Most Probable Failure Point Update Method for Accurate First-Order Reliability-Based Electromagnetic Designs

Byungsu, Kang; Mun, Jaegyeong; LimJongSu,; Kim, Dong Hun

doi:10.4283/jmag.2019.24.3.408

Cited by 2 publications

(1 citation statement)

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“…In the research of engineering structural reliability, common methods include rst-order reliability method, Monte Carlo method, and response surface method. e rst-order reliability method has many applications in engineering practice because it is easy to understand and put in use [1][2][3]. For the rst-order reliability method, the problem of robustness and e ciency has always been the core problem of the method.…”

Section: Introductionmentioning

confidence: 99%

Improved Hybrid Response Surface Method Based on Double Weighted Regression and Vector Projection

Xia

Wang

2022

Mathematical Problems in Engineering

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In order to increase the accuracy and stability of the classical response surface method and relevant method, a new improved response surface method based on the idea of double weighting factors and vector projection method is proposed. The response surface is fitted by the weighted regression technique, which allows the sampling points to be weighted by their distance from the true failure surface and that from the estimated design point. It uses the vector of the gradient projection method to get new sampling points in the process of iteration, in order to make the sampling points closer to the design point, and the value of deviation coefficient is constantly adjusted. To some extent, these strategies increase the accuracy and stability of the response surface method, while the calculation time is decreased. At last, the rationality and efficiency of the proposed method are demonstrated through five examples. Besides, as revealed from this investigation, compared with other conventional algorithms, this method has a few obvious advantages; this algorithm not only has high precision and efficiency, but also has solid stability.

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Section: Introductionmentioning

confidence: 99%

Improved Hybrid Response Surface Method Based on Double Weighted Regression and Vector Projection

Xia

Wang

2022

Mathematical Problems in Engineering

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An Efficient High-Order-Moment-Based Reliability Method Combining the Maximum Likelihood Point and Cubic Normal Transformation

Cao

Lü

2022

Machines

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Moment-based methods can measure the safety degrees of mechanical systems affected by unavoidable uncertainties, utilizing only the statistical moments of random variables for reliability analysis. For the conventional derivation of the first four statistical moments based on the second-order Taylor expansion series evaluated at the most likelihood point (MLP), skewness and kurtosis involve the higher fourth raw moments of random variables and thus are unfavorable for engineering applications. This paper develops new computing formulae for the first four statistical moments which require only the first four central moments of random variables, and the probability distribution of the performance function is approximated using cubic normal transformation. Several numerical examples are given to demonstrate the accuracy of the proposed methods. Comparisons of the two proposed approaches and the maximum entropy method (ME) are also made regarding reliability assessment.

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Most Probable Failure Point Update Method for Accurate First-Order Reliability-Based Electromagnetic Designs

Cited by 2 publications

References 0 publications

Improved Hybrid Response Surface Method Based on Double Weighted Regression and Vector Projection

Improved Hybrid Response Surface Method Based on Double Weighted Regression and Vector Projection

An Efficient High-Order-Moment-Based Reliability Method Combining the Maximum Likelihood Point and Cubic Normal Transformation

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