Titlebook: Application of Surrogate-based Global Optimization to Aerodynamic Design; Emiliano Iuliano,Esther Andrés Pérez Book 2016 Springer Internat

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Aerodynamic Shape Design by Evolutionary Optimization and Support Vector Machines,jective function, in combination with an evolutionary algorithm (EA) to enable the discovery of global optima. The proposed methodology is applied to improve the aerodynamic performance of a two-dimensional airfoil and a three-dimensional wing and results on surrogate model validation and optimization-focused sampling criteria are discussed.

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Adaptive Sampling Strategies for Surrogate-Based Aerodynamic Optimization,sts of the Proper Orthogonal Decomposition of computed aerodynamic flow fields and Radial Basis Functions interpolation to reconstruct the aerodynamic flow at any unknown design vector. The surrogate model is coupled to an evolutionary algorithm to globally explore the design space. Several adaptive

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PCA-Enhanced Metamodel-Assisted Evolutionary Algorithms for Aerodynamic Optimization,rther accelerated by exploiting the principal component analysis (PCA) of the elite members of the evolving population. In each generation of the MAEA, PCA is used to (a) better guide the application of evolution operators and (b) train metamodels, in the form of radial basis functions networks, on

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