Earticle

초록

영어

This paper describes the use of approximation in Collaborative Optimization (CO) method, one of the Multidisciplinary Design Optimization (MDO) techniques. The approximation is used to model the result of a disciplinary design, optimal discrepancy function value, as a function of the interdisciplinary target variables passed from system level to the discipline. The optimal discrepancy function value is used to examine the interdisciplinary compatibility constraint (discrepancy function =0) duringthe system level optimization. However, the peculiar shape of the compatibility constraint makes it difficult to exploit well–developed conventional approximation methods. This paper introduces the combination of neural network classification and kriging to resolve this problem. In addition, for the purpose of enhancing the accuracy of the approximation, the approximation is continuously updated using the information obtained from the system level optimization. This iterative process is continued until acceptable convergence is achieved.

목차

Abstract
1. Introduction
2. Using Approximation in CO
3. Modeling Optimal Disciplinary Design
3.1 Introduction of Classification Neural Net-work
3.2 Using Implicit Extra Point Information
4. Managing Approximation Models in Optimization
5. Illustrative Example
5.1 Mathematical Example
5.2 Hub frame example
6. Conclusions
Acknowledgements
References

키워드

저자

• Chang-Kyu Park [ 박창규 | Member, School of Mechanical & Automotive Engineering, Gwangju University ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국기계항공기술학회지(구 한국기계기술학회지) [Journal of the Korean Society of Mechanical and Aviation Technology ]

• 간기

  격월간

• pISSN

  1229-604X

• eISSN

  2508-3805

• 수록기간

  1999~2026

• 등재여부

  KCI 등재

• 십진분류

  KDC 550 DDC 620