Oct 19, 2021 · The more accurate the closure relation, the stronger the simulation approaches kinetic-based results. In this paper, new closure terms are ...
Mar 24, 2022 · In this paper, new closure terms are constructed using machine learning techniques. Two different machine learning models, a multi-layer ...
In this paper, we propose different closure terms extracted using machine learning techniques as an alternative. We show in this work how two different machine ...
We show in this work how two different machine learning models, a multi-layer perceptron and a gradient boosting regressor, can synthesize higher-order moments ...
Mar 24, 2022 · Simulations of large-scale plasma systems are typically based on a fluid approximation approach. These models construct a moment-based ...
In this study, we present a learning framework based on neural networks that exploits rotational symmetries in the closure terms to learn accurate closure ...
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Jamal, and G. Lapenta, "Identification of high order closure terms from fully kinetic simulations using machine learning", Physics of Plasmas 29, 032706 (2022).
PDF-like approaches are designed to directly evaluate the closure terms associated with the nonlinear chemical source terms in the energy and species equations.
In this paper, we take a data-driven approach and apply machine learning to the moment closure problem for the radiative transfer equation in slab geometry.
[PDF] Learning fast, accurate, and stable closures of a kinetic theory of ... - arXiv
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Aug 13, 2023 · require closure assumptions to model unrepresented higher-order moments. In this study, we present a learning framework based on neural ...