Seismic response prediction and parameters estimation of the frame structure equipped with the base isolation-fluid inerter system (FS-BIFI) based on the PI-LSTM model

Abstract

This paper introduces a novel approach, the physics-informed long short-term memory (PI-LSTM) model, to address the forward and inverse problems of the frame structure equipped with the base isolation-fluid inerter system (FS-BIFI). Validation of the PI-LSTM model's effectiveness is demonstrated through a numerical case study of a single-story FS-BIFI. Employing this approach, the PI-LSTM model accurately predicted displacement and acceleration responses of a three-story FS-BIFI. Moreover, it conducts an evaluation of unknown damping-related parameters (β1, β2) and a stiffness-related parameter (μ) of the fluid inerter mounted on the FS-BIFI. The model demonstrates a robust confidence value of 96.68% in predicting response error values within the range of [− 10%, 10%]. Notably, the relative errors in estimating unknown parameters (β1, β2, μ) stand at 12.760%, 8.857%, and 3.750%, respectively. The results show that the PI-LSTM model has great potential for response prediction and parameter inversion of complex structural systems.