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Reliability-Based Design Optimization Using Enhanced Pearson System

개선된 피어슨 시스템을 이용한 신뢰성기반 최적설계

  • Kim, Tae-Kyun (Dept. of Automotive Engineering, Graduate School, Hanyang Univ.) ;
  • Lee, Tae-Hee (Dept. of Automotive Engineering, College of Engineering, Hanyang Univ.)
  • 김태균 (한양대학교 대학원 자동차공학과) ;
  • 이태희 (한양대학교 미래자동차공학과)
  • Received : 2010.01.05
  • Accepted : 2010.12.17
  • Published : 2011.02.01

Abstract

Since conventional optimization that is classified as a deterministic method does not consider the uncertainty involved in a modeling or manufacturing process, an optimum design is often determined to be on the boundaries of the feasible region of constraints. Reliability-based design optimization is a method for obtaining a solution by minimizing the objective function while satisfying the reliability constraints. This method includes an optimization process and a reliability analysis that facilitates the quantization of the uncertainties related to design variables. Moment-based reliability analysis is a method for calculating the reliability of a system on the basis of statistical moments. In general, on the basis of these statistical moments, the Pearson system estimates seven types of distributions and determines the reliability of the system. However, it is technically difficult to practically consider the Pearson Type IV distribution. In this study, we propose an enhanced Pearson Type IV distribution based on a kriging model and validate the accuracy of the enhanced Pearson Type IV distribution by comparing it with a Monte Carlo simulation. Finally, reliability-based design optimization is performed for a system with type IV distribution by using the proposed method.

Keywords

RBDO;Reliability Analysis;Kriging Model;Pearson System;Pearson Type IV Distribution

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