Seismic analysis based on a new interval method with incomplete information

TL;DR

This paper introduces an efficient interval method for seismic analysis of structures under incomplete uncertainty information, improving computational efficiency while maintaining accuracy.

Contribution

It proposes a new dynamic evolution strategy (DES-ES) and a framework (DES-ES-SS) for interval seismic analysis, enhancing efficiency over traditional Monte Carlo methods.

Findings

DES-ES outperforms CMA-ES in efficiency

DES-ES-SS maintains accuracy for stationary and non-stationary seismic accelerations

Numerical experiments validate improved computational performance

Abstract

For seismic analysis in engineering structures, it is essential to consider the dynamic responses under seismic excitation, necessitating the description of seismic accelerations. Limit seismics samples lead to incomplete uncertainty information, which is described by the non-probabilistic method reasonable. This study employs the minimum interval radius-based interval process (MRIP) based on the convex model to describe the time-variant uncertain seismic acceleration, subsequently conducting uncertainty analysis for seismic structures. However, the Monte Carlo simulation for uncertainty analysis requires extensive deterministic computations to ensure accuracy, exhibiting poor computational efficiency. To address this issue, this paper first improves the covariance matrix adaptation evolution strategy (CMA-ES) through the dynamic evolution sequence, proposing DES-ES, whose efficiency is validated to be higher than that of CMA-ES. Furthermore, leveraging the dependency of the responses, a computational framework named DES-ES-SS is proposed. Numerical experiments demonstrate that DES-ES-SS improves computational efficiency while maintaining the accuracy of the interval uncertainty analysis of the seismic structures whether the seismic acceleration is stationary or non-stationary.