Parametric identification of seismic isolators using differential evolution and particle swarm optimization

•This paper is concerned with the parametric identification of seismic isolators.•The Bouc–Wen model is considered to simulate the hysteretic response.•Parametric identification is performed using two soft computing techniques.•Experimental data are carried out from standardized qualification tests.•Good agreement is found between experimental data and numerical simulations.

The objective of a base isolation system is to decouple the building from the damaging components of the earthquake by placing isolators between the superstructure and the foundation. The correct identification of these devices is, therefore, a critical step towards reliable simulations of base-isolated systems subjected to dynamic ground motion. In this perspective, the parametric identification of seismic isolators from experimental dynamic tests is here addressed. In doing so, the focus is on identifying Bouc–Wen model parameters by means of particle swarm optimization and differential evolution. This paper is especially concerned with the assessment of these non-classical parametric identification techniques using a standardized experimental protocol to set out the dynamic loading conditions. A critical review of the obtained outputs demonstrates that particle swarm optimization and differential evolution can be effectively exploited for the parametric identification of seismic isolators.

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