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Hyperbolic Machine Learning Moment Closures for the BGK Equations
This closure is motivated by the exact closure for the free streaming limit that we derived in our paper on closures in transport \cite{Huang2022-RTE1}.
Machine learning moment closure models for the radiative transfer equation III: enforcing hyperbolicity and physical characteristic speeds
In our second paper \cite{huang2021hyperbolic}, we identified a symmetrizer which leads to conditions that enforce that the gradient based ML closure is symmetrizable hyperbolic and stable over long time.
Machine learning moment closure models for the radiative transfer equation II: enforcing global hyperbolicity in gradient based closures
This is the second paper in a series in which we develop machine learning (ML) moment closure models for the radiative transfer equation (RTE).
Machine learning moment closure models for the radiative transfer equation I: directly learning a gradient based closure
In this paper, we take a data-driven approach and apply machine learning to the moment closure problem for radiative transfer equation in slab geometry.
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