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The accurate representation of Internal Combustion Engine (ICE) flows via CFD is an extremely complex task: it strongly depends on a combination of highly impacting factors, such as grid resolution (both local and global), choice of the turbulence model, numeric schemes and mesh motion technique. A well-founded choice must be made in order to avoid excessive computational cost and numerical difficulties arising from the combination of fine computational grids, high-order numeric schemes and geometrical complexity typical of ICEs. The paper focuses on the comparison between different mesh motion technologies, namely layer addition and removal, morphing/remapping and overset grids. Different grid strategies for a chosen mesh motion technology are also discussed. The performance of each mesh technology and grid strategy is evaluated in terms of accuracy and computational efficiency (stability, scalability, robustness).

Fuel deposits in DISI engines promote unburnt hydrocarbon and soot formation: due to the increasingly stringent emission regulations (EU6 and forthcoming), it is necessary to deeply analyze and well-understand the complex physical mechanisms promoting fuel deposit formation. The task is not trivial, due to the coexistence of mutually interacting factors, such as complex moving geometries, influencing both impact angle and velocity, and time-dependent wall temperatures. The experimental characterization of actual engine conditions on transparent combustion chambers is limited to highly specialized research laboratories; therefore, 3D-CFD simulations can be a fundamental tool to investigate and understand the complex interplay of all the mentioned factors. The aim is pursued in this study by means of full-cycle simulations accounting for instantaneous fuel/piston thermal interaction and actual fuel characteristics.

After-treatment sensors are used in the ECU feedback control to calibrate the engine operating parameters. Due to their contact with exhaust gases, especially NOx sensors are prone to soot deposition with a consequent decay of their performance. Several phenomena occur at the same time leading to sensor contamination: thermophoresis, unburnt hydrocarbons condensation and eddy diffusion of submicron particles. Conversely, soot combustion and shear forces may act in reducing soot deposition. This study proposes a predictive 3D-CFD model for the analysis of the development of soot deposition layer on the sensor surfaces. Alongside with the implementation of deposit and removal mechanisms, the effects on both thermal properties and shape of the surfaces are taken in account. The latter leads to obtain a more accurate and complete modelling of the phenomenon influencing the sensor overall performance.