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Robust optimization of 2D airfoils driven by full Navier-Stokes computations

机译:由完整的Navier-Stokes计算驱动的2D机翼的稳健优化

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摘要

A new approach to the constrained design of aerodynamic shapes is suggested. The approach employs Genetic Algorithms (GAs) as an optimization tool in combination with a Reduced-Order Models (ROM) method based on linked local data bases obtained by full Navier-Stokes computations. The important features of the approach include: (1) a new strategy for efficient handling of non-linear constraints in the framework of GAs (2) scanning of the optimization search space by a combination of full Navier-Stokes computations with the ROM method (3) multilevel parallelization of the whole computational framework. The method was applied to the problem of one-point transonic profile optimization with non-linear constraints. The results demonstrated that the approach combines high accuracy of optimization (based on full Navier-Stokes computations) and efficient handling of various non-linear constraints with high computational efficiency and robustness. A significant computational time-saving (in comparison with optimization tools fully based on Navier-Stokes computations) allowed the method to be used in a demanding engineering environment.
机译:提出了一种新的方法来限制空气动力学形状的设计。该方法采用遗传算法(GA)作为优化工具,并与基于通过完整Navier-Stokes计算获得的链接本地数据库的降阶模型(ROM)方法结合使用。该方法的重要特征包括:(1)在GA框架中有效处理非线性约束的新策略(2)通过将完整的Navier-Stokes计算与ROM方法结合使用来扫描优化搜索空间( 3)整个计算框架的多级并行化。该方法被应用于非线性约束的单点跨音速剖面优化问题。结果表明,该方法结合了优化的高精度(基于完整的Navier-Stokes计算)和对各种非线性约束的有效处理以及较高的计算效率和鲁棒性。节省大量计算时间(与完全基于Navier-Stokes计算的优化工具相比)使该方法可用于苛刻的工程环境中。

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