2022
DOI: 10.48550/arxiv.2202.05122
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Ensemble Kalman method for learning turbulence models from indirect observation data

Xin-Lei Zhang,
Heng Xiao,
Xiaodong Luo
et al.

Abstract: In this work, we propose using an ensemble Kalman method to learn a nonlinear eddy viscosity model, represented as a tensor basis neural network, from velocity data. Datadriven turbulence models have emerged as a promising alternative to traditional models for providing closure mapping from the mean velocities to Reynolds stresses. Most datadriven models in this category need full-field Reynolds stress data for training, which not only places stringent demand on the data generation but also makes the trained m… Show more

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