# Reliability Estimation Using Two-Staged Kriging Metamodel and Genetic Algorithm

• 조태민 (한국과학기술원 기계공학과) ;
• 주병현 (한국과학기술원 기계공학과) ;
• 정도현 (한국자동차부품연구원) ;
• 이병채 (한국과학기술원 기계공학과)
• 발행 : 2006.09.01
• 115 11

#### 초록

In this study, the effective method for reliability estimation is proposed using tow-staged kriging metamodel and genetic algorithm. Kriging metamodel can be determined by appropriate sampling range and the number of sampling points. The first kriging metamodel is made based on the proposed sampling points. The advanced f'=rst order reliability method is applied to the first kriging metamodel to determine the reliability and most probable failure point(MPFP) approximately. Then, the second kriging metamodel is constructed using additional sampling points near the MPFP. These points are selected using genetic algorithm that have the maximum mean squared error. The Monte-Carlo simulation is applied to the second kriging metamodel to estimate the reliability. The proposed method is applied to numerical examples and the results are almost equal to the reference reliability.

#### 키워드

신뢰도;크리깅 메타모델;개선된 1차 신뢰도법;최대 가능 손상점;유전자 알고리즘

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#### 피인용 문헌

1. Prediction of Consumed Electric Power on a MQL Milling Process using a Kriging Meta-Model vol.32, pp.4, 2015, https://doi.org/10.7736/KSPE.2015.32.4.353
2. An adaptive importance sampling method with a Kriging metamodel to calculate failure probability vol.31, pp.12, 2017, https://doi.org/10.1007/s12206-017-1119-8