State space enhanced subtraction average-based optimization for structural parameter identification with soil-structure interaction

This study developed a mechanical model of frame structures considering soil-structure interaction (SSI) based on Subtraction Average-Based Optimizer (SABO) algorithm and performs optimization of the physical parameters. Comparative validation with traditional Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) algorithms confirmed that the SABO algorithm exhibits superior convergence accuracy and computational efficiency. Subsequent verification using a 6-story Benchmark model and a 5-story Benchmark model incorporating SSI effects demonstrated that the errors between simulated acceleration and displacement results and measured data were within 10 %, proving the algorithm's applicability for SSI integrated frame models. Further refinement of parameter identification, particularly for soil mechanics, damping, and stiffness, and seismic response analysis, are achieved using experimental data from a shaking table test on a twelve-story frame structure. The results indicate that soft soil foundations reduce structural acceleration responses but increase displacement amplitudes. Furthermore, Shanghai bedrock seismic waves exhibit significantly lower acceleration and displacement peaks compared to Kobe waves and Chi-Chi waves. These findings quantitatively characterize the spectral modulation effects of SSI on high-rise structures under diverse seismic excitations, providing valuable insights into intelligent methodologies for evaluating structural parameters and seismic responses.