Wyniki wyszukiwania - BazTech

Ograniczanie wyników

1 2023

Znaleziono wyników: 1

Liczba wyników na stronie

Wyniki wyszukiwania

Sortuj według:

Ogranicz wyniki do:

Reliability analysis method of coupling optimal importance sampling density and multi-fidelity Kriging model

Xie Jiayu, Tian Zongrui, Zhi Pengpeng, Zhao Yadong

Eksploatacja i Niezawodność

2023

Vol. 25, no. 2

art. no. 161893

The commonly used reliability analysis approaches for Kriging-based models are usually conducted based on high-fidelity Kriging models. However, high-fidelity surrogate models are commonly costly. Therefore, in order to balance the calculation expense and calculation time of the surrogate model, this paper proposes a multi-fidelity Kriging model reliability analysis approach with coupled optimal important sampling density (OISD+MFK). First, the MEI learning function is proposed considering the training sample distance, model computation cost, expected improvement function, and model relevance. Second, a dynamic stopping condition is proposed that takes into account the failure probability estimation error. Finally, the optimal importance sampling density is incorporated into the reliability analysis process, which can effectively reduce failure probability estimation error. The results of the study show that the approach proposed in this paper can reduce the calculation cost while outputting relatively accurate failure probability evaluation results.