Multisphere-based importance sampling for structural reliability

Thedy, John; Liao, Kuo‐Wei

doi:10.1016/j.strusafe.2021.102099

Cited by 14 publications

(2 citation statements)

References 31 publications

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“…Although MCS is the most convenient implementation approach, it is extremely time-consuming when dealing with small failure probability and complex numerical models (e.g., fidelity finite element models (FEM)). Meanwhile, tremendous variation techniques of the MCS such as subset simulation [3,4], importance sampling [5,6] and directional sampling [7,8] have been developed to obtain more accurate results with fewer samplings. However, the main drawback of insufficient still exists in those methods.…”

Section: Akmentioning

confidence: 99%

AWK-TIS: An Improved AK-IS Based on Whale Optimization Algorithm and燭runcated Importance Sampling for Reliability Analysis

Qin¹,

Cao²,

Zhang³

2023

Computer Modeling in Engineering &Amp; Sciences

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In this work, an improved active kriging method based on the AK-IS and truncated importance sampling (TIS) method is proposed to efficiently evaluate structural reliability. The novel method called AWK-TIS is inspired by AK-IS and RBF-GA previously published in the literature. The innovation of the AWK-TIS is that TIS is adopted to lessen the sample pool size significantly, and the whale optimization algorithm (WOA) is employed to acquire the optimal Kriging model and the most probable point (MPP). To verify the performance of the AWK-TIS method for structural reliability, four numerical cases which are utilized as benchmarks in literature and one real engineering problem about a jet van manipulate mechanism are tested. The results indicate the accuracy and efficiency of the proposed method.

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Section: Akmentioning

confidence: 99%

AWK-TIS: An Improved AK-IS Based on Whale Optimization Algorithm and燭runcated Importance Sampling for Reliability Analysis

Qin¹,

Cao²,

Zhang³

2023

Computer Modeling in Engineering &Amp; Sciences

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“…By selecting an appropriate radius, the AHKRA algorithm can concentrate on the area with enough impact on the failure probability, thus avoiding unnecessary function evaluation. x 1…10 = N(0, 1) Multivariate quadratic LS (Thedy and Liao, 2021) 3…”

Section: Mathematical Casesmentioning

confidence: 99%

Adaptive hyperball Kriging method for efficient reliability analysis

Yang

Prayogo

2022

AIEDAM

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Although an accurate reliability assessment is essential to build a resilient infrastructure, it usually requires time-consuming computation. To reduce the computational burden, machine learning-based surrogate models have been used extensively to predict the probability of failure for structural designs. Nevertheless, the surrogate model still needs to compute and assess a certain number of training samples to achieve sufficient prediction accuracy. This paper proposes a new surrogate method for reliability analysis called Adaptive Hyperball Kriging Reliability Analysis (AHKRA). The AHKRA method revolves around using a hyperball-based sampling region. The radius of the hyperball represents the precision of reliability analysis. It is iteratively adjusted based on the number of samples required to evaluate the probability of failure with a target coefficient of variation. AHKRA adopts samples in a hyperball instead of an n-sigma rule-based sampling region to avoid the curse of dimensionality. The application of AHKRA in ten mathematical and two practical cases verifies its accuracy, efficiency, and robustness as it outperforms previous Kriging-based methods.

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Reliability-based structural optimization using adaptive neural network multisphere importance sampling

Thedy

Liao

2023

Struct Multidisc Optim

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Multisphere-based importance sampling for structural reliability

Cited by 14 publications

References 31 publications

AWK-TIS: An Improved AK-IS Based on Whale Optimization Algorithm and燭runcated Importance Sampling for Reliability Analysis

AWK-TIS: An Improved AK-IS Based on Whale Optimization Algorithm and燭runcated Importance Sampling for Reliability Analysis

Adaptive hyperball Kriging method for efficient reliability analysis

Reliability-based structural optimization using adaptive neural network multisphere importance sampling

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