Machine Learning and Its Application to Reacting Flows : ML and Combustion

Introduction.- ML Algorithms, Techniques and their Application to Reactive Molecular Dynamics Simulations.- Big Data Analysis, Analytics & ML role.- ML for SGS Turbulence (including scalar flux) Closures.- ML for Combustion Chemistry.- Applying CNNs to model SGS flame wrinkling in thickened flame LES (TFLES).- Machine Learning Strategy for Subgrid Modelling of Turbulent Combustion using Linear Eddy Mixing based Tabulation.- MILD Combustion-Joint SGS FDF.- Machine Learning for Principal Component Analysis & Transport.- Super Resolution Neural Network for Turbulent non-premixed Combustion.- ML in Thermoacoustics.- Concluding Remarks & Outlook.