This paper proposes a novel adaptive design of experiment (ADoE) framework with cost-aware sampling strategy and nonstationary surrogate model for efficient wind tunnel testing. The ADoE framework, which is based on the Gaussian process, can effectively reduce the required number of an experiment while maintaining its accuracy. The proposed cost-aware sampling strategy augments the framework by selecting cost-efficient experiment points and the nonstationary surrogate model effectively reflects the nonlinearity of the system on the response surface model. The efficacy of the proposed framework has been validated through a virtual experiment using an actual high angle-of-attack wind tunnel test dataset, which is highly nonlinear.

中文翻译：

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风洞试验非平稳代理模型实验的成本意识自适应设计

本文提出了一种新颖的自适应实验设计 (ADoE) 框架，该框架具有成本感知采样策略和非平稳代理模型，用于高效风洞测试。基于高斯过程的 ADoE 框架可以有效减少所需的实验次数，同时保持其准确性。所提出的成本感知采样策略通过选择具有成本效益的实验点来增强框架，非平稳代理模型有效地反映了响应面模型上系统的非线性。所提出框架的有效性已通过使用高度非线性的实际高迎角风洞测试数据集的虚拟实验得到验证。