Simulation Study of New Buckling Restraint Bracing Based on Bayesian Optimization Algorithm to Identify the Parameters of Modified Bouc–Wen Model

Abstract

The introduction of new materials can significantly improve the performance of existing dampers, but the constitutive model of new materials is difficult to be obtained in a short time, which makes its numerical simulation difficult. Bouc–Wen–Baber–Noori (BWBN) model can well describe the stress-strain relationship of materials, and it is helpful to introduce new materials into numerical simulation. In this paper, a new high manganese steel material is used to fabricate buckling restrained brace, and based on the improved Transition Markov Chain Monte Carlo (iTMCMC) sampling method and Bayesian reasoning, a new parameter identification of BWBN model is completed; model parameters are introduced into OpenSees to complete the response analysis of the new steel damper in the structure. It provides a new method and approach for introducing new materials into structural seismic resistance and proves its reliability.