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Metamodels for aerothermodynamic design optimization of hypersonic spiked blunt bodies

机译：高超声速尖刺钝体气动热力学设计优化的元模型

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The use of spikes in the design of hypersonic vehicles yields a considerable reduction in drag and aerodynamic heating. However, their effectiveness relies strongly on the parameters of the actual designs. In this work, surrogates generated from high fidelity models are used in the context of design optimization of a spiked blunt body in hypersonic flow conditions. Four different surrogate models including a quadratic response surface and three Kriging surrogates were constructed based on the values of drag and maximum temperature responses. The evolutionary genetic algorithm is applied to find the optimum design based on each of the surrogates for these two objectives. The structure of the various surrogate models was investigated and the main differences were addressed. For the cases investigated in this work, the Kriging surrogate based on exponential correlations produced a relatively better overall performance. It was concluded that, instead of adding more training samples, eliminating some samples that show undesired aerodynamic performance yield a remarkable improvement in surrogates' performance. The optimized designs produced 92% and 13% reduction in drag and wall temperature responses, respectively.
机译：在超音速飞行器的设计中使用尖钉会大大降低阻力和空气动力加热。但是，它们的有效性在很大程度上取决于实际设计的参数。在这项工作中，在高超声速流动条件下，对尖刺钝体进行设计优化时，会使用高保真模型生成的替代物。根据阻力和最大温度响应的值，构建了四个不同的替代模型，包括二次响应曲面和三个Kriging替代。应用进化遗传算法基于这两个目标的每个替代物找到最佳设计。研究了各种替代模型的结构，并解决了主要差异。对于这项工作中调查的案例，基于指数相关性的Kriging替代产生了相对较好的整体性能。结论是，代替添加更多的训练样本，消除一些显示出不良空气动力学性能的样本，可以显着提高代理人的性能。经过优化的设计使阻力和壁温响应分别降低了92％和13％。

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