A comprehensive preference-based optimization framework with application to high-lift aerodynamic design

Abstract

An integral component of transport aircraft design is the high-lift configuration, which can provide significant benefits in aircraft payload-carrying capacity. However, aerodynamic optimization of a high-lift configuration is a computationally challenging undertaking, due to the complex flow-field. We propose the use of a designerinteractive multiobjective optimization framework which identifies and exploits preferred regions of the Pareto frontier. Visual data mining tools are introduced to statistically extract information from the design space and confirm the relative influence of both variables and objectives to the preferred interests of the designer. The framework is assisted by the construction of time-adaptive Kriging models, which are cooperatively used with a high fidelity Reynolds-averaged Navier-Stokes solver. The successful integration of these design tools is facilitated through the specification of a reference point, which is ideally based on an existing design configuration. The framework is demonstrated to perform efficiently for the present case-study within the imposed computational budget.

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ORCID for Andras Sobester: orcid.org/0000-0002-8997-4375

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