Investigation of inelastic response ratios for buildings with damping subjected to near-fault ground motions using numerical simulations and transformer-based models

Inelastic responses are used in seismic design to estimate inelastic seismic demand from known elastic demand, yet current provisions remain limited, especially when damping and displacement ductility are considered. This study investigated the inelastic displacement ratio and inelastic velocity ratio for single degree of freedom (SDOF) systems subjected to near-fault ground motions, with particular focus on the effects of fling-step and forward-directivity motions. For numerical modeling and analysis, an extensive nonlinear response history analysis (NLRHA) was conducted on SDOF systems incorporating parametric variations in dynamic characteristics of structural systems such as elastic period, displacement ductility, and viscous damping under different ground motion conditions. From numerical modeling, empirical equations are proposed to express the inelastic displacement ratio ( I R D ) and inelastic velocity ratio ( I R V ) using elastic period, viscous damping ratio, displacement ductility, and the type of ground motion. In parallel, neural networks are trained on a dataset of 36,456 samples using additional variables, including the predominant period of the ground motion, moment magnitude, and closest rupture distance. Neural network models achieved R 2 = 0 . 944 (for I R D ) and R 2 = 0 . 916 (for I R V ) for unseen data, indicating the highest accuracy. Model explanations indicated that the predictions adhere to the domain knowledge. Comparative assessments reveal that while empirical equations capture general trends for design purposes, neural network models accurately predict even minor variations in inelastic responses. These data-driven methods provide a complementary approach in predicting the inelastic response compared to empirical equations. • Numerically simulated the inelastic responses of SDOF systems with damping under near-fault motions. • Influence of the ductility and viscous damping on inelastic responses was evaluated. • Empirical equations are proposed to estimate the inelastic displacement and velocity ratios. • Transformer-based models are developed to predict the inelastic responses.