LOcal Uncertainty Processing (LOUP) method for multidisciplinary robust design optimization

doi:10.1007/s00158-012-0798-0

2012-04-24

PRE

Vincent Baudoui *

Patricia Klotz

Jean‐Baptiste Hiriart‐Urruty

Franck Morel

DOI：10.1007/s00158-012-0798-0

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摘要

En 中文

In this paper, we develop an easy-to-implement approximate method to take uncertainties into account during a multidisciplinary optimization. Multidisciplinary robust design usually involves setting up a full uncertainty propagation within the system, requiring major modifications in every discipline and on the shared variables. Uncertainty propagation is an expensive process, but robust solutions can be obtained more easily when the disciplines affected by uncertainties have a significant effect on the objectives of the problem. A heuristic method based on local uncertainty processing (LOUP) is presented here, allowing approximate solving of specific robust optimization problems with minor changes in the initial multidisciplinary system. Uncertainty is processed within the disciplines that it impacts directly, without propagation to the other disciplines. A criterion to verify a posteriori the applicability of the method to a given multidisciplinary system is provided. The LOUP method is applied to an aircraft preliminary design industrial test case, in which it allowed to obtain robust designs whose performance is more stable than the one of deterministic solutions, relatively to uncertain parameter variations.

Keyword:

Multidisciplinary design optimization

Robust design optimization

Multi-objective design optimization

Uncertainty

Surrogate model