A Systematic Adaptive Mesh Refinement Method for Large Eddy Simulation of Turbulent Flame Propagation

Abstract

This paper presents a feature-based Adaptive Mesh Refinement (AMR) method for Large Eddy Simulation of propagating deflagrations, using massive-scale parallel unstructured AMR libraries. The proposed method, named Turbulent Flame Propagation-AMR (TFP-AMR), is able to track the transient dynamics of both the turbulent flame and the vortical structures in the flow. To handle the interaction of the turbulent flame brush with the vortical structures of the flow, a vortex selection criterion is derived from flame/vortex interaction theory. The method is built with the general intent to prioritise conservatively estimated parameters, rather than to rely on user-dependent parameters. In particular, a specific mesh adaptation triggering strategy is constructed, adapted to the strongly transient physics found in deflagrations, to guarantee that the quantities of interest consistently reside within a region of high accuracy throughout the transient process. The methodology is applied and validated on several elementary cases representing fundamental bricks of the full problem: (1) a laminar flame propagation, (2) the advection of a pair of non-reacting vortices, (3) a flame/vortex interaction. The method is then applied to three different configurations of a three-dimensional complex explosion scenario in an obstructed chamber. All cases demonstrate the TFP-AMR capability to recover accurate results at reduced computational cost without requiring any ad hoc tuning of the AMR method or its parameters, thus demonstrating its genericity and robustness.