Abstract
A dynamic adaptive combustion modeling framework based on chemical explosive mode analysis (CEMA) is proposed to account for different flame features such as local auto-ignition, premixed and non-premixed flamelets in diesel spray flames. The proposed modeling strategy is achieved by assigning zone-dependent combustion models on-the-fly to different flame zones segmented using a CEMA-based approach. An approximate CEMA formulation is developed to approximate the eigenvalue of the chemical explosive mode with high computational efficiency in three-dimensional (3-D) turbulent flame simulations. The utility of the CEMA-based criterion for dynamic flame segmentation is first demonstrated using CEMA-based adaptive chemistry by applying different reduced chemistry to different flame zones. The capability of the dynamic adaptive combustion modeling strategy is then demonstrated in large eddy simulations (LES) of turbulent lifted n-dodecane spray flames. Specifically, inert mixing is used for chemically inactive zones, and the well-mixed combustion model with finite rate chemistry is applied in the pre-ignition zone to capture the two-stage ignition as well as premixed reaction fronts. Adaptive mesh refinement (AMR) is further adopted near the premixed reaction fronts to capture the local flame structure and flame propagation speed. For the post-ignition zone, a recently developed tabulated flamelet model (TFM) is applied and compared with the flamelet progress variable (FPV) method. It is shown that CEMA-based adaptive chemistry induces small errors to the statistically-averaged flame structures, as CEMA is an effective and robust approach for on-the-fly flame segmentation. It is further seen that the CEMA-based adaptive modeling strategy more accurately predicts the ignition delay time and flame lift-off length compared with the low-cost flamelet models such as TFM and FPV, while the computational cost is substantially lower compared with the well-mixed combustion model using finite rate chemistry.
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