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Reliability-Based Design Optimization Using Akaike Information Criterion for Discrete Information

이산정보의 아카이케 정보척도를 이용한 신뢰성 기반 최적설계

  • Lim, Woo-Chul (Dept. of Automotive Engineering, College of Engineering, Hanyang Univ.) ;
  • Lee, Tae-Hee (Dept. of Automotive Engineering, College of Engineering, Hanyang Univ.)
  • 임우철 (한양대학교 공과대학 자동차공학과) ;
  • 이태희 (한양대학교 공과대학 자동차공학과)
  • Received : 2012.02.27
  • Accepted : 2012.06.09
  • Published : 2012.08.01

Abstract

Reliability-based design optimization (RBDO) can be used to determine the reliability of a system by means of probabilistic design criteria, i.e., the possibility of failure considering stochastic features of design variables and input parameters. To assure these criteria, various reliability analysis methods have been developed. Most of these methods assume that distribution functions are continuous. However, in real problems, because real data is often discrete in form, it is important to estimate the distributions for discrete information during reliability analysis. In this study, we employ the Akaike information criterion (AIC) method for reliability analysis to determine the best estimated distribution for discrete information and we suggest an RBDO method using AIC. Mathematical and engineering examples are illustrated to verify the proposed method.

Keywords

Akaike Information Criterion(AIC);Maximum Likelihood Estimation(MLE);Reliability Analysis;Reliability-based Design Optimization;Monte Carlo Simulation;Bogie Frame

Acknowledgement

Grant : 공간-시간 통계적 모형 기반 최적 설계 기법 연구

Supported by : 한국연구재단

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