Reliability Analysis on Structures Based on a Modified Iterative Response Surface Method

Wei, Yanxu; Bai, Guang-Chen; Wang, Bowei; Bai, Baojun

doi:10.1155/2018/8794160

Cited by 6 publications

(3 citation statements)

References 35 publications

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“…Probabilistic analysis is necessary for accurate failure prevention and reliability assessment of turbines [38]. Currently, probabilistic analysis methods based on surrogate models, such as response surface methods (RSM) [27,41], artificial neural networks (ANN) [1,46], Kriging [11], and radial basis functions (RBF), are extensively promoted and applied in engineering. Fan proposed a surrogate model based on local maximum entropy (LME) theory in reliability analysis and sensitivity analysis of turbine disks with random geometric parameters [8].…”

Section: Introductionmentioning

confidence: 99%

Reliability analysis of multi-site damage with failure dependency of the turbine based on flow-thermal-solid coupling analysis and the Monte Carlo validated simulations

Qian¹,

Zeng²,

Huang³

et al. 2023

Eksploatacja i Niezawodność – Maintenance and Reliability

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The harsh environmental loads may lead to strength failure in the turbine in an aero-engine. To accurately assess the strength reliability of the turbine under multiple loads, the stress distributions of 41 danger sites of a turbine under thermal, centrifugal, and pneumatic loads were determined by the flow-thermal-solid coupling analysis using ANSYS. Second, based on the flow-thermal-solid coupling analysis and response surface method, the probabilistic analysis model of stress at the danger site was established. And the probabilistic distribution of stress was determined by sampling and hypothesis testing. Finally, the reliability model of the turbine with multi-site damage and failure dependency was established, by which a reliability of 0.99802 was calculated. And the actual reliability of the turbine was 0.99626 determined by the Monte Carlo simulations, which verified the model in precision. The results indicated that the reliability model has a high efficiency and higher precision than the traditional reliability model with failure independence.

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Section: Introductionmentioning

confidence: 99%

Reliability analysis of multi-site damage with failure dependency of the turbine based on flow-thermal-solid coupling analysis and the Monte Carlo validated simulations

Qian¹,

Zeng²,

Huang³

et al. 2023

Eksploatacja i Niezawodność – Maintenance and Reliability

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show abstract

“…Goswami et al [15] proposed an improved RSM based on the moving least squares method to reduce the number of iterations. Wei et al [16] proposed a modifed iterative response surface method (called NDIRSM) to improve the accuracy and efciency of structural reliability analysis. Based on the idea of double weight factor and vector projection method, Xia and Wang [17] proposed a new improved response surface method.…”

Section: Introductionmentioning

confidence: 99%

Improved Response Surface Method Based on Linear Gradient Iterative Criterion

Xia

Kong

et al. 2023

Advances in Civil Engineering

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Aiming at the problem of big calculation error in solving reliability index by the traditional response surface method, an improved response surface method based on the linear gradient iteration criterion is proposed. First, the linear gradient iteration criterion is proposed to reduce the iteration step size with the increase of iteration times. It will improve the fitting accuracy of response surface and lead to a better convergence while approaching the limit state surface. Then, the reduction coefficient of the linear gradient iterative criterion is studied. The optimal value of coefficient is 0.2. The improved response surface method will get a more accurate reliability index quickly. Examples show that the proposed method has obvious advantages of high accuracy and efficiency. The application of this method can also be expanded in other similar engineering structure.

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“…e response surface method can e ectively overcome the disadvantages of the above two methods. Because the response surface method is simple in principle, e cient in calculation, and easy to operate, scholars in the eld of reliability have paid extensive attention to the response surface method [11][12][13]. At present, many scholars have improved the response surface method in the two aspects of weighted regression and vector projection.…”

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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Reliability Analysis on Structures Based on a Modified Iterative Response Surface Method

Cited by 6 publications

References 35 publications

Reliability analysis of multi-site damage with failure dependency of the turbine based on flow-thermal-solid coupling analysis and the Monte Carlo validated simulations

Reliability analysis of multi-site damage with failure dependency of the turbine based on flow-thermal-solid coupling analysis and the Monte Carlo validated simulations

Improved Response Surface Method Based on Linear Gradient Iterative Criterion

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

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