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Multidisciplinary Optimization of Multibody Systems with Application to the Design of Rail Vehicles

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Abstract

A methodology for the design optimization of multibody systems is presented. The methodology has the following features: (1) multibody dynamics is employed to model and simulate complex systems; (2) multidisciplinary optimization (MDO) methods are used to combine multibody systems and additional systems in a synergistic manner; (3) using genetic algorithms (GAs) and other effective search algorithms, the mechanical and other design variables are optimized simultaneously. The methodology is shown to handle the conflicting requirements of rail vehicle design, i.e., lateral stability, curving performance, and ride quality, in an effective manner. By coordinating these conflicting requirements at the system level, three multibody models corresponding to each of these requirements for a rail vehicle are optimized simultaneously.

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References

  1. Kodiyalam, S. and Sobieski, J., ‘Multidisciplinary design optimization—Some formal methods, framework requirements, and application to vehicle design’, International Journal of Vehicle Design, Special Issue, 25(1/2), 2001, 3–22.

  2. Bestle, D. and Eberhard, P., ‘Dynamic system design via multicriteria Optimization’, in Multiple Criteria Decision Making: Proceedings of the Twelfth International Conference on Multiple Criteria Decision Making, Fandel, G. and Gal, T. (eds.), Springer-Verlag, 1995, pp. 467–478.

  3. He, Y., ‘Design of rail vehicles with passive and active suspensions using multidisciplinary optimization, multibody dynamics, and genetic algorithms’, Ph.D. Thesis, University of Waterloo, Canada, 2003.

  4. He, Y. and McPhee, J., ‘Design optimization of rail vehicles with passive and active suspensions: A combined approach using genetic algorithms and multibody dynamics’, Vehicle System Dynamics 37(Suppl.), 2002, 397–408.

    Google Scholar 

  5. Sobieski, J. and Haftka, R., ‘Multidisciplinary aerospace design optimization: Survey of recent developments’, Structural Optimization 14(1), 1997, 1–23.

    Article  Google Scholar 

  6. Sobieski, J., Kodiyalam, J. and Yang, R., ‘Optimization of car body for noise, vibration and harshness and crash’, in Proceedings of the 41st AIAA/ASME/AHS/ASC, Structures, Structural Dynamics, and Materials, Number AIAA-2001-1273, Atlanta, 2000.

  7. Yang, R., Gu, L., Tho, C. and Sobieski, J., ‘Multidisciplinary design optimization of a full vehicle with high performance computing’, in Proceedings of the 42nd AIAA/ASME/AHS/ASC, Structures, Structural Dynamics, and Materials, Number AIAA-2001-1273, Seattle, Washington, 2001.

  8. He, Y. and McPhee, J., Colloquium on Computer-Aided Optimization of Mechanical Systems, Erlangen–Nurenmberg, Germany, 2003.

    Google Scholar 

  9. Anderson, R., ‘The A'GEM multibody dynamics package’, Vehicle System Dynamics 22, 1993, 41–44.

    Google Scholar 

  10. Eberhard, P., Schiehlen, W. and Bestle, D., ‘Some advantages of stochastic methods in multicriteria optimization of multibody systems’, Archive of Applied Mechanics 69, 1999, 543–554.

    Google Scholar 

  11. Cramer, E., Dennis, J., Frank, P., Lewis, R. and Shubin, G., ‘Problem formulation for multidisciplinary design optimization’, SIAM Journal on Optimization 4(4), 1994, 754–776.

    Article  Google Scholar 

  12. Braun, R. and Kroo, I., ‘Development and application of the collaborative optimization architecture in a multidisciplinary design environment’, in Multidisciplinary Design Optimization: State of the Art, Alexandrov, N. and Hussaini, M. (eds.), Society of Industrial and Applied Mathematics (SIAM) Publications, Philadelphia, Softbound, ISBN 0-89871-359-5, February, 1997.

  13. Kodiyalam, S. and Sobieski, J., ‘Bi-level lntegrated system synthesis with response surface’, AIAA Journal 38(8), 2000, 3476–3488.

    Google Scholar 

  14. Renaud, J. and Gabriele, G., ‘Improved coordination in non-hierarchic system optimization’, AIAA Journal 31(12), 1993, 2367–2373.

    Google Scholar 

  15. Bestle, D. and Eberhard, P., ‘Multi-criteria multi-model design optimization’, in Optimization of Mechanical Systems: Proceedings of the IUTAM Symposium on Optimization of Mechanical Systems, Bestle, D. and Schiehlen, W. (eds.), Kluwer Academic Publishers, 1995, 467–478.

  16. Goldberg, D., Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, Reading, Massachusetts, 1989.

    Google Scholar 

  17. Baumal, A., ‘Automated design of mechanical systems through numerical optimization of dynamic behaviour’, Master's Thesis, University of Waterloo, Canada, 1997.

  18. He, Y. and McPhee, J., ‘Optimization of the lateral stability of rail vehicles’, Vehicle System Dynamics 38(5), 2002, 361–390.

    Article  Google Scholar 

  19. Fortin, C., ‘Dynamic curving simulation of forced-steering rail vehicles’, Ph.D. Thesis, Queen's University, Canada, 1984.

  20. He, Y. and McPhee, J., ‘Optimization of curving performance of rail vehicles’, Vehicle System Dynamics, in press.

  21. Wickens, A., ‘The dynamic stability of a simplified four-wheeled railway vehicle having profiled wheels’, International Journal of Solids and Structures 1, 1965, 385–406.

    Article  Google Scholar 

  22. Hedrick, J., Wormly, D. and Kar, A., ‘Performance limits of rail passenger vehicles: Evaluation and optimization’, in Technical Report Prepared under U.S. Department of Transportation, Contract DOT-OS-70052, 1978.

  23. Garg, V. and Dukkipati, R., Dynamics of Railway Vehicle Systems, Academic Press, Toronto, 1984.

    Google Scholar 

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Correspondence to John Mcphee.

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He, Y., Mcphee, J. Multidisciplinary Optimization of Multibody Systems with Application to the Design of Rail Vehicles. Multibody Syst Dyn 14, 111–135 (2005). https://doi.org/10.1007/s11044-005-4310-0

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  • DOI: https://doi.org/10.1007/s11044-005-4310-0

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