Large-eddy simulation/probability density function modeling of a pre-chamber turbulent jet ignition

To circumvent the adverse effects of climate change and to achieve net zero emissions by the year 2050, it is essential to have a steady progress towards reducing the carbon footprints. Turbulent Jet Ignition (TJI) is an innovation in which the spark plug of a spark-ignited combustion engine is replaced by a small volume pre-chamber to produce a high-temperature jet causing main-chamber ignition. TJI enables more robust lean combustion and thereby increases fuel efficiency. In this study, computational fluid dynamics simulations of an experimental TJI rig are conducted by using the combined Large-Eddy Simulation (LES) and transported Probability Density Function (PDF) method to assess the model's predictive capability for the relevant lean premixed combustion regime. A consistent Eulerian Monte-Carlo Fields (EMCF) approach is used to approximate the multi-dimensional transported PDF equation. A machine learning assisted mixing model is employed for the micro-mixing process in the stochastic differential equations. The predicted pre-chamber flame propagation and the lean main-chamber ignition is validated by using the available experiments data.