Transactions of the Korean Society of Mechanical Engineers A (대한기계학회논문집A)

The Korean Society of Mechanical Engineers (대한기계학회)
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Improvement of Sensitivity Based Concurrent Subspace Optimization Using Automatic Differentiation

자동미분을 이용한 민감도기반 분리시스템동시최적화기법의 개선

  • Published : 2001.02.01
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Abstract

The paper describes the improvement on concurrent subspace optimization(CSSO) via automatic differentiation. CSSO is an efficient strategy to coupled multidisciplinary design optimization(MDO), wherein the original design problem is non-hierarchically decomposed into a set of smaller, more tractable subspaces. Key elements in CSSO are consisted of global sensitivity equation, subspace optimization, optimum sensitivity analysis, and coordination optimization problem that require frequent use of 1st order derivatives to obtain design sensitivity information. The current version of CSSO adopts automatic differentiation scheme to provide a robust sensitivity solution. Automatic differentiation has numerical effectiveness over finite difference schemes tat require the perturbed finite step size in design variable. ADIFOR(Automatic Differentiation In FORtran) is employed to evaluate sensitivities in the present work. The use of exact function derivatives facilitates to enhance the numerical accuracy during the iterative design process. The paper discusses how much the automatic differentiation based approach contributes design performance, compared with traditional all-in-one(non-decomposed) and finite difference based approaches.

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References

  1. Sobieski, J., 1993, 'Multidisciplinary Design Optimization: An Emerging New Engineering Discipline,' World Congress on Optimal Design of Structural Systems, Rio de Janeiro, Brazil
  2. Tolson, R. H., Sobieski, J., 1985, 'Multidisciplinary Analysis and Synthesis: Needs and Opportunities,' AIAA Paper No. 85-0584
  3. Sobieski, J., 1982,'A Linear Decomposition Method for Large Optimization Problems - Blueprint for Development,' NASA TM-83248
  4. Sobieski, J., 1988, 'Optimization by Decomposition: A Step from Hierarchic to Non-Hierarchic Systems,' NASA CP-30301
  5. Bloebaum, C. L., 1991, 'Formal and Heuristic System Decomposition Methods in Multidisciplinary Synthesis,' Ph.D Dissertation in Aerospace Engineering, the University of Florida, Gainseville, FL
  6. Hajla, P., Bloebaum, C. L., and Sobieski, J., 1990, 'Application of Global Sensitivity Equations in Multidisciplinary Aircraft Synthesis,' the AIAA Journal of Aircraft, Vol. 27, No. 12, pp. 1002-1010
  7. Iri, M., 1998, 'Automatic Computation of Partial Derivatives and Rounding Error Estimates with Applications to Large-Scale Systems of Nonlinear Equations,' Journal of computers and Applied Mathematics, Vol. 24, pp. 365-392 https://doi.org/10.1016/0377-0427(88)90298-1
  8. Rall, L. B., 1981, 'Automatic Differentiation: Techniques and Applications,' Lecture Notes in Computer Science No. 120, Springer, New York
  9. Bathelemy, J.-F. M., Hall, L. E., 1995, 'Automatic Differentiation as a Tool in Engineering Design,' Structural Optimization, Vol. 9, pp. 76-82
  10. Walsh, J., and Young, K., 1995, 'Automatic Differentiation Evaluated as a Tool for Rotorcraft Design and Optimization,' proceedings of the American Helicopter Society National Technical Specialists' Meeting on Rotorcraft Structures, Williamsburg, VA
  11. Bischof, C., Corliss, G., Green, L., Griewank, A., Haigler, K., Newman, P., 1992, 'Automatic Differentiation of Advanced CFD Codes for Multidisciplinary Design,' Computing System in Engineering, Vol. 3, No. 6, pp. 625-637 https://doi.org/10.1016/0956-0521(92)90014-A
  12. ADIFOR 2.0: User's Manual(Revision D), Rice University, Houston, Texas
  13. Vanderplaats,G. N., 1973, 'CONMIN-A FORTRAN Program for Constrained Function Minimization - User's Manual,' NASA TMX-62282
  14. NASA-MDOB Test Suite Problems, NASA Langley Research Center, Hampton, VA, 1996
  15. Arslan, M., 1998, 'Domain Decomposition in Multidisciplinary Design: Role of Artificial Neural Networks and Intelligent Agents,' Ph.D. Dissertation in Mechanical Engineering Rensselaer Polytechnic Institute, Troy, NY