发表机构
Université Paris-Saclay; CEA; Service d’Études Mécaniques et Thermiques; CMAP; CNRS; École polytechnique; Institut Polytechnique de Paris; CEA, DAM, DIF（巴黎萨克雷大学; 法国替代能源和原子能委员会; 机械与热力学研究服务处; 应用数学中心; 法国国家科学研究中心; 巴黎综合理工学院; 巴黎理工学院; 法国替代能源和原子能委员会，达姆实验室，流体动力学部门）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文针对地震与结构参数联合不确定性下的楼层反应谱估计问题，提出多保真度蒙特卡洛方法，通过结合低、高保真模型降低计算成本与估计误差，经核电站反应堆厂房案例验证其适用性。
AI 中文摘要
楼层反应谱（FRS）是设计非结构构件（如设备或组件）的关键工具。由于多种物理现象会影响FRS，估计FRS可能需要采用主结构的高保真（HF）力学模型。但此类模型的数值模拟通常计算成本高昂，因此本文提出采用多保真度蒙特卡洛（MFMC）方法高效估计FRS。该方法依赖于快速低保真（LF）模型的观测值作为控制变量；若LF与HF样本的相关系数绝对值接近1，相较于仅基于HF数据样本的标准蒙特卡洛估计，此方法可同时降低方差与估计误差。通过针对柏崎刈羽核电站反应堆厂房的案例研究，我们验证了该方法适用于FRS估计的可行性：即便采用单自由度系统这类简单的LF模型，它仍能有效降低方差与估计误差；同时表明该方法在考虑建模不确定性的前提下仍能保持相当的性能，且其易用性使其成为从业者的实用工具。
英文摘要
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.
