An improved Bayesian collocation method for steady-state response analysis of structural dynamic systems with large interval uncertainties

作者：

Highlights：

• An improved Bayesian collocation method (IBCM) is developed for structural steady-state response analysis with large interval uncertainties.

• Sequential Gaussian process surrogate model is applied for interval analysis.

• A bi-directional sampling strategy is proposed to guide to search the extrema.

• A decayed weight function is presented to balance exploration and exploitation in highly nonlinear cases.

摘要

•An improved Bayesian collocation method (IBCM) is developed for structural steady-state response analysis with large interval uncertainties.•Sequential Gaussian process surrogate model is applied for interval analysis.•A bi-directional sampling strategy is proposed to guide to search the extrema.•A decayed weight function is presented to balance exploration and exploitation in highly nonlinear cases.

论文关键词：Interval uncertainty,Uncertainty quantification,Surrogate model,Gaussian process,Steady-state response analysis

论文评审过程：Received 16 September 2019, Revised 2 February 2021, Accepted 8 July 2021, Available online 26 July 2021, Version of Record 26 July 2021.

论文官网地址：https://doi.org/10.1016/j.amc.2021.126523