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CFD and FE tools are intensively adopted by engine manufacturers in order to prevent thermo-mechanical failures reducing time- and cost-to market. The capability to predict correctly the physical factors leading to damages is hence essential for their application in the industrial practice. This is even more important for last generation SI engines, where the more and more stringent need to lower fuel consumption and pollutant emissions is pushing designers to reduce engine displacement in favor of higher specific power, usually obtained by means of turbocharging. This brings to a new generation of SI engines characterized by higher and higher adiabatic efficiency and thermo-mechanical loads. A recent research highlighted the different behavior of the thermal boundary layer of such engines operated at high revving speeds and high loads if compared to the same engines operated at low loads and revving speeds or even engines with a lower specific power.

Recently, a growing interest in the development of more accurate phenomenological turbulence models is observed, since this is a key pre-requisite to properly describe the burn rate in quasi-dimensional combustion models. The latter are increasingly utilized to predict engine performance in very different operating conditions, also including unconventional valve control strategies, such as EIVC or LIVC. Therefore, a reliable phenomenological turbulence model should be able to physically relate the actuated valve strategy to turbulence level during the engine cycle, with particular care in the angular phase when the combustion takes place.

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).

The paper reports a wide numerical analysis of the well-known “Darmstadt engine” operated under motored condition. The engine, which features multiple optical accesses and is representative of currently made four-valve pentroof GDI production engines, is simulated using computational grids of increasing density and two widely adopted approaches to model turbulence, Reynolds Averaged Navier Stokes (RANS) and Large Eddy Simulation (LES). In the first part of the paper, attention is focused on the increase of grid density within the RANS modelling framework: both bulk-flow grid density and near-wall grid density are varied in order to analyse potentials and limitations of the different grid strategies and evaluate the trade-off between accuracy and computational cost.

Hybrid URANS/LES turbulence modeling is rapidly emerging as a valuable complement to standard LES for full-engine multi-cycle simulation. Among the available approaches, zonal hybrids are potentially attractive due to the possibility of clearly identify URANS and LES zones, eventually introducing further zone types with dynamically switching behavior. The present work aims at evaluating the impact of different zonal configurations on the simulated flow statistics using the well-assessed TCC-III experimental engine setup. More specifically, different methods (URANS, LES or seamless DES) are applied inside the cylinder volume, as well as into the intake/exhaust ports and plenums. For each of the five tested configurations, in-cylinder flow features are compared against the reference TCC-III experimental measurements, in terms of velocity field statistics and quality indices.