A Generalized Artificial Neural Network for Displacement-Based Seismic Design of Mass Timber Rocking Walls

Abstract

ABSTRACT Displacement-based seismic design often requires nonlinear time history simulation of building responses which is computationally intensive. This technical note presents an artificial neural network (ANN) designed to generate max inter-story drift for buildings with post-tensioned mass timber (MT) rocking walls systems. This particular lateral system was selected because it is an innovative system with limited physical design parameters, making it an ideal candidate for ANN. The proposed model achieved significantly higher computational efficiency than time history simulation, while maintaining similar level of accuracy. The proposed method could potentially be used for automated design of MT rocking wall lateral systems.