Extensions of Stochastic Optimization Results to Problems with System Failure Probability Functions

Purpose This paper aims to develop a method for evaluating the failure probability and global sensitivity of multiple failure modes based on convex-probability hybrid uncertainty. Design/methodology/approach The uncertainty information of the input variable is considered as convex-probability hybrid uncertainty. Moment-independent variable global sensitivity index based on the system failure probability is proposed to quantify the effect of the input variable on the system failure probability. Two-mode sensitivity indices are adopted to characterize the effect of each failure mode on the system failure probability. The method based on active learning Kriging (ALK) model with a truncated candidate regions (TCR) is adopted to evaluate the systems failure probability, as well as sensitivity index and this method is termed as ALK-TCR. Findings The results of five examples demonstrate the effectiveness of the sensitivity index and the efficiency of the ALK-TCR method in solving the problem of multiple failure modes based on the convex-probability hybrid uncertainty. Originality/value Convex-probability hybrid uncertainty is considered on system reliability analysis. Moment-independent variable sensitivity index based on the system failure probability is proposed. Mode sensitivity indices are extended to hybrid uncertain reliability model. An effective global sensitivity analysis approach is developed for the multiple failure modes based on convex-probability hybrid uncertainty.

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The variability of system failure probability

Reliability Engineering ◽

10.1016/0143-8174(84)90045-3 ◽

1984 ◽

Vol 9 (2) ◽

pp. 117-125 ◽

Cited By ~ 2

Author(s):

D.C. Connors

Keyword(s):

Failure Probability ◽

System Failure

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A New Concept for Assessing System Reliability Based on Probability Decomposition Method

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.353-358.2525 ◽

2007 ◽

Vol 353-358 ◽

pp. 2525-2528

Author(s):

Yang Pei ◽

Bi Feng Song ◽

Qing Han

Keyword(s):

Failure Probability ◽

System Reliability ◽

Decomposition Method ◽

Fault Tree Analysis ◽

System Failure ◽

Reliability Design ◽

Critical States ◽

Component Importance ◽

Probability Concept ◽

Probability Decomposition

In fault tree analysis, the system failure probability and the component importance measures cannot totally include the contribution of all the component existing states to system reliability. It is for this reason that an ‘equivalent’ failure probability concept is proposed. First, the system existing states are analyzed by probability decomposition method. Then Markov chain method and the expectation theory are used to calculate the expected working number resulting in system failure. And the system equivalent failure probability is finally attained. Analysis shows that: (1) equivalent failure probability not only includes the contribution of critical states of component to system reliability, but also the non-critical states of component are considered; and (2) it may provide a thorough assessment of system reliability and is useful for reliability design.

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Stability Analysis of Soil Nailing Supporting Structure Based on System Failure Probability Method

Earthwork Project Management, Slope Stability Analysis, and Wave-Based Testing Techniques ◽

10.1061/9780784478523.006 ◽

2014 ◽

Author(s):

Jian Liu ◽

Ke Shang ◽

Xing Wu

Keyword(s):

Stability Analysis ◽

Failure Probability ◽

Probability Method ◽

System Failure ◽

Soil Nailing ◽

Supporting Structure

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Editorial for the Special Issue on “Fault Trees and Attack Trees: Extensions, Solution Methods, and Applications”

Information ◽

10.3390/info12040175 ◽

2021 ◽

Vol 12 (4) ◽

pp. 175

Author(s):

Daniele Codetta-Raiteri

Keyword(s):

Reliability Analysis ◽

Failure Probability ◽

System Failure ◽

Special Issue ◽

Fault Trees ◽

Qualitative And Quantitative ◽

Minimal Cut Sets ◽

Minimal Cut ◽

Attack Trees ◽

Solution Methods

Fault Trees are well-known models for the reliability analysis of systems, used to compute several kinds of qualitative and quantitative measures, such as minimal cut-sets, system failure probability, sensitivity (importance) indices, etc [...]

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