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Entropy 2018, 20(3), 202; https://doi.org/10.3390/e20030202

Global Reliability Sensitivity Analysis Based on Maximum Entropy and 2-Layer Polynomial Chaos Expansion

1
School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China
2
Science and Technology on Reliability and Environmental Engineering Laboratory, Beihang University, Beijing 100191, China
3
CRRC ZIC Research Institute of Electrical Technology & Material Engineering, Zhuzhou 412001, China
*
Author to whom correspondence should be addressed.
Received: 5 February 2018 / Revised: 13 March 2018 / Accepted: 14 March 2018 / Published: 16 March 2018
(This article belongs to the Special Issue Maximum Entropy and Its Application II)
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Abstract

To optimize contributions of uncertain input variables on the statistical parameter of given model, e.g., reliability, global reliability sensitivity analysis (GRSA) provides an appropriate tool to quantify the effects. However, it may be difficult to calculate global reliability sensitivity indices compared with the traditional global sensitivity indices of model output, because statistical parameters are more difficult to obtain, Monte Carlo simulation (MCS)-related methods seem to be the only ways for GRSA but they are usually computationally demanding. This paper presents a new non-MCS calculation to evaluate global reliability sensitivity indices. This method proposes: (i) a 2-layer polynomial chaos expansion (PCE) framework to solve the global reliability sensitivity indices; and (ii) an efficient method to build a surrogate model of the statistical parameter using the maximum entropy (ME) method with the moments provided by PCE. This method has a dramatically reduced computational cost compared with traditional approaches. Two examples are introduced to demonstrate the efficiency and accuracy of the proposed method. It also suggests that the important ranking of model output and associated failure probability may be different, which could help improve the understanding of the given model in further optimization design. View Full-Text
Keywords: global reliability sensitivity analysis; polynomial chaos expansion; Sobol’s indices; the maximum entropy method global reliability sensitivity analysis; polynomial chaos expansion; Sobol’s indices; the maximum entropy method
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Zhao, J.; Zeng, S.; Guo, J.; Du, S. Global Reliability Sensitivity Analysis Based on Maximum Entropy and 2-Layer Polynomial Chaos Expansion. Entropy 2018, 20, 202.

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