Optimization of the Numerical Spray Modeling for Polyoxymethylene Dimethyl Ethers for Combustion Prediction in CONVERGE

Different approaches are undertaken to mitigate the impact of the transport sector on climate change. Alongside electrifying powertrains, sustainable e-fuels such as polyoxymethylene dimethyl ethers (OME) are considered a promising bridging technology for different applications. However, this requires that the engines are optimized for the new fuels. Accordingly, this study aims to optimize the numerical spray modeling of OME in CONVERGE. Based on the KH–RT break-up model, the spray simulations of three different commercial injectors for heavy-duty applications are analyzed regarding the predictability of the liquid and gaseous penetration lengths and the total simulation time. A sensitivity analysis is conducted for the turbulence model, mesh size, and spray parameters prior to optimizing the spray model and validating it with experimental results. While each parameter individually influences the different phases of the injection event, the sensitivity analysis reveals that the break-up time constant B₁ has overall the most significant impact on the penetration length. Additionally, the standard k-ε model demonstrated the best alignment for turbulence modeling. The computational time was reduced by optimizing the parcel count and grid size while achieving a further optimized grid size with finer maximum size and coarser minimum size for use in the full-engine combustion model. The optimization reduced the RMSE for the liquid penetration length (LPL) and gaseous penetration length (GPL) by 75% to 1.01 mm and 1.26 mm, respectively. The validation with experimental data shows that the resulting model can be used in qualitative design optimization regarding injection pressure, counter pressure, and nozzle hole diameter with an overall RMSE for the penetration length around 2 mm.