Non-equilibrium kinetics of a microwave-assisted jet flame: Global model and comparison with experiment

Developing a systematic understanding of plasma driven chemical reaction pathways is difficult due to the stiffness and non-linear processes inherent with the involved physics. In the context of microwave-coupled plasmas within atmospheric pressure nozzle geometries, we have developed a kinetic global model (KGM) framework designed for quick exploration of parameter space. Our final goal is understanding key reaction pathways within non-equilibrium plasma assisted combustion (PAC), and their roles in the combustion process; of primary importance is the ability to determine possible system dependent reaction mechanism augmentation and specific reaction selectivity. In combination with a Boltzmann equation solver, kinetic plasma and gas-phase chemistry are coupled with a compressible gas flow model and solved with iterative feedback to match observed bulk conditions from experiments. We use a non-equilibrium electron energy distribution function (EEDF) to define electron-impact processes, allowing for demonstration of variation in reaction pathways due to changes in the EEDF shape. An Eulerian approach was developed as a purely steady-state flow model, followed by a Lagrangian time-dependent approach requiring knowledge of spatial electromagnetic field and flow profiles. Spatial profiles are converted into time-dependent envelopes affecting system parameters. The KGM is first applied to argon and air (N2-O2, N2-O2-Ar) systems as a means of assessing the soundness of the assumptions inherent in any global model. The simplified nature of the gas-phase chemistry and the availability of cross-sectional data reduce the sources of uncertainty in the model, which can be validated against the experimental measurements of electron density, emission spectrum and gas temperature. The test with air greatly increases the complexity by incorporating a plethora of excited states, providing new energy sink mechanisms (e.g. translational and vibrational excitation) and reaction pathw- ys. The KGM is then applied to plasma driven combustion mechanisms (e.g. H2 or CH4 with an oxidizer source), which increases the importance of flow treatment and the range of gas-phase chemistry time-scales. As the reaction mechanisms become more complex, the limits of available data will begin to hinder model physicality, requiring analytical and/or empirical treatment of gaps in data to maintain completeness of the reaction mechanisms. Due to the relative simplicity of simulations with global models, the KGM can also be used to provide a sensitivity analysis to errors and variations within available data.