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An Efficient Constraint Boundary Sampling Method for Sequential RBDO Using Kriging Surrogate Model

크리깅 대체모델을 이용한 순차적 신뢰성기반 최적설계를 위한 효율적인 제한조건경계 샘플링 기법

Kim, Jihoon;Jang, Junyong;Kim, Shinyu;Lee, Tae Hee;Cho, Su-gil;Kim, Hyung Woo;Hong, Sup
김지훈;장준용;김신유;이태희;조수길;김형우;홍섭

  • Received : 2016.01.31
  • Accepted : 2016.04.12
  • Published : 2016.06.01

Abstract

Reliability-based design optimization (RBDO) requires a high computational cost owing to its reliability analysis. A surrogate model is introduced to reduce the computational cost in RBDO. The accuracy of the reliability depends on the accuracy of the surrogate model of constraint boundaries in the surrogated-model-based RBDO. In earlier researches, constraint boundary sampling (CBS) was proposed to approximate accurately the boundaries of constraints by locating sample points on the boundaries of constraints. However, because CBS uses sample points on all constraint boundaries, it creates superfluous sample points. In this paper, efficient constraint boundary sampling (ECBS) is proposed to enhance the efficiency of CBS. ECBS uses the statistical information of a kriging surrogate model to locate sample points on or near the RBDO solution. The efficiency of ECBS is verified by mathematical examples.

Keywords

Constraint Boundary Sampling;FORM;Kriging Surrogate Model;RBDO

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Acknowledgement

Supported by : 한국에너지기술평가원