A novel evidence-based fuzzy reliability analysis method for structures

Tao, Yourui; Cao, Liang; Huang, Zonghou

doi:10.1007/s00158-016-1570-7

Cited by 15 publications

(5 citation statements)

References 27 publications

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“…e current highway alignment reliability theory only considers the randomness of the influencing factors and does not consider the fuzzy nature of these influencing factors. Fuzzy reliability theory is a further development of reliability theory, which considers the fuzziness of influencing factors when applied to structural reliability calculation [21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Reliability Calculation Method of Highway Alignment

Chen

Zhao

2022

Mathematical Problems in Engineering

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Considering the randomness and fuzziness of highway route design parameters, based on the reliability theory and triangular fuzzy numbers, the fuzzy variables are transformed into random variables. Three new fuzzy reliability calculation methods of highway alignment are derived, namely, the equivalent density function method, the information entropy method, and the general density function method. The proposed calculation methods are applied to the reliability analysis of highway horizontal curve design. The results show that if the fuzzy variables are symmetric fuzzy numbers, the equivalent mean values obtained by the three methods are equal. If the fuzzy variables are asymmetric fuzzy numbers, the equivalent mean values and equivalent standard deviations of the three methods are different. Compared with the traditional reliability calculation method, the values obtained by the proposed method have a large reliability index, small failure probability, and high calculation accuracy. Compared with the other two methods, the general density function method has the fastest convergence and higher accuracy. The general density function method is then applied to the calculation of highway circular curve radius, under the condition of a superelevation failure rate of 5%, to generate the recommended values of the safety and reliability index.

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Section: Introductionmentioning

confidence: 99%

Fuzzy Reliability Calculation Method of Highway Alignment

Chen

Zhao

2022

Mathematical Problems in Engineering

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“…Garg [9] proposed a fuzzy reliability analysis method based on credibility theory to solve the problem that all failure rates are usually assumed to follow the identical type of fuzzy set, and the membership and non-membership functions can be constructed by different types of intuitionistic fuzzy numbers. Tao et al [21] developed an uncertainty model combining Zagadnienie optymalizacji niezawodnościowej konstrukcji w przypadkach, gdy mamy do czynienia ze zmiennymi rozmytymi i przedziałowymi odgrywa ważną rolę w praktyce inżynierskiej. Problemy optymalizacji niezawodności, w których wykorzystuje się tylko zmienne przedziałowe można z powodzeniem rozwiązywać stosując przedziałową symulację Monte Carlo, metodę ekstremum czy aproksymację metodą punktu siodłowego.…”

Section: Introductionunclassified

Reliability-based design optimization under fuzzy and interval variables based on entropy theory

Gao¹,

Zhang²

2019

Eksploatacja i Niezawodność – Maintenance and Reliability

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Reliability-based design optimization undeR fuzzy and inteRval vaRiables based on entRopy theoRy opaRta na teoRii entRopii niezawodnościowa optymalizacja kon-stRukcji dla zmiennych Rozmytych i pRzedziałowych Reliability-based design optimization under fuzzy and interval variables is important in engineering practice. The interval MonteCarlo simulation (IMCS), extremum method, and saddlepoint approximation (SPA) can be used for reliability optimization issues contain only interval variables. Thus, how to deal with the fuzzy variables is critical for system reliability analysis and optimization design. The α-level cut method can be applied to deal with fuzzy variables but it is complex and computationally expensive. Therefore, an equivalent conversion method based on entropy theory is proposed in this paper, which can convert the fuzzy variables to the normal random variables to avoid the complex integral process. According to the equivalent conversion method, the entropybased sequential optimization and reliability assessment (E-SORA) is developed in combination with the worst case analysis (WCA) for reliability-based design optimization under fuzzy and interval variables. A numerical example about the reliability design of the crank-link mechanism under fuzzy and interval variables is solved by the E-SORA, double-loops method, and α-level cut algorithm, respectively, is used to demonstrate the accuracy and efficiency, and the results show that the proposed method is feasible for reliability-based design optimization under fuzzy and interval variables.

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“…Therefore, reasonable reliability optimization design methodologies must have the ability to deal with such uncertainties [11,12]. Bayesian theory and fuzzy mathematics were the initiate instruments to handle the uncertainties in conventional reliability optimization design [13,14]. Ren et al [15] put forward the multi-attribute group decision-making (MAGDM) with the integration of techniques for order preference by similarity to ideal solution (TOPSIS) and interval-valued intuitionistic fuzzy sets, which can consider the reliability of information.…”

Section: Introductionmentioning

confidence: 99%

Reliability-Based and Cost-Oriented Product Optimization Integrating Fuzzy Reasoning Petri Nets, Interval Expert Evaluation and Cultural-Based DMOPSO Using Crowding Distance Sorting

Zhang

Feng

et al. 2017

Applied Sciences

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Featured Application: By integrating fuzzy reasoning Petri Nets, interval expert evaluation and cultural-based dynamic multi-objective particle swarm optimization (DMOPSO) using crowding distance sorting, the proposed reliability-based and cost-oriented product optimization method is effective to conduct the early product design. A reasonable reliability optimization design scheme can be output, and it is of important guiding significance for the product detailed design. The superiority of the proposed method lies in its outstanding ability to deal with the uncertainties information and dynamic product failure propagation. Abstract:In reliability-based and cost-oriented product optimization, the target product reliability is apportioned to subsystems or components to achieve the maximum reliability and minimum cost. Main challenges to conducting such optimization design lie in how to simultaneously consider subsystem division, uncertain evaluation provided by experts for essential factors, and dynamic propagation of product failure. To overcome these problems, a reliability-based and cost-oriented product optimization method integrating fuzzy reasoning Petri net (FRPN), interval expert evaluation and cultural-based dynamic multi-objective particle swarm optimization (DMOPSO) using crowding distance sorting is proposed in this paper. Subsystem division is performed based on failure decoupling, and then subsystem weights are calculated with FRPN reflecting dynamic and uncertain failure propagation, as well as interval expert evaluation considering six essential factors. A mathematical model of reliability-based and cost-oriented product optimization is established, and the cultural-based DMOPSO with crowding distance sorting is utilized to obtain the optimized design scheme. The efficiency and effectiveness of the proposed method are demonstrated by the numerical example of the optimization design for a computer numerically controlled (CNC) machine tool.

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A novel evidence-based fuzzy reliability analysis method for structures

Cited by 15 publications

References 27 publications

Fuzzy Reliability Calculation Method of Highway Alignment

Fuzzy Reliability Calculation Method of Highway Alignment

Reliability-based design optimization under fuzzy and interval variables based on entropy theory

Reliability-Based and Cost-Oriented Product Optimization Integrating Fuzzy Reasoning Petri Nets, Interval Expert Evaluation and Cultural-Based DMOPSO Using Crowding Distance Sorting

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