Modelling of Shear Walls with Opening Using Machine Learning Techniques

A Shear wall is the most appropriate structure shape in reinforced concrete buildings. Thus, examining the Shear Wall in structural systems is vital because it effectively resists lateral loads such as wind and seismic forces. The behaviour of such reinforced concrete building with Shear Wall differs from that of other reinforced concrete constructions. Thus, structural analysis of Shear Walls with openings for natural light, ventilation, entry, escape etc is required This factor has been analysed in terms of maximum storey displacement and base shear for model with Shear Walls and openings, using Equivalent static method to analyse the seismic performance of the structures. A comprehensive dataset is prepared using Staad Pro v8i software. The models are developed for the number of stories from 5 to 40, with different sizes of openings in the shear wall. A total of 240 models were analysed in III, IV and V zones of the earthquake, as defined by Indian code. The study involves the data set preparation and training, testing and validation using different machine learning techniques like deep neural networks, artificial neural networks and random forests. so that it will be helpful in predicting the seismic response of any similar multi-storey building in terms of Maximum storey displacement and Base shear.