Application of a multi-zone model for the prediction of species concentrations in rapid compression machine experiments

A multi-zone model for simulating rapid compression machine (RCM) experiments is integrated with a chemistry solver for robust, computationally-efficient speciation predictions. The model builds upon previous work (Goldsborough et al., 2012) by simulating chemical kinetics in each temperature-varying main combustion chamber zone. The accuracies of the model predictions are evaluated by a comparison to results from computational fluid dynamics (CFD) simulations. The present model is shown to yield significant improvement over a homogeneous modeling approach in predicting chemical species mole fractions, as well as accurate predictions of temperature and pressure. Species mole fractions predicted by the present model are on average within ∼15% of CFD predictions, while the difference in predicted mole fractions between a homogeneous model and CFD are ∼90% on average. The improvement in species predictions is due to the fact that the present model simulates chemical reaction throughout the entire main reaction chamber in an RCM, while the homogeneous model utilizes a reactor model that simulates conditions inside the core of the reaction chamber only. The enhanced model will enable direct comparison to cylinder-averaged experimental speciation data that is obtained by expanding a reactive mixture to quench the reaction.