Conditional Source-term Estimation (CSE) is a combustion model based on the conditional moment hypothesis where transport equations for reactive species are conditionally averaged on conserved scalars. Major advantages of this strategy are the reduced spatial dependence of the conditional averages and negligible fluctuations around the conditional averages, which considerably simplify the reaction rate closure. Historically, simulations using CSE are limited to low carbon fuels (i.e. methane and hydrogen) where the reduced chemistry manifold can be constructed through techniques including intrinsic low dimensional manifolds and trajectory generated manifolds. However, the use of such strategies to create manifolds for diesel surrogates has proven problematic.

In this study, the potential of a combination of an unsteady Flamelet Generated Manifold (FGM) and the Conditional Source-term Estimation approach to predict the ignition and flame propagation on an autoigniting n-dodecane spray flame is assessed. Simulations are performed on a single-hole injection of n-dodecane under a wide range of Engine Combustion Network’s “Spray A” conditions within a Reynolds-averaged Navier-Stokes (RANS) framework. Results from parametric sweeps of ambient temperature and oxygen concentration are qualitatively validated against experimental data from the literature and compared against predictions from an industry standard well-stirred reactor model. The efficacy of the CSE-FGM RANS approach in predicting flame characteristics is evaluated and further compared with high fidelity CSE-FGM simulations using the Large Eddy Simulation (LES) turbulence model.

Overall, it was found that the CSE-FGM RANS model was able to capture global flame properties — showing particular strength in predicting auto-ignition events in the low temperature region. The model was also able to satisfactorily capture details of the two-stage ignition process. The results were shown to be consistent with those of the CSE-FGM LES model, demonstrating the adaptability of the CSE-FGM approach to different turbulence modelling paradigms.

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