Neural-ISAM hybridizes in-situ adaptive tabulation with on-the-fly neural network training to prune manifold databases, lowering memory for complex combustion models in LES of Sandia flames.
Local quenching due to flame stretch and non-premixed turbulent combustion.Combustion Science and Technology, 30(1-6):1–17
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Neural-ISAM: A hybrid in-situ machine learning approach for complex manifold-based combustion models in LES of turbulent flames
Neural-ISAM hybridizes in-situ adaptive tabulation with on-the-fly neural network training to prune manifold databases, lowering memory for complex combustion models in LES of Sandia flames.