Multidisciplinary design optimization framework for the pre design stage

Date

2010-09-30T00:00:00Z

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Publisher

Springer Science Business Media

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Type

Article

ISSN

0921-0296

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Citation

M. Guenov, P. Fantini, L. Balachandran, J. Maginot, M. Padulo and M. Nunez. Multidisciplinary design optimization framework for the pre design stage. Journal of Intelligent and Robotic Systems, Volume 59, Issue 3-4, 2010, pp223-240.

Abstract

Presented is a novel framework for performing flexible computational design studies at preliminary design stage. It incorporates a workflow management device (WMD) and a number of advanced numerical treatments, including multi-objective optimization, sensitivity analysis and uncertainty management with emphasis on design robustness. The WMD enables the designer to build, understand, manipulate and share complex processes and studies. Results obtained after applying the WMD on various test cases, showed a significant reduction of the iterations required for the convergence of the computational system. The tests results also demonstrated the capabilities of the advanced treatments as follows: The novel procedure for global multi-objective optimization has the unique ability to generate well-distributed Pareto points on both local and global Pareto fronts simultaneously. The global sensitivity analysis procedure is able to identify input variables whose range of variation does not have significant effect on the objectives and constraints. It was demonstrated that fixing such variables can greatly reduce the computational time while retaining a satisfactory quality of the resulting Pareto front. The novel derivative-free method for uncertainty propagation, which was proposed for enabling multi-objective robust optimization, delivers a higher accuracy compared to the one based on function linearization, without altering significantly the cost of the single optimization step.

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Keywords

Design computational workflow Multidisciplinary design optimisation Multiobjective optimisation Robust optimisation Sensitivity analysis Uncertainty management normal constraint method robust design pareto frontier

Rights

The original publication is available at www.springerlink.com

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