Multi-fidelity Monte Carlo estimation of floor response spectra under combined seismic and structural parameter uncertainties
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.
Related
- An unscented universal filter for joint input-state-parameter estimation of a partially measured system: an application to drive-by structural health monitoring
- A Structure-Preserving Semi-Lagrangian based bi-fidelity method for the Vlasov--Poisson system with uncertainties
- Active Pilot Sampling for Multi-fidelity Estimation in Stochastic Optimization
- Estimation with Quantized Parameter Side-Information
- Asymptotic approximation of sensitivities in finite dimensional continuous data assimilation with application to parameter estimation
BibTeX
@misc{baillie2026multifidelity,
title = {{Multi-fidelity Monte Carlo estimation of floor response spectra under combined seismic and structural parameter uncertainties}},
author = {Nils Baillie and Baptiste Kerleguer and Cyril Feau and Josselin Garnier and Fan Wang},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.01674},
eprint = {2609.01674},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.01674},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Multi-fidelity Monte Carlo estimation of floor response spectra under combined seismic and structural parameter uncertainties
AU - Nils Baillie
AU - Baptiste Kerleguer
AU - Cyril Feau
AU - Josselin Garnier
AU - Fan Wang
PY - 2026
DA - 2026/09/01
PB - arXiv
DO - 10.48550/arxiv.2609.01674
UR - https://arxiv.org/abs/2609.01674
AB - 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.
ER -