Model Turbulen pada Aliran Campuran Udara dan Hot EGR MEsin Diesel dengan Menggunakan Simulasi Numerik

Abstract

Exhaust gas recirculation (EGR) is a method in which the exhaust gases of combustion inserted back into the engine cylinder. Numerical simulations are used to identify the characteristics of air and EGR mixtures the intake manifold EGR in diesel engines that can not be seen directly through the experiment without the use of sophisticated tools such as thermal cameras. Information obtained from numerical simulations are used to identify the temperature of the air mixture and EGR. In addition, the results of this simulation can be used as a reference for thermocouple placement is used as a means of monitoring temperature of the mixture. Working fluid used in this modeling is hot air and cold air. Velocity and temperature of incoming fluid at the entrance of the intake manifold and EGR pipe was varied in the range of openings, load and round. Turbulence modeling is used k-ε model, k-ω model and Reynolds Stress Model. The result showed that the RSM model in modeling turbulent air mixing with EGR gives the best accuracy results than the k-ε turbulence model and k-ω. Largest percentage error is shown at 100% load variation where the average error obtained from RSM turbulent model of about 0586%, followed by k-ε and then 0846% 0955% k-ω. While the smallest percentage of error is shown in load of 25% where the average error obtained from RSM turbulent model around 0291%, followed by k-ε 0:34% and then the k-ω 0389% but the RSM model has a higher time consuming compared with the model Another turbulent followed by k-ω and k-ε with time consuming an average of 559 iterations each for the RSM model, 418 iterations for k-ω model and 288 iterations for k-ε model. It can be concluded that the prediction of turbulence in the flow of air mixing with EGR by Reynolds Stress Model is closer to the experimental results than the k-ε model and k-ω model but the model of Reynolds Stress Model has a higher time consuming than the k-ε model and k-ω.