An efficient Kriging model-based importance sampling method for estimating the failure probability-based parameter global sensitivity index with uncertain distribution parameters

Yun, Wanying; Wang, Yan

doi:10.1016/j.ast.2022.107861

Cited by 8 publications

(6 citation statements)

References 39 publications

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“…The pivotal issue of IS-based failure estimation is to build an accurate h x (x), which is mainly determined using MPP solved using FORM and its improvements. 44,65,66 Unfortunately, FORM involves gradient computation, which limits the surrogate model to the explicit model; and the poor accuracy of FORM in the high-nonlinearity problems 47,67,68 further limits its usability. In this case, the OIS method is proposed: firstly, the MMP solution is modeled as an optimization problem, as shown in Equation (19), given that MPP is the point closest to the sampling center on the LSF 69,70 ; then, the proposed MRSMA algorithm is used to solve Equation ( 19) considering its preeminent search performance; finally, the computed MPP-based h x (x) is used to perform efficient OIS sampling.…”

Section: Optimized Importance Samplingmentioning

confidence: 99%

“…To exhibit the broad engineering availability of the proposed method, the AOK-ES also is employed to analyze the turbine disk, 43,65 as shown in Figure 14. The load worked on the turbine disk can be described as follows:…”

Section: Case V: An Aero-engine Turbine Diskmentioning

confidence: 99%

“…The pivotal issue of IS‐based failure estimation is to build an accurate h x ( x ), which is mainly determined using MPP solved using FORM and its improvements 44,65,66 . Unfortunately, FORM involves gradient computation, which limits the surrogate model to the explicit model; and the poor accuracy of FORM in the high‐nonlinearity problems 47,67,68 further limits its usability.…”

Section: Adaptive Optimized Kriging Combining Efficient Sampling Aok‐esmentioning

confidence: 99%

“…To exhibit the broad engineering availability of the proposed method, the AOK‐ES also is employed to analyze the turbine disk, 43,65 as shown in Figure 14. The load worked on the turbine disk can be described as follows:

\begin{equation}F = \frac{{C{\omega }^2}}{{2\pi }} + 2\rho {\omega }^2J\end{equation}

where, C , ω , ρ , and J are coefficient, rotational speed, mass density and cross section moment of inertia, respectively; and ω = 2 nπ ( n is the rotational frequency).…”

Section: Case Studiesmentioning

confidence: 99%

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AOK‐ES: Adaptive optimized Kriging combining efficient sampling for structural reliability analysis

Huang,

Zhang,

Wang

et al. 2024

Quality & Reliability Eng

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The pivotal problem in reliability analysis is how to use as few actual assessments as possible to obtain an accurate failure probability. Although adaptive Kriging provides a viable method to address this problem, unsatisfied Kriging surrogate accuracy and reliability modeling samples often lead to an unacceptable computing burden. In this paper, an adaptive optimized Kriging combining efficient sampling (AOK‐ES) is proposed: first, to enhance the Kriging approximation ability, a high‐fidelity optimized Kriging model (OKM) is established; further, to ensure the samples quality of OKM modeling and reliability calculation, an improved Latin hypercube sampling method and an optimized importance sampling approach are developed correspondingly. Six different types of case studies demonstrate the superiority of the proposed AOK‐ES. The analysis results demonstrate that the proposed AOK‐ES holds the potential to reduce computing cost while ensuring accuracy.

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Section: Optimized Importance Samplingmentioning

confidence: 99%

Section: Case V: An Aero-engine Turbine Diskmentioning

confidence: 99%

Section: Adaptive Optimized Kriging Combining Efficient Sampling Aok‐esmentioning

confidence: 99%

\begin{equation}F = \frac{{C{\omega }^2}}{{2\pi }} + 2\rho {\omega }^2J\end{equation}

where, C , ω , ρ , and J are coefficient, rotational speed, mass density and cross section moment of inertia, respectively; and ω = 2 nπ ( n is the rotational frequency).…”

Section: Case Studiesmentioning

confidence: 99%

See 2 more Smart Citations

AOK‐ES: Adaptive optimized Kriging combining efficient sampling for structural reliability analysis

Huang,

Zhang,

Wang

et al. 2024

Quality & Reliability Eng

View full text Add to dashboard Cite

show abstract

“…35 Therefore, GSA facilitates a comprehensive assessment of the impact of different input values on the output response. 36 In the literature, GSA methods include failure probability-based GSA, 37,38 moment-independent GSA, 39,40 and variance-based GSA. 32,41,42 Fang et al proposed a reliability analysis approach for mechanisms with mixed uncertainties using polynomial chaos expansion.…”

Section: Introductionmentioning

confidence: 99%

Fatigue reliability and sensitivity analysis of aero‐disk considering correlation

Di,

Li,

Nan

et al. 2024

Quality & Reliability Eng

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Aero‐disk is a key component of aero‐engine. Due to its complex working conditions, aero‐disk is prone to structural failures. Therefore, it is essential to analyze the reliability and importance input variables of aero‐disk. In this paper, a framework of aero‐disk reliability analysis and global sensitivity analysis (GSA) was established. First, the hazardous regions of aero‐disk were determined by finite element analysis, and the limit state function of aero‐disk was defined by the life interference model. Then D‐Vine model was utilized to establish the correlation model for aero‐disk hazardous regions to evaluate the reliability of aero‐disk. In addition, two GSA methods based on Copula and space partition were proposed to identify important input random variables considering underlying correlation, and the accuracy of the proposed method was verified by two examples. Finally, the proposed method was applied to the GSA of aero‐disk. The results show that the established framework fills in the gap of uncertainty analysis of aero‐disk, which can be extended to other engineering fields. The proposed GSA methods have both high efficiency and accuracy and can realize multi‐dimensional GSA when the correlation of input variables is considered.

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A novel training point selection strategy guided by the maximum reduction of structural state misclassification probability for time-dependent reliability analysis

Lü

Feng

2023

Aerospace Science and Technology

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An efficient Kriging model-based importance sampling method for estimating the failure probability-based parameter global sensitivity index with uncertain distribution parameters

Cited by 8 publications

References 39 publications

AOK‐ES: Adaptive optimized Kriging combining efficient sampling for structural reliability analysis

AOK‐ES: Adaptive optimized Kriging combining efficient sampling for structural reliability analysis

Fatigue reliability and sensitivity analysis of aero‐disk considering correlation

A novel training point selection strategy guided by the maximum reduction of structural state misclassification probability for time-dependent reliability analysis

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