, 10, and 20) for assessing along‐wind loads. Evaluation of dynamic wind load and its responses, for the aspect ratio not specified in the IS 875 (Part 3): 2015, may have to be estimated by the boundary layer wind tunnel experiment or other computational techniques. Both the experimentation and computational methods are expensive in terms of time and the resources required. Alternatively, ANN is an efficient and cost‐effective computational technique that can be employed to estimate the dynamic wind response of a building. In this paper, ANN predicted estimations are presented for calculating dynamic along‐wind base shear and base bending moment of a tall building. The response is generated using the best fit ANN model for the aspect ratio (h/b) ranging in between 3 and 20. Finally, these responses were used to propose a simplified empirical equation as a function of aspect ratio, side ratio, wind velocity, and terrain category. Furthermore, charts were developed for calculating the story shear force and story bending moments for the building heights varying from 100 to 250 m. The proposed new approach is one of the quick evaluators for dynamic along‐wind response of the tall buildings.