In this paper, we compare the capabilities of two open source near-wall-modeled large eddy simulation (NWM-LES) approaches regarding prediction accuracy, computational costs and ease of use to predict complex turbulent flows relevant to internal combustion (IC) engines. The applied open source tools are the commonly used OpenFOAM, based on the finite volume method (FVM), and OpenLB, an implementation of the lattice Boltzmann method (LBM). The near-wall region is modeled by the Musker equation coupled to a van Driest damped Smagorinsky-Lilly sub-grid scale model to decrease the required mesh resolution. The results of both frameworks are compared to a stationary engine flow bench experiment by means of particle image velocimetry (PIV). The validation covers a detailed error analysis using time-averaged and root mean square (RMS) velocity fields. Grid studies are performed to examine the performance of the two solvers. In addition, the differences in the processes of grid generation are highlighted. The performance results show that the OpenLB approach is on average 32 times faster than the OpenFOAM implementation for the tested configurations. This indicates the potential of LBM for the simulation of IC engine-relevant complex turbulent flows using NWM-LES with computationally economic costs.

In this work, entropy generation analysis is applied to characterize and optimize a turbulent impinging jet on a heated solid surface. In particular, the influence of plate inclinations and Reynolds numbers on the turbulent heat and fluid flow properties and its impact on the thermodynamic performance of such flow arrangements are numerically investigated. For this purpose, novel model equations are derived in the frame of Large Eddy Simulation (LES) that allows calculation of local entropy generation rates in a post-processing phase including the effect of unresolved subgrid-scale irreversibilities. From this LES-based study, distinctive features of heat and flow dynamics of the impinging fluid are detected and optimal operating designs for jet impingement cooling are identified. It turned out that (1) the location of the stagnation point and that of the maximal Nusselt number differ in the case of plate inclination; (2) predominantly the impinged wall acts as a strong source of irreversibility; and (3) a flow arrangement with a jet impinging normally on the heated surface allows the most efficient use of energy which is associated with lowest exergy lost. Furthermore, it is found that increasing the Reynolds number intensifies the heat transfer and upgrades the second law efficiency of such thermal systems. Thereby, the thermal efficiency enhancement can overwhelm the frictional exergy loss.

The quantification of the prediction accuracy in large eddy simulations (LES) is very challenging due to various interacting errors associated with this approach. When dealing with errors in LES using implicit filtering, numerical and modeling errors have drawn the interest of many researchers. Little attention has been paid to other sources of discrepancies between LES results and reference data, namely sampling errors, influence of the initial conditions, improper boundary conditions or uncertainties issuing from reference data. A framework of metrics that includes all these issues is addressed in the present paper to study subgrid-scale (SGS) models for LES and to quantify their prediction accuracy and computational costs. The method is applied to a simple wall-bounded turbulent flow at moderate Reynolds number. It turns out from the results obtained with six commonly used SGS models that wall-adapting models (WALE and SIGMA) and localized dynamic models reproduce the physics of the flow field more faithfully, reveal a superior prediction accuracy and have a similar computational cost than models using van Driest wall damping. Especially at the viscous wall region (\(r^+<50\)), wall-adapting and localized dynamic models are more accurate, reflecting the proper near wall behavior of such models. Relying on the analysis of sources of various errors, uncertainties in LES are estimated and systematically assessed, and their influence on simulation results is quantified. Finally, engineering estimations of the required averaging time to obtain basic estimates of statistical quantities with a predetermined degree of accuracy are suggested.

In this work, near-wall thermal transport processes and entropy generation mechanisms in a turbulent jet impinging on a ${45}^{\circ }$ -inclined heated surface are investigated using a direct numerical simulation (DNS). The objectives are to analyze the subtle mechanisms of heat transport in the vicinity of an inclined impinged wall, to determine the causes of irreversibilities that are responsible for the reduction of performance of impingement cooling applications and to provide a comprehensive dataset for model development and validation. Results for near-wall thermal characteristics including heat fluxes are analyzed. An entropy production map is provided from the second law analysis. The following main outcomes can be drawn from this study: (1) the location of peak heat transfer occurs not directly at the stagnation point; instead, it is slightly shifted towards the compression side of the jet, while at this region, the heat is transported counter to the temperature gradient; (2) turbulent thermal and fluid flow transport processes around the stagnation point are considerably different from those found in other near-wall-dominated flows and are strongly non-equilibrium in nature; (3) heat fluxes appear highly anisotropic especially in the vicinity of the impinged wall; (4) in particular, the heated wall acts as a strong source of irreversibility for both entropy production related to viscous dissipation and to heat conduction. All these findings imply that a careful design of the impinged plate is particularly important in order to use energy in such a thermal arrangement effectively. Finally, this study confirms that the estimation of the turbulent part of the entropy production based on turbulence dissipation rates in non-reacting, non-isothermal fluid flows represents a reliable approximate approach within the second law analysis, likewise in the context of computationally less expensive simulation techniques like RANS and/or LES.

Apart from electric vehicles, most internal combustion (IC) engines are powered while burning petroleum-based fossil or alternative fuels after mixing with inducted air. Thereby the operations of mixing and combustion evolve in a turbulent flow environment created during the intake phase and then intensified by the piston motion and influenced by the shape of combustion chamber. In particular, the swirl and turbulence levels existing immediately before and during combustion affect the evolution of these processes and determine engine performance, noise and pollutant emissions. Both the turbulence characteristics and the bulk flow pattern in the cylinder are strongly affected by the inlet port and valve design. In the present paper, large eddy simulation (LES) is appraised and applied to studying the turbulent fluid flow around the intake valve of a single cylinder IC-engine as represented by the so called magnetic resonance velocimetry (MRV) flow bench configuration with a relatively large Reynolds number of 45,000. To avoid an intense mesh refinement near the wall, various subgrid scale models for LES; namely the Smagorinsky, wall adapting local eddy (WALE) model, SIGMA, and dynamic one equation models, are employed in combination with an appropriate wall function. For comparison purposes, the standard RANS (Reynolds-averaged Navier–Stokes) k- $\epsilon$ model is also used. In terms of a global mean error index for the velocity results obtained from all the models, at first it turns out that all the subgrid models show similar predictive capability except the Smagorinsky model, while the standard k- $\epsilon$ model experiences a higher normalized mean absolute error (nMAE) of velocity once compared with MRV data. Secondly, based on the cost-accuracy criteria, the WALE model is used with a fine mesh of ≈39 millions control volumes, the averaged velocity results showed excellent agreement between LES and MRV measurements, revealing the high prediction capability of the suggested LES tool for valve flows. Thirdly, the turbulent flow across the valve curtain clearly featured a back flow resulting in a high speed intake jet in the middle. Comprehensive LES data are generated to carry out statistical analysis in terms of (1) evolution of the turbulent morphology across the valve passage relying on the flow anisotropy map, (2) integral turbulent scales along the intake-charge stream, (3) turbulent flow properties such as turbulent kinetic energy, turbulent velocity and its intensity within the most critical zone in intake-port and along the port length, it further transpires that the most turbulence are generated across the valve passage and these are responsible for the in-cylinder turbulence.

In the present paper, thermal transport and entropy production mechanisms in a turbulent round jet of compressed nitrogen at supercritical thermodynamic conditions are investigated using a direct numerical simulation. First, thermal transport and its contribution to the mixture formation along with the anisotropy of heat fluxes and temperature scales are examined. Secondly, the entropy production rates during thermofluid processes evolving in the supercritical flow are investigated in order to identify the causes of irreversibilities and to display advantageous locations of handling along with the process regimes favorable to mixing. Thereby, it turned out that (1) the jet disintegration process consists of four main stages under supercritical conditions (potential core, separation, pseudo-boiling, turbulent mixing), (2) causes of irreversibilities are primarily due to heat transport and thermodynamic effects rather than turbulence dynamics and (3) heat fluxes and temperature scales appear anisotropic even at the smallest scales, which implies that anisotropic thermal diffusivity models might be appropriate in the context of both Reynolds-averaged Navier–Stokes (RANS) and large eddy simulation (LES) approaches while numerically modeling supercritical fluid flows.