The maritime sector aims to achieve short and medium-term sustainability targets through the conversion of Internal Combustion Engines to methanol operation. For small to medium sized engines, Port Fuel Injection (PFI) is the most viable injection method to achieve this conversion. However, the knowledge of the behaviour of methanol in combustion engines, particularly its spray characteristics under PFI conditions, is limited. To better understand liquid methanol sprays, this paper studies the injection of methanol in marine PFI conditions through Computational Fluid Dynamics (CFD) modelling. The CFD models use the Lagrangian-Eulerian (LE) coupling method within the Reynolds Averaged Navier Stokes (RANS) turbulence framework. Numerical results were validated using dedicated methanol experiments from the literature for both high and low injection pressures. Subsequently, this predictive CFD framework was used in a number of different injection pressures with scaled injection quantities that represent marine applications. Moreover, we demonstrated that high injection pressure improves atomisation and, thus, evaporation prior to wall impingement. This work strongly contributes to our understanding of marine PFI methanol engines by modelling fuel quantities relevant for ship applications. Our approach can be implemented in full engine simulations to solve evaporation challenges often found in small-bore methanol marine engines.

To reduce emissions, methanol is a favorable carbon-neutrally-producible alternative fuel, which can substitute gasoline in direct-injection spark-ignition (DISI) engines. Robust DISI engine operation relies on a consistent air-fuel mixture. To understand the physical processes that characterize the mixture formation, predictive computational fluid dynamics (CFD) simulations are used to improve the understanding, operation, and emissions of these engines. However, using an alternative fuel such as methanol often poses challenges to the CFD simulations’ validity due to the alteration of the fuel properties. This study presents the validation of a CFD modeling approach that can be applied to the predictive modeling of DISI methanol engines. Our methodology uses Lagrangian-Eulerian methods to model the methanol eight-hole counter-bore style Spray M injector from the Engine Combustion Network (ECN). We used the Spray M1 condition, which represents a late-injection spray under a high ambient pressure and temperature environment. For the present study, we employed both a Reynolds Averaged Navier Stokes (RANS) and a Large Eddy Simulation (LES) turbulence approach in CONVERGE-CFD. To validate our models, we used the projected liquid volume (PLV) maps generated by the tomographic liquid volume fraction (LVF) based on methanol. Subsequently, we tuned our models based on the corresponding numerical predictions of the liquid penetration and LVF distributions. The results demonstrated that both the RANS and LES models could replicate the spray morphology and liquid length. While the RANS model was unable to fully capture the complex phenomena of spray collapse and sweeping in the methanol multi-hole spray, the LES model effectively reproduced these behaviors without excessive tuning effort.