This article summarizes and discusses recent developments with respect to artificial intelligence (AI) super-resolution as a subfilter model for large-eddy simulations. The focus is on the application of physics-informed enhanced super-resolution generative adversarial networks (PIESRGANs) for subfilter closure in turbulence and combustion applications. A priori and a posteriori results are presented for various applications, ranging from decaying turbulence to finite-rate chemistry flows. The high accuracy of AI super-resolution-based subfilter models is emphasized, and advantages and shortcoming are described.
CITATION STYLE
Bode, M. (2023). AI Super-Resolution: Application to Turbulence and Combustion. In Lecture Notes in Energy (Vol. 44, pp. 279–305). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-16248-0_10
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