System reliability analysis for mixed uncertain variables

Adduri, Phani R.; Penmetsa, Ravi

doi:10.1016/j.strusafe.2009.02.001

Cited by 43 publications

(29 citation statements)

References 15 publications

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“…The BPA function m D ðAÞ is calculated through equation (24). Thereby, its BPA (c) is shown in Table 6 P f ½SEAðx 1 , x 2 Þ À SEA 0 0 ¼ 111:6028 þ 0:0861x 1 À 11:5445x 2 þ 17571x 3 þ 0:0029x 2 1 þ 1:4128x 2 2 À 344410x 2 3 À 0:0631x 1 x 2 À 11:9867x 1 x 3 À 243:3111x 2 x 3 À 60 ð31Þ P f ½P 0 À Pðx 1 , x 2 Þ 0 ¼ 10 À 0:4322x 1 À 0:2064x 2 þ 5454:3x 3 þ 0:0018x 2 1 À 0:4288x 2 2 À 85077x 2 3 þ 0:0305x 1 x 2 À 25:9777x 1 x 3 þ 164:1223x 2 x 3 þ 66:9557…”

Section: Examplementioning

confidence: 99%

Hybrid reliability analysis for energy-absorbing composite structures based on evidence theory

Duan

Yang

Tao

et al. 2014

Journal of Reinforced Plastics and Composites

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It is important to investigate the uncertain modeling and reliability analysis for the crashworthiness capacity of composite energy-absorbing structures (CEAS) in which there are random and epistemic uncertainty. A probability-evidence theory hybrid uncertainty model and a corresponding efficient reliability analysis method for the crashworthiness capacity of CEAS are presented in this paper. In this method, evidence theory is introduced to address the difficulties in the epistemic uncertain modeling due to the lack of experimental samples, which expand greatly the applicability of reliability analysis technology in the crashworthiness capacity of CEAS research. Moreover, the probability theory is applied to address the random uncertainty. Based on the traditional equivalence normalization method, a probability-evidence theory hybrid reliability analysis model for the crashworthiness capacity of CEAS is developed. An explicit finite element analysis is used to calculate the peak crushing force and the specific energy absorption of CEAS which are presented by the quadratic response surface. Two numerical examples of CEAS are presented for verification of the validity of the proposed method.

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Section: Examplementioning

confidence: 99%

Hybrid reliability analysis for energy-absorbing composite structures based on evidence theory

Duan

Yang

Tao

et al. 2014

Journal of Reinforced Plastics and Composites

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“…Let x x ð Þ denote the membership function of the fuzzy variable x with the triangular and symmetric form. 23,25 It is schematically shown in Figure 1. The membership function is a mapping from the space of variable x to the interval ½0, 1.…”

Section: Problem Statementmentioning

confidence: 99%

“…FOSM and SORM) developed for single failure mode. By this way, the two and three orders of TFP can be computed based on equations (23) and (24).…”

Section: Lp-based Boundary Theorymentioning

confidence: 99%

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

Wei

Lü

Ren

2012

Proceedings of the Institution of Mechanical Engineers, Part C:

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In the design of engineering structure, uncertainties can be modeled as randomness or fuzziness depending on the amount of information available. In this article, the estimation of failure probability of structural system with multiple failure modes and mixed (random and fuzzy) inputs is considered. We firstly review the addition law of failure probability and a linear programming based bound method, and then these two techniques are combined to deal with structural system with multiple failure modes and only random inputs. Eventually, this method is extended for estimating the membership function of the failure probability of structural system with both random and fuzzy inputs. This method is computationally cheap, especially for the structural system with a large number of failure modes. Several numerical examples are introduced for demonstrating the efficiency and accuracy of the proposed method.

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“…As an intrinsic feature, practical systems involve uncertainties to a significant extent. Since the reliability and performance of systems are directly affected by uncertainties, a quantitative assessment of 10 uncertainty is widely recognized as an important task in practical engineering [1]. The obvious pathway to a realistic and powerful analysis of systems is a probabilistic approach.…”

Section: Introductionmentioning

confidence: 99%

Imprecise system reliability and component importance based on survival signature

Geng

Patelli

Beer

et al. 2016

Reliability Engineering & System Safety

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Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. AbstractThe concept of the survival signature has recently attracted increasing attention for performing reliability analysis on systems with multiple types of components.It opens a new pathway for a structured approach with high computational efficiency based on a complete probabilistic description of the system. In practical applications, however, some of the parameters of the system might not be defined completely due to limited data, which implies the need to take imprecisions of component specifications into account. This paper presents a methodology to include explicitly the imprecision, which leads to upper and lower bounds of the survival function of the system. In addition, the approach introduces novel and efficient component importance measures. By implementing relative importance index of each component without or with imprecision, the most critical component in the system can be identified depending on the service time of the system. Simulation method based on survival signature is introduced to deal with imprecision within components, which is precise and efficient. Numerical example is presented to show the applicability of the approach for systems.

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System reliability analysis for mixed uncertain variables

Cited by 43 publications

References 15 publications

Hybrid reliability analysis for energy-absorbing composite structures based on evidence theory

Hybrid reliability analysis for energy-absorbing composite structures based on evidence theory

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

Imprecise system reliability and component importance based on survival signature

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