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Multi-objective aerodynamic and stealthy performance optimization for airfoil using Kriging surrogate model

机译:使用Kriging替代模型的机翼多目标空气动力学和隐身性能优化

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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:类形状函数转换(CST)方法用于描述参数化的机翼几何形状。建立了翼型的空气动力学和隐身性能的参数化模型。基于N-S方程的计算流体动力学(CFD)方法建立了翼型的空气动力学分析模型。通过基于计算电磁法(CEM)的矩量法(MoM),建立了机翼的隐身性能分析模型。提出了基于克里格代理模型的机翼多目标气动隐身性能优化方法。采用拉丁超立方体方法来获取一组采样点。建立了空气动力学和隐身性能的克里格模型。通过将帕累托遗传算法与克里格代理模型相结合,对翼型的多目标气动和隐身性能进行了优化。所提出的方法由两个应用程序验证。研究结果表明,所建立的分析模型是合理的,所提出的多目标优化设计方法是可行的,可以有效提高机翼性能和优化效率。

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