One of the new challenges in aeronautics is combining and accounting for multiple disciplines while considering uncertainties or variability in the design parameters or operating conditions. This paper describes a methodology for robust multidisciplinary design optimisation when there is uncertainty in the operating conditions. The methodology, which is based on canonical evolution algorithms, is enhanced by its coupling with an uncertainty analysis technique. The paper illustrates the use of this methodology on two practical test cases related to Unmanned Aerial Systems (UAS). These are the ideal candidates due to the multi-physics involved and the variability of missions to be performed. Results obtained from the optimisation show that the method is effective to find useful Pareto non-dominated solutions and demonstrate the use of robust design techniques.
Evolutionary Optimisation Methods with Uncertainty for Modern Multidisciplinary Design in Aeronautical Engineering
2009
14 Seiten
Aufsatz/Kapitel (Buch)
Englisch
Multidisciplinary design optimisation under uncertainty: an information model approach
Online Contents | 2013
|Multidisciplinary design optimisation under uncertainty: an information model approach
Kraftfahrwesen | 2013
|Multidisciplinary Optimization of Aeronautical Systems
AIAA | 1990
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