Application of Collaborative Optimization Using Genetic Algorithm and Response Surface Method to an Aircraft Wing Design

  • Jun Sangook (School of Mechanical and Aerospace Engineering in Seoul National University) ;
  • Jeon Yong-Hee (School of Mechanical and Aerospace Engineering in Seoul National University) ;
  • Rho Joohyun (School of Mechanical and Aerospace Engineering in Seoul National University) ;
  • Lee Dong-ho (School of Mechanical and Aerospace Engineering in Seoul National University)
  • 발행 : 2006.01.01

초록

Collaborative optimization (CO) is a multi-level decomposed methodology for a large-scale multidisciplinary design optimization (MDO). CO is known to have computational and organizational advantages. Its decomposed architecture removes a necessity of direct communication among disciplines, guaranteeing their autonomy. However, CO has several problems at convergence characteristics and computation time. In this study, such features are discussed and some suggestions are made to improve the performance of CO. Only for the system level optimization, genetic algorithm is used and gradient-based method is used for subspace optimizers. Moreover, response surface models are replaced as analyses in subspaces. In this manner, CO is applied to aero-structural design problems of the aircraft wing and its results are compared with the multidisciplinary feasible (MDF) method and the original CO. Through these results, it is verified that the suggested approach improves convergence characteristics and offers a proper solution.

키워드

참고문헌

  1. Alexandrov, N. M. and Lewis, R. M., 2000, 'Analytical and Computational Aspects of Collaborative Optimization,' NASA TM 2000-210104
  2. Braun, R. D., 1996, 'Collaborative Optimization : an Architecture for Large-Scale Distributed Design,' Ph. D. Thesis, Stanford University, Stanford, California
  3. Braun, R. D., Moore, A. A. and Kroo, I., 1996, 'Use of the Collaborative Optimization Architecture for Launch Vehicle Design,' 6th AIAA/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, AIAA-96-4018
  4. Braun, R. D., Gage, P., Kroo, I. and Sobieski I., 1996, 'Implementation and Performance Issues in Collaborative Optimization,' 6th AIAA/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, AIAA-96-4017
  5. Cook, R. D., Malkus, D. S. and Plesha, M. E., 1989, Concepts and Applications of Finite Element Analysis, 3rd edition, John Wiley & Sons, New York
  6. Ghim, Y., Lee, D. and Lee, D., 2002, 'Collaborative Optimization for and Aircraft Wing Desgin,' Proc. of the KSAS Fall Annual Meeting 2002 (II), pp. 920-923, in Korea
  7. Ghim, Y., 2003, 'Application of Collaborative Optimization to an Aircraft Wing Design,' M. S. Thesis, Seoul National University, Seoul, in Korea
  8. Jang, B., Yang, Y., Jung, H. and Yeun, Y., 2005, 'Managing Approximation Models in Collaborative Optimization,' Structural and Multidisciplinary Optimization, Vol. 30, No. 1, pp. 1126
  9. Jeon, K., 2001,' Collaborative Optimization and the Response Surface Modeling for the Multidisciplinary Design Optimization,' M. S. Thesis, Konkuk University, Seoul, in Korea
  10. Jeon, Y., Jun, S., Ku, Y. and Lee, D., 2004, 'Multidisciplinary Optimization of the Supersonic Wing with Multi-level and Approximation Methods,' Proc. of the 2004 KSAS Spring Conference, KSAS04-1405, pp. 559-562. (in Korea)
  11. Jeon, Y., Park, E., Kim, Y., Jun, S., Ku, Y. and Lee, D., 2004, 'Feasibility Improvement of the Design Space Using Probabilistic Method,' 42th AIAA Aerospace Sciences Meeting and Exhibit, AIAA-2004-0537
  12. Jun, S., Ghim, Y., Jeon, Y. and Lee, D., 2003, 'Collaborative Optimization Using Response Surface Methodology,' Proc. of the 2003 KSAS Fall Conference, KSAS03-2202, pp. 494-497, in Korea
  13. Jun, S., Jeon, Y., Rho, J. and Lee, D., 2004, 'Application of Collaborative Optimization Using Response Surface Methodology to an Aircraft Wing Design,' 10th AIAA/ISSMO Multi-disciplinary Analysis and Optimization Conference, AIAA-2004-4442
  14. Kim, Y., Jeon, Y. and Lee, D., 2005, 'Multiobjective and Multidisciplinary Design Optimization of Supersonic Fighter Wing,' Journal of Aircraft, Accepted
  15. Kim, Y., Kim, J., Jeon, Y., Bang, J., Lee, D., Kim, Y. and Park, C., 2002, 'Multidisciplinary Aerodynamic-Structural Design Optimization of Supersonic Fighter Wing Using Response Surface Methodology,' 40th AIAA Aerospace Sciences Meeting and Exhibit, AIAA-2002-0322
  16. Kim, Y., Lee, D., Kim, Y. and Yee, K., 2002, 'Multidisciplinary Design Optimization of Supersonic Fighter Wing Using Response Surface Methodology,' 9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, AlAA-2002-5408
  17. Kodiyalam, S., 1998, 'Evaluation of Methods for MUltidisciplinary Design Optimization (MOO), Phase I,' NASA CR-1998-208716
  18. Kroo, I. and Manning, V., 2000, 'Collaborative Optimization; Status and Directions,' 8th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary A nalysis and Optimization, AIAA-2000-4721
  19. Sobieski, I. P. and Kroo, I. M., 2000, 'Collaborative Optimization Using Response Surface Estimation,' AIAA Journal, Vol. 38, No. 10, pp.1931-1938 https://doi.org/10.2514/2.847
  20. Yoon, S., Ahn, J. and Lee, D., 1999, 'Multidisciplinary Optimal Design of a Transport Wing Configuration,' KSAS Journal, Vol. 27, No.6, pp. 128-138.(in Korea)