Multi‐fidelity surrogate reduced‐order modeling of steady flow estimation,International Journal for Numerical Methods in Fluids

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Multi‐fidelity surrogate reduced‐order modeling of steady flow estimation
International Journal for Numerical Methods in Fluids ( IF 1.7 ) Pub Date : 2020-05-10 , DOI: 10.1002/fld.4850
Xu Wang ₁ , Jiaqing Kou ₁ , Weiwei Zhang ₁

Affiliation

A multi‐fidelity reduced‐order model (ROM), which incorporates low‐fidelity data to improve the prediction of high‐fidelity results, is proposed for the reconstruction of steady flow field at different conditions. The spatial basis functions of low‐fidelity and high‐fidelity data, which are generated for all training sets are extracted separately by proper orthogonal decomposition. Then a surrogate model is used to construct mappings between the mode coefficients obtained from low‐fidelity and the high‐fidelity data. In the online stage, both the low‐fidelity flow at the predicted state and the surrogate model are needed to predict the mode coefficients of the high‐fidelity flow, and the high‐fidelity flow field is subsequently reconstructed. This method differs from existing surrogate‐based reduced‐order modeling method because it allows the use of partial physical information for flow estimation, which is coming from the low‐fidelity data instead of adopting a black‐box mapping between system state and the projection coefficients. Numerical studies are presented for a lid‐driven cavity problem and transonic flow past a NACA0012 airfoil. Two low‐fidelity models, with either a coarse mesh or a lower numerical order, are considered respectively. Results show that the proposed multi‐fidelity ROM predicts the flow field accurately and outperforms the traditional methods in both interpolated and extrapolated conditions.

中文翻译：

多保真替代品稳定流估计的降阶建模

提出了一种融合低保真度数据以提高对高保真度结果的预测的多保真度降阶模型（ROM），用于在不同条件下重建稳态流场。通过适当的正交分解分别提取针对所有训练集生成的低保真和高保真数据的空间基础函数。然后使用替代模型来构造从低保真度数据获得的模态系数与高保真度数据之间的映射。在在线阶段，既需要预测状态下的低保真流，也需要代理模型来预测高保真流的众数系数，然后重建高保真流场。此方法与现有的基于代理的降阶建模方法不同，因为它允许使用部分物理信息进行流量估算，该信息来自低保真度数据，而不是在系统状态与投影系数之间采用黑盒映射。提出了关于盖驱动腔问题和通过NACA0012翼型的跨音速流动的数值研究。分别考虑了两个低保真度模型，它们具有粗糙的网格或较低的数值顺序。结果表明，所提出的多保真ROM在插值和外推条件下都能准确地预测流场，并且优于传统方法。它来自低保真度数据，而不是在系统状态和投影系数之间采用黑盒映射。提出了关于盖驱动腔问题和通过NACA0012翼型的跨音速流动的数值研究。分别考虑了两个低保真度模型，它们具有粗糙的网格或较低的数值顺序。结果表明，所提出的多保真ROM在插值和外推条件下都能准确地预测流场，并且优于传统方法。它来自低保真度数据，而不是在系统状态和投影系数之间采用黑盒映射。提出了关于盖驱动腔问题和通过NACA0012翼型的跨音速流动的数值研究。分别考虑了两个低保真度模型，它们具有粗糙的网格或较低的数值顺序。结果表明，所提出的多保真ROM在插值和外推条件下都能准确地预测流场，并且优于传统方法。

更新日期：2020-05-10

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