Pan Wang

Northwestern Polytechnical University

22Publications

9H-index

254Citations

Publications 22

Newest

Global sensitivity analysis for multivariate outputs based on multiple response Gaussian process model

#1Fuchao Liu (NPU: Northwestern Polytechnical University)H-Index: 2

#2Pengfei Wei (NPU: Northwestern Polytechnical University)H-Index: 11

Last.Zhufeng Yue (NPU: Northwestern Polytechnical University)H-Index: 3

view all 5 authors...

Abstract The computational models in real-world applications commonly have multivariate dependent outputs of interest, and developing global sensitivity analysis techniques, so as to measure the effect of each input variable on each output as well as their dependence structure, has become a critical task. In this paper, a new moment-independent sensitivity index is firstly developed for quantifying the effect of each input variable on the dependence structure of model outputs. Then, the multiple...

#1Sinan Xiao (NPU: Northwestern Polytechnical University)H-Index: 9

#2Zhenzhou Lu (NPU: Northwestern Polytechnical University)H-Index: 7

Last.Pan Wang (NPU: Northwestern Polytechnical University)H-Index: 9

view all 3 authors...

In this article, a new set of multivariate global sensitivity indices based on distance components decomposition is proposed. The proposed sensitivity indices can be considered as an extension of the traditional variance‐based sensitivity indices and the covariance decomposition‐based sensitivity indices, and they have similar forms. The advantage of the proposed sensitivity indices is that they can measure the effects of an input variable on the whole probability distribution of multivariate mo...

Global sensitivity analysis based on distance correlation for structural systems with multivariate output

#1Sinan Xiao (NPU: Northwestern Polytechnical University)H-Index: 9

#2Zhenzhou Lu (NPU: Northwestern Polytechnical University)H-Index: 7

Last.Pan Wang (NPU: Northwestern Polytechnical University)H-Index: 9

view all 3 authors...

Abstract Models with multivariate output are often used in practical structural systems. Multivariate global sensitivity analysis (GSA) plays an important role in quantifying the contribution of uncertainty in the model input to the output, which is quite useful for simplifying the models and improving the model performance. Many traditional global sensitivity indices can be considered as dependence measures of model input and output. However, these dependence measures can only measure the depen...

Variance-based sensitivity analysis with the uncertainties of the input variables and their distribution parameters

#1Pan Wang (NPU: Northwestern Polytechnical University)H-Index: 9

#2Zhenzhou Lu (NPU: Northwestern Polytechnical University)H-Index: 7

Last.Sinan Xiao (NPU: Northwestern Polytechnical University)H-Index: 9

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ABSTRACTFor the structural systems with both the uncertainties of input variables and their distribution parameters, three sensitivity indices are proposed to measure the influence of input variables, distribution parameters and their interactive effects. With those sensitivity indices, analysts can make a decision that whether it is worth to accumulate data of one distribution parameter to reduce its uncertainty. Due to the large computational cost, the analytical solutions are derived for quad...

#1Sinan Xiao (NPU: Northwestern Polytechnical University)H-Index: 9

#2Zhenzhou Lu (NPU: Northwestern Polytechnical University)H-Index: 21

Last.Pan Wang (NPU: Northwestern Polytechnical University)H-Index: 9

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Abstract Dynamic models with time-dependent output are widely used in engineering for risk assessment and decision making. Global sensitivity analysis for these models is very useful for simplifying the model, improving the model performance, etc. The existent covariance decomposition based global sensitivity analysis method combines the variance based sensitivity analysis results of the model output at all the instants, which just utilizes the information of the time-dependent output in time do...

Copula-based decomposition approach for the derivative-based sensitivity of variance contributions with dependent variables

#1Pan Wang (NPU: Northwestern Polytechnical University)H-Index: 9

#2Zhenzhou Lu (NPU: Northwestern Polytechnical University)H-Index: 7

Last.Zhufeng Yue (NPU: Northwestern Polytechnical University)H-Index: 4

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Abstract Variance-based sensitivity analysis with dependent variables represents how the uncertainties and dependence of variables influence the output uncertainty. Since the distribution parameters of variables are difficult to be given precisely, this work defines the derivative-based sensitivity of variance contribution with respect to the distribution parameters, which reflects how small variation of distribution parameters influences the variance contributions. By introducing the copula fun...

#1Sinan Xiao (NPU: Northwestern Polytechnical University)H-Index: 9

#2Zhenzhou Lu (NPU: Northwestern Polytechnical University)H-Index: 7

Last.Pan Wang (NPU: Northwestern Polytechnical University)H-Index: 9

view all 3 authors...

In this paper, a new kind of multivariate global sensitivity index based on energy distance is proposed. The covariance decomposition based index has been widely used for multivariate global sensitivity analysis. However, it just considers the variance of multivariate model output and ignores the correlation between different outputs. The proposed index considers the whole probability distribution of dynamic output based on characteristic function and contains more information of uncertainty tha...

A generalized separation for the variance contributions of input variables and their distribution parameters

#1Pan Wang (NPU: Northwestern Polytechnical University)H-Index: 9

#2Zhenzhou Lu (NPU: Northwestern Polytechnical University)H-Index: 7

Last.Sinan Xiao (NPU: Northwestern Polytechnical University)H-Index: 9

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Abstract For the structural system with both the uncertainties of input variables and their distribution parameters, this work investigates the generalized separation approach by transforming the original variable into the auxiliary variable with arbitrary distribution. Based on the variance based sensitivity analysis, the generalized sensitivity measures can be given, which are used to identify the influences of the auxiliary variables and distribution parameters simultaneously. For the differe...

#1Pan Wang (NPU: Northwestern Polytechnical University)H-Index: 9

#2Zhenzhou Lu (NPU: Northwestern Polytechnical University)H-Index: 21

ABSTRACTTo reduce the output variance, the variance-based importance analysis can provide an efficient way by reducing the variance of the ‘important’ inputs. But with the reduction of the variance of those ‘important’ inputs, the input importance will change and it is no longer the most efficient way to reduce the variance of those ‘important’ inputs alone. Thus, analyst needs to consider reducing the variance of other inputs to obtain a more efficient way. This work provides a graphical soluti...

Efficient numerical simulation method for evaluations of global sensitivity analysis with parameter uncertainty

#1Zhang-Chun Tang (NPU: Northwestern Polytechnical University)H-Index: 5

#2Zhenzhou Lu (NPU: Northwestern Polytechnical University)H-Index: 21

Last.Peng Wang (University of Electronic Science and Technology of China)H-Index: 1

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Abstract In this study, we propose an efficient numerical simulation method for structural systems with both epistemic and aleatory uncertainties to evaluate the effect of epistemic uncertainty on the failure probability measured by variance-based sensitivity analysis. The direct evaluation of this effect requires a “triple-loop” crude sampling procedure, which is time consuming. To circumvent the difficulty associated with the direct sampling-based procedure, we first construct an improved impo...

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Co-Authors

Zhenzhou Lu

H-index : 21

Sinan Xiao

H-index : 9

Zhenzhou Lu

H-index : 7

Zhang Feng

H-index : 4

Zhang-Chun Tang

H-index : 5