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Since the mechanisms leading to cyclic combustion variabilities in direct injection gasoline engines are still poorly understood, advanced computational studies are necessary to be able to predict, analyze and optimize the complete engine process from aerodynamics to mixing, ignition, combustion and heat transfer. In this work the Scale-Adaptive Simulation (SAS) turbulence model is used in combination with a parameterized lagrangian spray model for the purpose of predicting transient in-cylinder cold flow, injection and mixture formation in a gasoline engine. An existing CFD model based on FLUENT v15.0 [1] has been extended with a spray description using the FLUENT Discrete Phase Model (DPM). This article will first discuss the validation of the in-cylinder cold flow model using experimental data measured within an optically accessible engine by High Speed Particle Image Velocimetry (HS-PIV).

The world of shipping is at a turning point. Alongside methanol, ammonia and other PtL (Power to Liquid) fuels, liquefied natural gas (LNG) offers one way of achieving climate-friendly ship operation. Although currently still derived from fossil sources, LNG combines the properties of already having a well-established land-based infrastructure, of enabling a 100 % climate-neutral supply via electrolysis and methanization, and of its ability for any high proportion of climate-neutral LNG to be used as a drop-in fuel during the transformation process in the next decades; proven by the first bunkering of the container vessel “ElbBlue” with 20 tons of SNG (Synthetic Natural Gas) in 2021 [1]. Up to now, LNG fueled marine engines have predominantly been operated in fixed operation areas. Therefore, they can bunker stable gas qualities at specific ports and can be optimized for a specific gas quality.