Reliability analysis of structural system with multiple failure modes and mixed uncertain input variables

Wei, Pengfei; Lü, Zhenzhou; Ren, Bo

doi:10.1177/0954406212466010

Cited by 24 publications

(3 citation statements)

References 27 publications

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“…To determine the structural failure mode, the most formidable task is to determine the relationship between overall structure failure and individual component failure to determine when the failure of an individual component has occurred and whether the overall structure is still safe or not [23,24]. In this study, a practical technique for searching the structural failure mode proposed is mainly based on the degree of static indeterminacy of the overall structure [25]. The proposed technique can be described as the following steps:…”

Section: Structural Failure Modementioning

confidence: 99%

A Novel Approach to Evaluate the Time-Variant System Reliability of Deteriorating Concrete Bridges

Tian

Chen

2015

Mathematical Problems in Engineering

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Bridge time-variant system reliability is a useful measure to evaluate the lifetime performance of deteriorating bridge structures under uncertainty and is an influential performance indicator in bridge maintenance management programs. This paper proposes a computational methodology based on the Monte Carlo simulations for evaluating the time-variant system reliability of concrete bridges under environmental attacks. Methods related to the reduction of concrete sections and the variation of the load effects acting on the components are investigated using a finite element-based computational program, CBDAS (Concrete Bridge Durability Analysis System), to perform the assessment of lifetime structural performance. With regard to system reliability, a practical technique for searching the structural failure mode is also presented and a program, SRMCS (System Reliability by Monte Carlo Simulations), based on the Monte Carlo simulations is written to calculate and evaluate the structural system reliability of deteriorating concrete bridges. Finally, three numerical examples are presented to display the CBDAS and SRMCS functions.

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Section: Structural Failure Modementioning

confidence: 99%

A Novel Approach to Evaluate the Time-Variant System Reliability of Deteriorating Concrete Bridges

Tian

Chen

2015

Mathematical Problems in Engineering

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“…Wei et al. 14 combined the addition law of failure probability with the linear programming-based bounded method and used these techniques to address structural systems with multiple failure modes and only random inputs. Song et al.…”

Section: Introductionmentioning

confidence: 99%

Direct integration method based on dual neural networks to solve the structural reliability of fuzzy failure criteria

2019

Proceedings of the Institution of Mechanical Engineers, Part C:

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In practical engineering, fuzzy failure criteria can reflect the actual conditions of the normal use and durability of structures. Therefore, this topic has garnered considerable research attention. First, a fuzzy set and a membership function were proposed in this study. A fuzzy reliability mathematical model of structures was obtained by means of the fuzzy random event probability. Second, the distribution forms of common membership functions were introduced, and the optimal membership function was selected based on the Akaike information criterion. Third, considering the difficulty of calculating multiple integrals in the fuzzy reliability mathematical model, a direct integration method based on dual neural networks was introduced. This method provides a new approach for calculating structural reliability with the fuzzy failure criteria. Finally, the proposed method was verified by numerical examples. The results showed that this method could solve structural fuzzy reliability problems with multidimensional random variables with high computational efficiency and accuracy.

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“…11 In many cases, such model parameter uncertainty can be quantified by the epistemic uncertainty. Some nonprobabilistic methods can be used to represent the epistemic uncertainty, such as the Dempster-Shafer (D-S) evidence theory, 12 the fuzzy theory, 13,14 the interval theory, 15 etc. The D-S evidence theory has received considerable attentions in the field of uncertainty reasoning, 12 decision-making analysis, 16 and so forth, and some attempts have been made to study the influence of epistemic uncertainty on the FTA in the context of the D-S evidence theory.…”

Section: Introductionmentioning

confidence: 99%

Evidential network-based failure analysis for systems suffering common cause failure and model parameter uncertainty

Zuo

Xiahou

Liu

2018

Proceedings of the Institution of Mechanical Engineers, Part C:

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The fault tree analysis has been extensively implemented in failure analysis of engineered systems. In most cases, the probabilities of basic events, e.g. components’ failures, are represented by crisp values in the fault tree analyses. However, due to lack of knowledge, scarcity of failure data, or vague judgments from experts, it may produce parameter uncertainty associated with degradation models of components/systems, and such model parameter uncertainty can be quantified by the epistemic uncertainty. In addition, the common cause failure, related to the simultaneous failures of two or more components caused by physical interactions or shared environments, often exists in advanced engineered systems and computing systems. In this paper, by considering both the common cause failure and the epistemic uncertainty associated with model parameters, an evidential network model embedded with common cause failure is proposed to facilitate system failure analysis. The detailed transformations from some logic gates of a fault tree to an evidential network model are given. Moreover, the conditional belief mass tables are constructed to quantify the dependency between the states of components and the entire system. An engineering case of an aero-engine oil system, together with comparative results, is presented to demonstrate the effectiveness of the proposed evidential network model.

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Reliability analysis of structural system with multiple failure modes and mixed uncertain input variables

Cited by 24 publications

References 27 publications

A Novel Approach to Evaluate the Time-Variant System Reliability of Deteriorating Concrete Bridges

A Novel Approach to Evaluate the Time-Variant System Reliability of Deteriorating Concrete Bridges

Direct integration method based on dual neural networks to solve the structural reliability of fuzzy failure criteria

Evidential network-based failure analysis for systems suffering common cause failure and model parameter uncertainty

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