Multi-fidelity Monte Carlo estimation of floor response spectra under combined seismic and structural parameter uncertainties

2026-09-01

AI Summary

本文提出了一种多保真度蒙特卡洛方法，用于在地震和结构参数不确定性下高效估计楼层响应谱，通过高低保真度模型结合减少估计误差。

Abstract

Floor response spectra (FRS) are essential tools for the design of non-structural elements (such as equipment or components). Given the various physical phenomena influencing FRS, high-fidelity (HF) mechanical models of the primary structure may be required to estimate them. Since numerical simulations based on such models are generally computationally expensive, this paper proposes using a multi-fidelity Monte Carlo (MFMC) approach for the efficient estimation of FRS. The method relies on using observations from a fast low-fidelity (LF) model as control variables. If the absolute value of the correlation between LF and HF samples is close to 1, this approach reduces both variance and estimation error compared to a standard Monte Carlo estimate based solely on HF data samples. Through a case study involving the reactor building of the Kashiwazaki-Kariwa nuclear power plant, we demonstrate the suitability of this method for FRS estimation. It effectively reduces variance and estimation error, even when using a LF model as simple as a single-degree-of-freedom system. We also show that the method accounts for modeling uncertainties while maintaining comparable performance. Its ease of use makes it a valuable tool for practitioners.

Problem

• Floor Response Spectra
• Seismic Uncertainty
• Structural Parameter Uncertainty
• Multi-fidelity Monte Carlo

Innovation

• Multi-fidelity Monte Carlo
• Floor Response Spectra
• Variance Reduction
• Estimation Error
• Low-Fidelity Model