考虑替代模型不确定性的结构动力特性全局敏感性分析

万华平; 钟剑; 任伟新

doi:10.21656/1000-0887.380018

考虑替代模型不确定性的结构动力特性全局敏感性分析

doi: 10.21656/1000-0887.380018

合肥工业大学土木与水利工程学院, 合肥 230009

基金项目: 国家自然科学基金(51508144; 51608161);中国博士后科学基金(2015M581981;2016M602007);香江学者计划项目(XJ2016039);安徽省自然科学基金(1608085QE118)

详细信息

作者简介:
万华平(1986—)，男，副教授(E-mail： huaping.wan@hfut.edu.cn; huaping.wan@gmail.com)；任伟新(1960—)，男，教授，博士，博士生导师(通讯作者. E-mail：renwx@hfut.edu.cn).

中图分类号: U443.6
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出版历程
- 收稿日期: 2017-01-15
- 修回日期: 2017-01-22
- 刊出日期: 2018-01-15

Global Sensitivity Analysis of Structural Dynamic Characteristics Considering Metamodel Uncertainty

School of Civil and Hydraulic Engineering, Hefei University of Technology, Hefei 230009, P.R.China

Funds: The National Natural Science Foundation of China(51508144; 51608161);China Postdoctoral Science Foundation(2015M581981; 2016M602007)

摘要

摘要: 结构参数的不确定性必然导致其动力特性具有不确定性，全局敏感性分析是定量各不确定参数动力特性影响大小的有效手段但是全局敏感性分析具有计算花费高的问题，为此采用快速Gauss(高斯)过程模型来降低计算成本此外，该文采用的是全局Gauss过程模型而不是它的均值函数来进行全局敏感性分析，考虑了替代模型不确定性，给出了敏感性指标的分布该方法的可靠性通过具有解析敏感性指标值的测试函数得到验证最后，将该方法用于安庆铁路长江大桥动力特性的敏感性分析
- 替代模型不确定性 /
- 动力特性 /
- Gauss过程模型 /
- 全局敏感性分析 /
- 桥梁结构
Abstract: Uncertainty of structural parameters will unavoidably lead to uncertainty of structural natural frequencies. The global sensitvity analysis (GSA) is an effective approach to quantify the contributions of individual parameters to the induced uncertainty of dynamic characteristics. However, the GSA has the issue of high computational cost that needs to be addressed. The fast-running Gaussian process model (GPM) was used as a surrogate for the costly computer models, to reduce the computational burden of the GSA. Moreover, the influence of the metamodel uncertainty associated with the GPM was taken into account. The effectiveness of the presented GPM-based method for the GSA was verified with a test function. Finally the GPM-based approach was applied to the GSA of structural dynamic characteristics of the Anqing Yangtze River Railway Bridge.
- metamodel uncertainty /
- dynamic characteristic /
- Gaussian process model /
- global sensitivity analysis /
- bridge structure

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参考文献(13)

[1]	OAKLEY J E, O’HAGAN A. Probabilistic sensitivity analysis of complex models: a Bayesian approach[J]. Journal of the Royal Statistical Society: Series B (Statistical Methodology),2004,66(3): 751-769.
[2]	CHEN Wei, JIN Ruichen, SUDJIANTO A. Analytical variance-based global sensitivity analysis in simulation-based design under uncertainty[J]. Journal of Mechanical Design,2005,127(5): 875-886.
[3]	ROHMER J, FOERSTER E. Global sensitivity analysis of large-scale numerical landslide models based on Gaussian-process meta-modeling[J]. Computers & Geosciences,2011,37(7): 917-927.
[4]	WAN Huaping, REN Weixin. Parameter selection in finite-element-model updating by global sensitivity analysis using Gaussian process meta model[J]. Journal of Structural Engineering,2015,141(6): 04014164.
[5]	WAN Huaping, REN Weixin. A residual-based Gaussian process model framework for finite element model updating[J]. Computers & Structures,2015,156: 149-159.
[6]	WAN Huaping, REN Weixin. Stochastic model updating utilizing Bayesian approach and Gaussian process model[J]. Mechanical Systems and Signal Processing,2016,70/71: 245-268.
[7]	WAN Huaping, TODD M D, REN Weixin. Statistical framework for sensitivity analysis of structural dynamic characteristics[J]. Journal of Engineering Mechanics,2017,143(9): 04017093.
[8]	YAN Wangji, WAN Huaping, REN Weixin. Analytical local and global sensitivity of power spectrum density functions for structures subject to stochastic excitation[J]. Computers & Structures,2017,182: 325-336.
[9]	RASMUSSEN C E, WILLIAMS C K I. Gaussian Processes for Machine Learning [M]. The MIT Press, 2006.
[10]	SANTNER T J, WILLIAMS B J, NOTZ W I.The Design and Analysis of Computer Experiments [M]. Berlin: Springer, 2003.
[11]	EFRON B, STEIN C. The jackknife estimate of variance[J]. The Annals of Statistics,1981,9(3): 586-596.
[12]	SOBOL I M. Sensitivity estimates for non-linear mathematical models[J].MMCE,1993,1(4): 407-414.
[13]	TARANTOLA S, BECKER W, ZEITZ D. A comparison of two sampling methods for global sensitivity analysis[J]. Computer Physics Communications,2012,183(5): 1061-1072.

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考虑替代模型不确定性的结构动力特性全局敏感性分析

doi: 10.21656/1000-0887.380018

作者简介:
万华平(1986—)，男，副教授(E-mail： huaping.wan@hfut.edu.cn; huaping.wan@gmail.com)；任伟新(1960—)，男，教授，博士，博士生导师(通讯作者. E-mail：renwx@hfut.edu.cn).

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Global Sensitivity Analysis of Structural Dynamic Characteristics Considering Metamodel Uncertainty

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考虑替代模型不确定性的结构动力特性全局敏感性分析

doi: 10.21656/1000-0887.380018

作者简介: 万华平(1986—)，男，副教授(E-mail： huaping.wan@hfut.edu.cn; huaping.wan@gmail.com)；任伟新(1960—)，男，教授，博士，博士生导师(通讯作者. E-mail：renwx@hfut.edu.cn).

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出版历程

Global Sensitivity Analysis of Structural Dynamic Characteristics Considering Metamodel Uncertainty

计量

出版历程

目录

作者简介:
万华平(1986—)，男，副教授(E-mail： huaping.wan@hfut.edu.cn; huaping.wan@gmail.com)；任伟新(1960—)，男，教授，博士，博士生导师(通讯作者. E-mail：renwx@hfut.edu.cn).