Flamelet Generated Manifold

Flamelet Generated Manifolds (FGMs) are a technique used to simplify the computationally expensive task of modeling turbulent combustion by representing complex chemical reactions on low-dimensional manifolds. Current research focuses on improving the accuracy and efficiency of FGM methods, often employing deep neural networks and ensemble methods to learn the manifold representation and perform efficient lookups during simulations. This approach offers significant potential for accelerating simulations of turbulent combustion, impacting fields like engine design and climate modeling by enabling more detailed and accurate predictions.