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Contribution to Book
Robust Design Optimization by Polynomial Dimensional Decomposition
Proceedings of AIAA Aviation Technology, Integration and Operations Conference and the AIAA/ISSMO Multidisciplinary Analysis Optimization Conference (2012)
  • Xuchun Ren, Georgia Southern University
  • Sharif Rahman, University of Iowa
Abstract
This paper introduces four new methods for robust design optimization (RDO) of complex engineering systems. The methods involve polynomial dimensional decomposition (PDD) of a high-dimensional stochastic response for statistical moment analysis, a novel integration of PDD and score functions for calculating the second-moment sensitivities with respect to the design variables, and standard gradient-based optimization algorithms. New closed-form formulae are presented for the design sensitivities that are simultaneously determined along with the moments. The methods depend on how statistical moment and sensitivity analyses are dovetailed with an optimization algorithm, encompassing direct, single-step, sequential, and multi-point single-step design processes. Numerical results indicate that the proposed methods provide accurate and computationally efficient optimal solutions of RDO problems, including an industrial-scale lever arm design.
Keywords
  • Robust design optimization,
  • Polynomial dimensional decomposition
Publication Date
September 17, 2012
Publisher
American Institute of Aeronautics and Astronautics
ISBN
978-1-60086-930-3
DOI
10.2514/6.2012-5564
Citation Information
Xuchun Ren and Sharif Rahman. "Robust Design Optimization by Polynomial Dimensional Decomposition" Indianapolis, INProceedings of AIAA Aviation Technology, Integration and Operations Conference and the AIAA/ISSMO Multidisciplinary Analysis Optimization Conference (2012) p. 1 - 27
Available at: http://works.bepress.com/xuchun_ren/13/