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Adjoint Variable Method Combined with Complex Variable for Structural Design Sensitivity

보조변수법과 복소변수를 연동한 설계 민감도 해석 연구

  • Published : 2009.03.01

Abstract

The adjoint variable method can reduce computation time and save computer resources because it can selectively provide the sensitivity information for the positions that designers wish to measure. However, the adjoint variable method commonly employs exact analytical differentiation with respect to the design variables. It can be cumbersome to precisely differentiate every given type of finite element. This trouble can be overcome only if the numerical differentiation scheme can replace this exact manner of differentiation. But, the numerical differentiation scheme causes of severe inaccuracy due to the perturbation size dilemma. For assuring the accurate sensitivity without any dependency of perturbation size, this paper employs a complex variable that has been mainly used for computational fluid dynamics problems. The adjoint variable method combined with complex variables is applied to obtain the shape and size sensitivity for structural optimization. Numerical examples demonstrate that the proposed method can predict stable sensitivity results and that its accuracy is remarkably superior to traditional sensitivity evaluation methods.

Keywords

References

  1. Zienkiewicz, O.C. and Campbell, J.S., 1973, “Shape Optimization and Sequential Linear Programming. In Optimum Structural Design, Gallgher RH, Zienkiewicz OC (eds). Wiley: New York, pp. 109-127
  2. Barthelemy, B., Chen C.T. and Haftka, R.T., 1986, Sensitivity Approximation of the Static Structural Response. In First World Congress on Computational Mechanics, Austin, TX, Sept
  3. Pederson, P., Cheng, G. and Rasmussen, J., 1989, On Accuracy Problems of Semi-Analytical Sensitivity Analysis. Mechanics of Structures and Machines, Vol.17, No.3, pp. 373-384 https://doi.org/10.1080/089054508915647
  4. Cheng, G. and Liu, Y., 1987, A New Sensitivity Scheme for Sensitivity Analysis. Engineering Optimization, Vol.12, pp. 219-234 https://doi.org/10.1080/03052158708941096
  5. Cheng, G., Gu, Y. and Zhou, Y., 1989, Accuracy of Semi-Analytical Sensitivity Analysis. Finite Elements in Analysis and Design, Vol. 6, pp. 113-128 https://doi.org/10.1016/0168-874X(89)90039-5
  6. Olhoff N. and Rasmussen, J., 1991, Study of Inaccuracy in Semi-Analytical Analysis-a Model Problem. Structural Optimization, Vol. 3, pp. 203-213 https://doi.org/10.1007/BF01744055
  7. Barthelemy, B., Chon, C.T. and Haftka, R.T., 1988, Accuracy Problems Associated with Semi-Analytical Derivatives of Static Response. Finite Elements in Analysis and Design, Vol.4, pp. 249-265 https://doi.org/10.1016/0168-874X(88)90011-X
  8. Van Keulen, F. and De Boer, H., 1998, Rigorous Improvement of Semi-Analytical Design Sensitivities by Exact Differentiation of Rigid Body Motions. International Journal for Numerical Methods in Engineering, Vol.42, pp. 71-91 https://doi.org/10.1002/(SICI)1097-0207(19980515)42:1<71::AID-NME350>3.0.CO;2-C
  9. De Boer, H. and Van Keulen, F., 2000, Refined Semi-Analytical Design Sensitivities. International Journal of Solids and Structures, Vol.37, pp.6961-6980 https://doi.org/10.1016/S0020-7683(99)00322-4
  10. Parente, E. Jr. and Vaz, L.E., 2001, Improvement of semi Analytical Design Sensitivities of Non-Linear Structures Using Equilibrium Relations. International Journal for Numerical Methods in Engineering, Vol.50, pp. 2127-2142 https://doi.org/10.1002/nme.115
  11. Cho, M. and Kim, H., 2005, A Refined Semi-Analytic Design Sensitivity Based on Mode Decomposition and Neumann Series. International Journal for Numerical Methods in Engineering, Vol.62, pp.19-49 https://doi.org/10.1002/nme.1163
  12. Cho, M. and Kim, H., 2006, Improved Semi-Analytic Sensitivity Analysis Combined with Iterative Scheme in the Framework of Adjoint Variable Method, Computers and Structures, Vol.84, Issue 29-30, pp.1827-1840 https://doi.org/10.1016/j.compstruc.2006.08.042
  13. Lyness, J.N. and Moler, C.B., 1967, Numerical Differentiation of Analytic Functions, SIAM, J. Numer. Anal., Vol.4: pp.202-210 https://doi.org/10.1137/0704019
  14. Lyness, J.N., 1967, Numerical Algorithms Based on the Theory of Complex Variables, Proc. ACM 22nd Nat. Conf. Thompson Book Co. Washington DC, pp.124-134 https://doi.org/10.1145/800196.805983
  15. Squire, W. and Trapp, G., 1998, Using complex variables to Estimate Derivatives of Real Functions, SIAM Rev. Vol.40, No.1, pp.110-112 https://doi.org/10.1137/S003614459631241X
  16. Martins, J.R.R.A., Kroo, I.M. and Alonso, J.J., 2000, An Automated Method for Sensitivity Analysis Using Complex Variables, AIAA Paper 2000-0689
  17. Martins, J.R.R.A., Sturdza, P. and Alonso, J.J., 2001, The Connection Between the Complex-step Derivative Approximation and Algorithmic Differentiation, AIAA Paper 2001-0921
  18. Anderson, W.K., Newman, J.C., Whitfield, D.L. and Nielsen, E.J., 1999, Sensitivity Analysis for the Navier-stokes Equation on Unstructured Meshes Using Complex Variables, AIAA Paper No. 99-3294, Proceedings of the 17th Applied Aerodynamics Conference
  19. Newman, J.C., Anderson, W.K. and Whitfield, D.L., 1998, Multidisciplinary Sensitivity Derivatives Using Complex Variables, MSSU-COE-ERC-98-08
  20. Cervino, L.I. and Bewley, T.R., 2003, On the extension of the Complex-Step Derivative Technique to Pseudospectral Algorithms, Journal of Computational Physics, Vol.187, pp.544-549 https://doi.org/10.1016/S0021-9991(03)00123-2
  21. Burg, C.O.E. and Newman J.C., III, 2003, Computationally Efficient, Numerically Exact Design Space Derivatives via the Complex Talyor's Series Expansion Method, Computers and Fluids, Vol.32, pp.373-383 https://doi.org/10.1016/S0045-7930(01)00044-5