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<p>For seismic analysis in engineering structures, it is essential to consider the dynamic responses under seismic excitation, necessitating the description of seismic accelerations. The scarcity of seismic samples leads to incomplete uncertainty information, for which non-probabilistic methods provide a reasonable description. 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 (DES), 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. Furthermore, the proposed method can be extended to other complex engineering systems with time-variant spatial uncertainties, including nuclear reactor safety assessment and spacecraft dynamics.</p>

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Seismic analysis based on a new interval method with incomplete information

  • 期刊论文

  • 发表日期：

    2026年2月4日

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  • Shizhong Liang,
  • Yuxiang Yang,
  • Chen Li,
  • Feng Wu

摘要

For seismic analysis in engineering structures, it is essential to consider the dynamic responses under seismic excitation, necessitating the description of seismic accelerations. The scarcity of seismic samples leads to incomplete uncertainty information, for which non-probabilistic methods provide a reasonable description. 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 (DES), 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. Furthermore, the proposed method can be extended to other complex engineering systems with time-variant spatial uncertainties, including nuclear reactor safety assessment and spacecraft dynamics.