Sequential optimization and fuzzy reliability analysis for multidisciplinary systems

Wang, Lei; Xiong, Congcong; Liu, Guanhua; Shi, Qinghe

doi:10.1007/s00158-019-02258-y

Cited by 36 publications

(9 citation statements)

References 49 publications

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“…The use of the SA method for progressive analysis is efficient and practical. The SA has the following characteristics: (1) convenient calculation and strong operability; (2) good overall approximation effect to the function, especially the tail probability distribution; (3) SA method is useful when the PDF is known but the calculation of the CDF is difficult [41,42].…”

Section: The Saddlepoint Approximationmentioning

confidence: 99%

An Uncertainty Analysis and Reliability-Based Multidisciplinary Design Optimization Method Using Fourth-Moment Saddlepoint Approximation

Guo¹,

Lv²

2023

Computer Modeling in Engineering &Amp; Sciences

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In uncertainty analysis and reliability-based multidisciplinary design and optimization (RBMDO) of engineering structures, the saddlepoint approximation (SA) method can be utilized to enhance the accuracy and efficiency of reliability evaluation. However, the random variables involved in SA should be easy to handle. Additionally, the corresponding saddlepoint equation should not be complicated. Both of them limit the application of SA for engineering problems. The moment method can construct an approximate cumulative distribution function of the performance function based on the first few statistical moments. However, the traditional moment matching method is not very accurate generally. In order to take advantage of the SA method and the moment matching method to enhance the efficiency of design and optimization, a fourth-moment saddlepoint approximation (FMSA) method is introduced into RBMDO. In FMSA, the approximate cumulative generating functions are constructed based on the first four moments of the limit state function. The probability density function and cumulative distribution function are estimated based on this approximate cumulative generating function. Furthermore, the FMSA method is introduced and combined into RBMDO within the framework of sequence optimization and reliability assessment, which is based on the performance measure approach strategy. Two engineering examples are introduced to verify the effectiveness of proposed method.

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Section: The Saddlepoint Approximationmentioning

confidence: 99%

An Uncertainty Analysis and Reliability-Based Multidisciplinary Design Optimization Method Using Fourth-Moment Saddlepoint Approximation

Guo¹,

Lv²

2023

Computer Modeling in Engineering &Amp; Sciences

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“…Chaube and Singh [12] developed a technique for the evaluation of fuzzy reliability based on the membership function. Wang et al [13] presented an approach based on sequential optimization and fuzzy reliability for multidisciplinary systems. Furthermore, the authors also proposed a novel collocation method for the appraisal of the fuzzy reliability of systems.…”

Section: Reliability Evaluation Using Fuzzy Set Theorymentioning

confidence: 99%

Statistical Fuzzy Reliability Assessment of a Blended System

Chachra

Kumar

Ram

et al. 2023

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Fuzzy sets have been proven to constitute an asset in the evolution of reliability theory in recent decades. Their contribution in addressing the possibility of errors, insufficiency of data, randomness, or fuzziness, either in the system or in the accumulation of any data for the respective system, which is overlooked in the traditional reliability assessment, seems to be quite crucial. The present work deals with the statistical fuzzy reliability evaluation of a blended system that comprises two subsystems. One system contains two components aligned in a parallel configuration, and the other is a 3-out-of-5 system. The reliability of this model is assessed using two approaches to intuitionistic fuzzy sets (IFS), namely, traditional IFS and interval-valued intuitionistic fuzzy sets (IVIFS). Three cases are considered in each approach, which are compared individually as well as with each other. It was established that the IVIFS yield better results than the IFS. The obtained results are displayed in both tabular and graphical forms for better assessment.

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“…Wang et al 32 used the interval set‐theoretic model to describe the uncertain‐but‐bounded uncertainties in TO problems, and the iterative dimension‐by‐dimension method was further constructed to accelerate the convergence rate considerably 33 . The fuzzy method adopted the membership level to describe the uncertain parameters to achieve design results under different safety targets 34,35 . In the study by Yin et al, 36 the fuzzy theory was extended to topology to account for the epistemic uncertainties successfully.…”

Section: Introductionmentioning

confidence: 99%

Robust topology optimization methodology for continuum structures under probabilistic and fuzzy uncertainties

Meng

Wang

et al. 2021

Numerical Meth Engineering

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Owing to the variations in geometric dimensions, material properties and external loads in engineering applications, robust topology optimization (RTO) has garnered increasing attention in recent years to account for the uncertain behaviors during the preliminary concept design phases. This paper presents a hybrid RTO method to simultaneously resolve the epistemic and aleatory uncertainties. First, based on the probabilistic and fuzzy methodologies, the hybrid RTO model is formulated with nested double optimization loops using Monte Carlo simulations. Second, an efficient iterative method is proposed based on the perturbation method to accelerate the rate of convergence of the proposed hybrid RTO model. The derivatives of the hybrid robust compliance objective function with respect to the deterministic design variables, random parameters, and fuzzy parameters are then derived using the adjoint variable method. Finally, a T-shaped beam design, an L-shaped beam design, and a three-dimensional cantilever beam design are tested to validate the proposed hybrid RTO method.

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Sequential optimization and fuzzy reliability analysis for multidisciplinary systems

Cited by 36 publications

References 49 publications

An Uncertainty Analysis and Reliability-Based Multidisciplinary Design Optimization Method Using Fourth-Moment Saddlepoint Approximation

An Uncertainty Analysis and Reliability-Based Multidisciplinary Design Optimization Method Using Fourth-Moment Saddlepoint Approximation

Statistical Fuzzy Reliability Assessment of a Blended System

Robust topology optimization methodology for continuum structures under probabilistic and fuzzy uncertainties

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