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Found 4 papers, 0 papers with code
Transfer learning for predicting source terms of principal component transport in chemically reactive flow
The performance of the reduced-order model with a sparse dataset is found to be remarkably enhanced if the training of the ANN model is restricted by a regularization term that controls the degree of knowledge transfer from source to target tasks.
A Framework for Combustion Chemistry Acceleration with DeepONets
A combustion chemistry acceleration scheme is developed based on deep operator networks (DeepONets).
Generalized Joint Probability Density Function Formulation inTurbulent Combustion using DeepONet
The DeepONet is a machine learning model that is parameterized on the unconditional means of PCs at a given spatial location and discrete PC coordinates and predicts the joint probability density value for the corresponding PC coordinate.
An Efficient Machine-Learning Approach for PDF Tabulation in Turbulent Combustion Closure
In this work, we address these issues by introducing an adaptive training algorithm that relies on multi-layer perception (MLP) neural networks for regression and self-organizing maps (SOMs) for clustering data to tabulate using different networks.
