Nowadays, detailed kinetics is necessary for a proper estimation of both flame structure and pollutant formation in compression ignition engines. However, large mechanisms and the need to include turbulence/chemistry interaction introduce significant computational overheads. For this reason, tabulated kinetics is employed as a possible solution to reduce the CPU time even if table discretization is generally limited by memory occupation. In this work the authors applied tabulated homogeneous reactors (HR) in combination with different turbulent-chemistry interaction approaches to model non-premixed turbulent combustion. The proposed methodologies represent good compromises between accuracy, required memory and computational time. The experimental validation was carried out by considering both constant-volume vessel and Diesel engine experiments. First, the ECN Spray A configuration was simulated at different operating conditions and results from different flame structures are compared with experimental data of ignition delay, flame lift-off, heat release rates, radicals and soot distributions. Afterwards, engine simulations were carried out and computed data are validated by cylinder pressure and heat release rate profiles.
A detailed prediction of injection and air–fuel mixing is fundamental in modern direct injection, spark-ignition engines to guarantee a stable and efficient combustion process and to minimize pollutant formation. Within this context, computational fluid dynamics simulations nowadays represent a powerful tool to understand the in-cylinder evolution of spray and air–fuel charge. To guarantee the accuracy of the adopted multidimensional spray sub-models, it is mandatory to validate the computed results against available experimental data under well-defined operating conditions. To this end, in this work, the authors proposed the calibration and validation of a comprehensive set of spray sub-models by means of the simulation of the Spray G experiment, available in the context of the engine combustion network. For a suitable validation of the proposed numerical setup in addition to the baseline condition, gasoline direct injection operating points typical of early injection with homogeneous operation, late injection with high ambient density and flash boiling with enhanced fuel evaporation were also simulated. Numerical computations were validated against a wide set of available experimental data by means of an accurate post-processing analysis taking into account axial liquid and vapor penetrations, gas-phase velocity between spray plumes, droplet size, plume liquid velocity, direction and mass distribution. Satisfactory results were achieved with the proposed setup, which is able to predict gasoline spray evolution under different operating conditions.
A detailed understanding of the air–fuel mixing process in gasoline direct injection engines is necessary to avoid soot formation that might result from charge inhomogeneities or liquid fuel impingement on the cylinder walls. Within this context, the use of multidimensional models might be helpful to better understand how spray evolution in cylinder charge motions and combustion chamber design affects the mixture quality at spark-timing. In this work, the authors developed and applied a computational fluid dynamics methodology to simulate gas exchange and air–fuel mixture formation in gasoline direct injection engines. To this end, a suitable set of spray submodels was implemented into an open-source code to properly describe the evolution of gasoline jets emerging from multihole atomizers. Furthermore, the complete liquid film dynamics was also considered. For a proper assessment of the approach, a gasoline direct injection engine running at full load was simulated and effects of spray targeting and engine speed were studied. A detailed postprocessing of the computed data of liquid film mass, homogeneity index and equivalence ratio distributions was performed and correlated with experimental data of particulate emissions. Satisfactory results were achieved, proving the effectiveness of the proposed methodology in predicting the effects of injection system and operating conditions on soot formation.
Swirling flows are very dominant in applied technical problems, especially in IC engines, and their prediction requires rather sophisticated modeling. An adaptive low-pass filtering procedure for the modeled turbulent length and time scales is derived and applied to Menter' original k − ω SST turbulence model. The modeled length and time scales are compared to what can potentially be resolved by the computational grid and time step. If the modeled scales are larger than the resolvable scales, the resolvable scales will replace the modeled scales in the formulation of the eddy viscosity; therefore, the filtering technique helps the turbulence model to adapt in accordance with the mesh resolution and the scales to capture. The novel turbulence model presented in this work will be called Dynamic Length Scale Resolution Model (DLRM), because of its capability to dynamically adapt its behavior according to the grid resolution and to consequently switch from modeling to resolving the turbulent length scales. Validation has been carried out both on a strongly swirling flow through a sudden expansion and on a simple IC engine geometry with one axial central valve; the model seems able to capture unsteady effects and to produce accurate time-averaged results (especially if compared to its standard RANS formulation) and looks particularly suitable when used with grids where turbulence would not be sufficiently resolved for an accurate LES.
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