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Pengfei Wei
Northwestern Polytechnical University
37Publications
9H-index
316Citations
Publications 37
Newest
#1Jingwen Song (NPU: Northwestern Polytechnical University)H-Index: 6
#2Pengfei Wei (NPU: Northwestern Polytechnical University)H-Index: 9
Last.Zuxiang Lei (ECJTU: East China Jiaotong University)
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Abstract Non-intrusive Imprecise Stochastic Simulation (NISS) is a recently developed general methodological framework for efficiently propagating the imprecise probability models and for estimating the resultant failure probability functions and bounds. Due to the simplicity, high efficiency, stability and good convergence, it has been proved to be one of the most appealing forward uncertainty quantification methods. However, the current version of NISS is only applicable for model with input v...
#1Fuchao Liu (NPU: Northwestern Polytechnical University)H-Index: 1
#2Fuchao LiuH-Index: 2
Last.Zhufeng YueH-Index: 3
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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...
#1Sifeng BiH-Index: 3
#2Matteo BroggiH-Index: 9
Last.Michael BeerH-Index: 19
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Abstract The tendency of uncertainty analysis has promoted the transformation of sensitivity analysis from the deterministic sense to the stochastic sense. This work proposes a stochastic sensitivity analysis framework using the Bhattacharyya distance as a novel uncertainty quantification metric. The Bhattacharyya distance is utilised to provide a quantitative description of the P-box in a two-level procedure for both aleatory and epistemic uncertainties. In the first level, the aleatory uncerta...
#1Pengfei Wei (NPU: Northwestern Polytechnical University)H-Index: 9
#2Jingwen Song (NPU: Northwestern Polytechnical University)H-Index: 6
Last.Zhufeng Yue (NPU: Northwestern Polytechnical University)H-Index: 3
view all 7 authors...
© 2019 Elsevier Ltd Structural reliability analysis for rare failure events in the presence of hybrid uncertainties is a challenging task drawing increasing attentions in both academic and engineering fields. Based on the new imprecise stochastic simulation framework developed in the companion paper, this work aims at developing efficient methods to estimate the failure probability functions subjected to rare failure events with the hybrid uncertainties being characterized by imprecise probabili...
#1Pengfei Wei (NPU: Northwestern Polytechnical University)H-Index: 9
#2Jingwen Song (NPU: Northwestern Polytechnical University)H-Index: 6
Last.Zhufeng Yue (NPU: Northwestern Polytechnical University)H-Index: 3
view all 7 authors...
Abstract Uncertainty propagation through the simulation models is critical for computational mechanics engineering to provide robust and reliable design in the presence of polymorphic uncertainty. This set of companion papers present a general framework, termed as non-intrusive imprecise stochastic simulation , for uncertainty propagation under the background of imprecise probability. This framework is composed of a set of methods developed for meeting different goals. In this paper, the perform...
#1Jingwen Song (NPU: Northwestern Polytechnical University)H-Index: 6
#2Zhenzhou Lu (NPU: Northwestern Polytechnical University)H-Index: 18
Last.Pengfei Wei (NPU: Northwestern Polytechnical University)H-Index: 9
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AbstractIn many disciplines involving high-dimensional data, permutation variable importance measure (PVIM) based on random forest is widely used for importance ranking of model inputs. This work extends the traditional PVIM to investigate the regional effects of the internal value range of model inputs. The PVIM function is firstly defined to measure the residual PVIM when the distribution range of one input variable is reduced to its subranges. An efficient computational algorithm is developed...
#1Pengfei Wei (NPU: Northwestern Polytechnical University)H-Index: 9
#2Fuchao Liu (NPU: Northwestern Polytechnical University)H-Index: 2
Last.Chenghu Tang (NPU: Northwestern Polytechnical University)H-Index: 3
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Abstract In the context of structural system reliability, quantifying the relative importance of random input variables and failure modes is necessary for improving system reliability and simplifying the reliability-based design problems. We firstly introduce the reliability-based variable importance analysis (VIA) indices to structural systems for quantifying the individual, interaction and total effects of each random input variable on the system failure probability, and propose two new reliab...
#1Pengfei Wei (NPU: Northwestern Polytechnical University)H-Index: 9
#2Fuchao Liu (NPU: Northwestern Polytechnical University)H-Index: 2
Last.Zuotao Wang (NPU: Northwestern Polytechnical University)H-Index: 1
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Abstract This paper develops a new global sensitivity analysis (GSA) framework for computational models with input variables being characterized by second-order probability models due to epistemic uncertainties. Firstly, two graphical tools, called individual effect (IE) function and total effect (TE) function, are defined for identifying the influential and non-influential input variables. Secondly, two probabilistic GSA indices, called T-indices, are introduced for comparing the relative impor...
#1Wenxuan WangH-Index: 3
#2Hangshan GaoH-Index: 3
Last.Changcong ZhouH-Index: 2
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Identifying the parameters that substantially affect the time-dependent reliability is critical for reliability-based design of motion mechanism. The time-dependent local reliability sensitivity and global reliability sensitivity are the two effective techniques for this type of analysis. This work extends the first-passage method and PHI2 method, which are commonly used for estimating the time-dependent reliability, for efficiently estimating the time-dependent local reliability sensitivity and...
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