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arXiv 2201.03200physics.flu-dyncs.LG

Predictions of Reynolds and Nusselt numbers in turbulent convection using machine-learning models

Technische Universität Ilmenau(伊尔梅瑙工业大学);Indian Institute of Technology Kanpur(印度理工学院坎普尔分校)

Shashwat Bhattacharya, Mahendra K Verma, Arnab Bhattacharya

英文摘要:

In this paper, we develop a multivariate regression model and a neural network model to predict the Reynolds number (Re) and Nusselt number in turbulent thermal convection. We compare their predictions with those of earlier models of convection: Grossmann-Lohse~[Phys. Rev. Lett. \textbf{86}, 3316 (2001)], revised Grossmann-Lohse~[Phys. Fluids \textbf{33}, 015113 (2021)], and Pandey-Verma [Phys. Rev. E \textbf{94}, 053106 (2016)] models. We observe that although the predictions of all the models are quite close to each other, the machine learning models developed in this work provide the best match with the experimental and numerical results.

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