In-Situ Adaptive Manifolds for Soot and Emissions Predictions in Turbulent Reacting Flows

Manifold-based combustion models reduce the computational cost of turbulent reacting flow simulations by projecting the thermochemical state onto a low-dimensional manifold, which can be computed separately from the flow solver. Traditionally, the model is pretabulated by precomputing solutions to a set of manifold equations. For soot and emissions, additional dimensions are required to account for heat losses, so these pretabulated databases can become very memory intensive, and many of the states may not even be accessed. In-Situ Adaptive Manifolds (ISAM) has recently been developed, in which necessary manifold solutions are computed on-the-fly and stored for reuse with In-Situ Adaptive Tabulation (ISAT). In this work, ISAM is coupled to a soot model based on the Hybrid Method of Moments (HMOM), and a new approach for incorporating heat losses into ISAM has been developed. The model is demonstrated and validated against the Sandia Sooting Flame. The computational efficiency of the sooting ISAM framework will be discussed.