WAN Huaping, ZHONG Jian, REN Weixin. Global Sensitivity Analysis of Structural Dynamic Characteristics Considering Metamodel Uncertainty[J]. Applied Mathematics and Mechanics, 2018, 39(1): 1-10. doi: 10.21656/1000-0887.380018
Citation: WAN Huaping, ZHONG Jian, REN Weixin. Global Sensitivity Analysis of Structural Dynamic Characteristics Considering Metamodel Uncertainty[J]. Applied Mathematics and Mechanics, 2018, 39(1): 1-10. doi: 10.21656/1000-0887.380018

Global Sensitivity Analysis of Structural Dynamic Characteristics Considering Metamodel Uncertainty

doi: 10.21656/1000-0887.380018
Funds:  The National Natural Science Foundation of China(51508144; 51608161);China Postdoctoral Science Foundation(2015M581981; 2016M602007)
  • Received Date: 2017-01-15
  • Rev Recd Date: 2017-01-22
  • Publish Date: 2018-01-15
  • 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.
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  • [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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