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Accurate predictions of in-cylinder heat transfer processes of internal combustion engines (ICEs) require a comprehensive understanding of the boundary layer development in the near-wall region (NWR). To add to the understanding of this NWR, this study uses experimental data of near-wall measurements collected in the transparent combustion chamber (TCC-III) engine via Particle Image Velocimetry (PIV) and toluene Planar Laser Induced Fluorescence (PLIF) thermometry. These near-wall flow and temperature distributions were compared with large-eddy simulations (LES) and 3-D conjugate heat transfer (CHT) modeling with a commercial CFD code (CONVERGE). The implementation of the conjugate heat transfer model enables capturing the variability in wall heat transfer as observed in the measurements.

Large-eddy simulations (LES) of a motoring single-cylinder engine with transparent combustion chamber (TCC-II) are carried out using a commercially available computer code, CONVERGE. Numerical predictions are compared with high-speed particle image velocimetry (PIV) measurements. Predictions of two spatial discretization schemes, namely, numerically stabilized central difference scheme (CDS) and fully upwind scheme are compared. Four different subgrid scale (SGS) models; a non-eddy viscosity dynamic structure turbulence (DST) model of Pomraning and Rutland, one-equation eddy-viscosity (1-Eqn) model of Menon et al., a zeroequation eddy-viscosity model of Vreman, and the zeroequation standard Smagorinsky model are employed on two different grid configurations. Additionally, simulations are also performed by deactivating the LES SGS models. It is found that the predictions when using the numerically stabilized CDS are significantly better than using the fully upwind scheme.

Near-term energy policy for ground transportation is likely to have a strong focus on both gains in efficiency as well as the use of alternate fuels; as both can reduce crude oil dependence and carbon loading on the environment. Stratified-charge spark-ignition direct-injection (SIDI) engines are capable of achieving significant gains in efficiency. In addition, these engines are likely to be run on alternative fuels. Specifically, lower alcohols such as ethanol and iso-butanol, which can be produced from renewable sources. SIDI engines, particularly the spray-guided variant, tend to be very sensitive to mixture preparation since fuel injection and ignition occur within a short time of each other. This close spacing is necessary to form a flammable mixture near the spark plug while maintaining an overall lean state in the combustion chamber. As a result, the physical properties of the fuel have a large effect on this process.

Simultaneous two-component measurements of gas velocity and multi-dimensional numerical simulation are employed to characterize the evolution of the in-cylinder turbulent flow structure in a re-entrant bowl-in-piston engine under motored operation. The evolution of the mean flow field, turbulence energy, turbulent length scales, and the various terms contributing to the production of the turbulence energy are correlated and compared, with the objectives of clarifying the physical mechanisms and flow structures that dominate the turbulence production and of identifying the source of discrepancies between the measured and simulated turbulence fields. Additionally, the applicability of the linear turbulent stress modeling hypothesis employed in the k-ε model is assessed using the experimental mean flow gradients, turbulence energy, and length scales.

In previous work, Reuss [1] studied the cycle-to-cycle variation in the large-scale velocity structures of high and low-swirl in-cylinder flows of an IC engine. The vector flow fields were obtained from PIV measurements in a two-valve, pancake-shaped, Transparent Combustion Chamber (TCC) engine. In this study, the Reynolds-decomposed turbulence properties such as kinetic energy, length scales, and dissipation rate were directly measured for the two cases. The results demonstrate that, at TDC compression, the low-swirl flow is dominated by turbulence at the largest scales, whereas the high-swirl flow has a considerably lower turbulence Reynolds number. The dissipation rate and length scale calculated from mixing-length theory greatly exceeded the dissipation computed from the 2-D velocity-gradients and integral-length scales computed from the autocorrelation, respectively.