TY - JOUR
T1 - Evolutionary optimization of transonic airfoils for static and dynamic trim performance
AU - Candon, Michael
AU - Carrese, Robert
AU - Joseph, Nishit
AU - Ogawa, Hideaki
AU - Marzocca, Pier
N1 - Publisher Copyright:
© 2016, © The Author(s) 2016.
PY - 2017/5/1
Y1 - 2017/5/1
N2 - The development and accelerated use of optimization frameworks in aircraft design is a testament to their ability to identify optimal and often non-intuitive shapes as a result of multi-disciplinary design objectives. Airfoil design is a continuously revised multi-disciplinary problem, and is pivotal to illustrate the performance of optimization frameworks involving numerical simulation, flexible shape parametrization, and intelligent evolutionary algorithms. An often overlooked component of this classic problem is to consider the dynamic aeroelastic behavior under trim conditions, which can generate explicit boundaries to the flight envelope. Trim introduces a significantly strong coupling with objectives governing static performance, e.g. aerodynamic and/or structural, thereby resulting in a highly nonlinear and discontinuous design space. In this paper, a multi-objective particle swarm optimization framework for multi-disciplinary performance improvement is presented, pertaining to aerodynamic, structural and aeroelastic design criteria at trim conditions. The framework is assisted by the construction of adaptive Kriging surrogates, which is cooperatively used with the numerical solver to identify optimal solutions within a computational constraint. Designer preferences are introduced to reflect the optimal compromise between the objectives. Results of the optimization process indicate a large spread in design variable influence and interaction, and a subtle yet clear distinction between all objectives is illustrated through the catalog of final airfoil candidates obtained.
AB - The development and accelerated use of optimization frameworks in aircraft design is a testament to their ability to identify optimal and often non-intuitive shapes as a result of multi-disciplinary design objectives. Airfoil design is a continuously revised multi-disciplinary problem, and is pivotal to illustrate the performance of optimization frameworks involving numerical simulation, flexible shape parametrization, and intelligent evolutionary algorithms. An often overlooked component of this classic problem is to consider the dynamic aeroelastic behavior under trim conditions, which can generate explicit boundaries to the flight envelope. Trim introduces a significantly strong coupling with objectives governing static performance, e.g. aerodynamic and/or structural, thereby resulting in a highly nonlinear and discontinuous design space. In this paper, a multi-objective particle swarm optimization framework for multi-disciplinary performance improvement is presented, pertaining to aerodynamic, structural and aeroelastic design criteria at trim conditions. The framework is assisted by the construction of adaptive Kriging surrogates, which is cooperatively used with the numerical solver to identify optimal solutions within a computational constraint. Designer preferences are introduced to reflect the optimal compromise between the objectives. Results of the optimization process indicate a large spread in design variable influence and interaction, and a subtle yet clear distinction between all objectives is illustrated through the catalog of final airfoil candidates obtained.
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U2 - 10.1177/1045389X16679019
DO - 10.1177/1045389X16679019
M3 - Article
AN - SCOPUS:85019156908
VL - 28
SP - 1071
EP - 1088
JO - Journal of Intelligent Material Systems and Structures
JF - Journal of Intelligent Material Systems and Structures
SN - 1045-389X
IS - 8
ER -