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Aerodynamic inverse design using multifidelity models and manifold mapping

机译：使用多保真度模型和歧管映射的空气动力学逆设计

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摘要

Aerodynamic inverse design is proposed using multifidelity models and the manifold mapping (MM) technique. Aerodynamic inverse design aims at achieving a target performance characteristic, such as a pressure coefficient distribution of an airfoil or local lift distribution of a wing. Due to the high computational cost of accurate aerodynamic models and the large number of design variables, the overall cost of inverse design can be prohibitive. The MM-based optimization algorithm leverages the speed of the low-fidelity model to accelerate the optimization process, but refers back to the high-fidelity model to ensure an accurate solution. In this work, the MM technique is applied to the characteristic distribution under consideration in each application. In particular, the pressure coefficient distribution is modeled with the MM technique in the case of airfoil inverse design, and the sectional lift distribution in the case of wing design. The proposed method is tested and evaluated on six airfoil inverse design cases and one rectangular wing inverse design case. In the two-dimensional cases, parameterized with eight design variables, direct aerodynamic inverse design using pattern search required 700 to 1200 high-fidelity model evaluations, which took 300 to 700 hours in total. The MM-based design algorithm required less than 20 high-fidelity simulations and 1000 to 2000 low-fidelity evaluations, which took 30 to 90 hours. In the three-dimensional case, parameterized with three design variables, direct aerodynamic inverse design took around 50 hours, whereas the MM-based design needed around six hours. (C) 2018 Elsevier Masson SAS. All rights reserved.
机译：使用多保真度模型和歧管映射（MM）技术提出了气动逆设计。空气动力学逆向设计旨在实现目标性能特征，例如机翼的压力系数分布或机翼的局部升力分布。由于精确的空气动力学模型的高计算成本和大量的设计变量，逆向设计的总成本可能会过高。基于MM的优化算法利用低保真度模型的速度来加速优化过程，但会参考高保真度模型以确保准确的解决方案。在这项工作中，将MM技术应用于每种应用中考虑的特性分布。特别是，在机翼逆向设计的情况下，压力系数分布通过MM技术建模，在机翼设计的情况下，采用截面升力分布模型。在6个翼型反设计案例和1个矩形机翼反设计案例中对所提出的方法进行了测试和评估。在具有八个设计变量参数的二维情况下，使用模式搜索进行直接的空气动力学逆向设计需要700至1200个高保真模型评估，这总共需要300至700个小时。基于MM的设计算法需要进行少于20次的高保真度仿真和1000至2000次的低保真度评估，这需要30至90个小时。在具有三个设计变量参数的三维情况下，直接的空气动力学逆向设计需要大约50个小时，而基于MM的设计需要大约6个小时。 （C）2018 Elsevier Masson SAS。版权所有。

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