An Approach Based on Enhanced Collaborative Optimization and Kriging Approximation in Multidisciplinary Design Optimization

Abstract:

This paper concentrates on the computational challenge in multidisciplinary design optimization (MDO) and a comprehensive strategy combining enhanced collaborative optimization (ECO) and kriging approximation models is introduced. In this strategy, the computational and organizational advantages of original collaborative optimization (CO) are inherited by ECO, which can satisfy the strengthened consistency requirements. Kriging approximation models are constructed to replace high-fidelity simulation models in individual disciplines and reduce the expensive computational cost in practical MDO problems. The proposed methodology is demonstrated by solving the classical speed reducer design problem. The better results indicate that ECO using kriging approximation models can achieve a considerable reduction of computational expense while guaranteeing the accuracy of optimal solutions with efficient convergence.

• Periodical: Advanced Materials Research (Volumes 118-120)
• Pages: 399-403
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.118-120.399
• Online since: June 2010
• Authors: M. Xiao, Liang Gao, Hao Bo Qiu, Xin Yu Shao, Xue Zheng Chu
• Keywords: Collaborative Optimization (CO), Enhanced Collaborative Optimization (ECO), Kriging Approximation, Multidisciplinary Design Optimisation (MDO)

References

[1] T.A. Zang and L.L. Green: Multidisciplinary Design Optimization Techniques: Implications and Opportunities for Fluid Dynamics Research, 30th AIAA Fluid Dynamics Conference, Norfolk, VA, AIAA Paper 99-3798 (1999).

DOI: 10.2514/6.1999-3798

[2] R.D. Braun and I.M. Kroo, in: Multidisciplinary Design Optimization: State of the Art, edited by N. Alexandrov and M.Y. Hussaini, SIAM (1996).

[3] M. Xiao, H.B. Qiu, L. Gao, X.Y. Shao and X.Z. Chu: An Enhanced Collaborative Optimization Methodology for Multidisciplinary Design Optimization, 2010 International Conference on Mechanical, Industrial, and Manufacturing Technologies, Sanya, China (2010).

[4] J. Sacks, W.J. Welch, T.J. Mitchell and H.P. Wynn: Statistical Science Vol. 4 (1989), p.409.

[5] T.W. Simpson, T.M. Mauery, J.J. Korte and F. Mistree: AIAA Journal Vol. 39 (2001), p.2233.

[6] T.W. Simpson, A.J. Booker, D. Ghosh, A.A. Giunta, P.N. Koch and R.J. Yang: Structural Multidisciplinary Optimization Vol. 27 (2004), p.302.