Application Of An Advanced RANS Turbulence Model In Modeling In-cylinder Flow Of Internal Combustion Engines

As one of the most important and fundamental processes, the in-cylinder turbulence flow directly influences spray, fuel/air mixing, combustion, and emission processes in internal combustion engines (ICE). Thus, it is of great importance to accurately model the turbulence flow in ICE, which is also crucial for engine designing. However, the in-cylinder turbulence flow can not be fully accurately reproduced using current numerical simulation tools due to strongly transient, compressible, and anisotropical characteristics of the flow. With the rapid development of computer technology, the investigation of high-fidelity Large-Eddy Simulation (LES) and Direct Numerical Simulation (DNS) techniques have been promoted. However, the computational cost is still very high employing state-of-the-art LES technique as well as DNS technique. In comparison, it is still promising to develop computationally efficient and practical Reynolds Averaged Navier-Stokes (RANS) models.In this study, a three-dimensional Computational Fluid Dynamics (CFD) code KIVA3V was used as the numerical simulation tool. An improved RANS turbulence model based on generalized Re-Normalization Group (RNG) closure analysis (GRNG model) was employed to investigate in-cylinder charge flow, spray, fuel/air mixing, combustion and emission in several different operating conditions of the engines by comparing with the standard k-ε turbulence model and RNG turbulence model. The effects of mesh resolution as well as the operating parameters including swirl ratio, injection pressure, and load were examined in this study. The simulation results were compared with the measurements to evaluate the predicting performance of the newly developed GRNG turbulence model. Our aim is to expand the operating range of the new model and make it capable of predicting the in-cylinder flow in more wide conditions for various engines.The test cases included the backward facing step flow, intake flow of a single-valve engine, spray of an optical engine, as well as the combustion in a light-duty optical engine and a heavy-duty diesel engine. The simulation results were compared with the measurements, and the standard k-ε turbulence model and RNG turbulence model were chosen for comparison with the GRNG model. The results showed that the predicting performance of the GRNG model was improved significantly in modeling the cases with pure flow (i.e., the backward facing step flow and intake flow of a single-valve engine) compared with the other two turbulence models, especially for the prediction of the distribution of turbulent kinetic energy in backward facing step flow. As for the prediction of spray, both the predicted spray penetration and distribution shape of equivalence ratio using GRNG model matched the measurements better than that of the standard k-ε turbulence model and RNG turbulence model. In the simulation of the cases with combustion, the predictions using the GRNG model matched better with the measured in-cylinder pressure and heat release rate traces compared with that of the other two turbulence models under different swirl ratios (i.e.,1.55,2.2,3.5 and 4.5) and injection pressures (i.e.,500, 860, and 1220 bar). Furthermore, the GRNG turbulence model showed improved predictions in modeling the combustion process in a heavy-duty engine under different loads with indicated mean effective pressure (IMEP) of 0.44,1.10, and 1.95 MPa.In conclusion, the GRNG turbulence model showed significantly improved prediction results compared with the standard k-ε turbulence model and RNG turbulence model, which proved that the new model is more reliable and practical for the simulation of Internal Combustion Engines (ICE).