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Multi-Objective Aerodynamic and Stealthy Performance Optimization for Airfoil Using Kriging Surrogate Model

机译:使用Kriging代理模型的翼型多目标空气动力学和隐形性能优化

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The Class-Shape function Transformation (CST) method is used to describe the parameterized airfoil geometry. The parameterized models for aerodynamic and stealthy performance of airfoil are constructed. The aerodynamic analysis model of airfoil is constructed by Computational Fluid Dynamics (CFD) method based on N-S equations. And the stealthy performance analysis model of airfoil is constructed by Computational Electromagnetic Method (CEM) based Method of Moments (MoM). The multi-objective aerodynamic and stealthy performance optimization method for airfoil using Kriging surrogate model is presented in this paper. The Latin hypercube method is employed to get a set of sample points. The aerodynamic and stealthy performance Kriging models are built. The multi-objective aerodynamic and stealthy performance optimization of airfoil is optimized by combining Pareto genetic algorithm with Kriging surrogate model. The presented method is validated by two applications. The results of the investigation show that the constructed analysis models are reasonable and the presented multi-objective optimization design method is feasible, which can improve the performance of airfoil and the efficiency of optimization effectively.
机译:类形函数变换(CST)方法用于描述参数化翼型几何形状。构建了用于空气动力学和翼型性能的参数化模型。基于N-S方程的计算流体动力学(CFD)方法构建翼型的空气动力学分析模型。翼型的隐身性能分析模型由基于计算电磁法(CEM)的矩(MEM)构成。本文介绍了使用Kriging代理模型的翼型的多目标空气动力学和隐形性能优化方法。采用拉丁超立方体方法来获得一组样本点。建立了空气动力学和隐形性能Kriging模型。通过将Pariging遗传算法与Kriging代理模型相结合来优化翼型的多目标空气动力学和隐形性能优化。呈现的方法由两个应用程序验证。调查结果表明,构造的分析模型是合理的,所示的多目标优化设计方法是可行的,可以提高翼型的性能和有效优化的优化效率。

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