Reduced order modeling of fluid flows: Machine learning, Kolmogorov barrier, closure modeling, and partitioning

28 May 2020 Shady Ahmed Suraj Pawar Omer San Adil Rasheed

In this paper, we put forth a long short-term memory (LSTM) nudging framework for the enhancement of reduced order models (ROMs) of fluid flows utilizing noisy measurements. We build on the fact that in a realistic application, there are uncertainties in initial conditions, boundary conditions, model parameters, and/or field measurements... (read more)

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