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The Selective Catalytic Reduction (SCR) is a promising approach to meet future legislation regarding the nitric oxide emissions of diesel engines. In automotive applications a liquid urea-water solution (UWS) is injected into the hot exhaust gas. It evaporates and decomposes to ammonia vapor acting as the reducing agent. Significant criteria for an efficient SCR system are a fast mixture preparation of the UWS and a high ammonia uniformity at the SCR catalyst. Multiphase CFD simulation is capable to support the development of this process. However, major challenges are the correct description of the liquid phase behavior and the simulation of the ammonia vapor mixing in the turbulent exhaust gas upstream of the SCR catalyst. This paper presents a systematic study of the impact of the turbulence model and the numerical spatial discretization scheme on the prediction of the turbulent mixing process of the gaseous ammonia.

In exhaust systems with selective catalytic reduction (SCR) a fast conversion of liquid urea to gaseous ammonia and a uniform distribution of the ammonia vapor upstream of the SCR catalyst are essential to reduce the nitric oxides efficiently. For the prediction of the mixing process and the transport of ammonia vapor with the CFD method an accurate description of the turbulent flow field is a basic requirement. This paper presents the comparison of simulation results using three different turbulence models (high-Re kε-RNG model, low-Re kω-SST model, Reynolds stress model) with measurements of the turbulent velocity field using Laser Doppler Anemometry (LDA). The investigations were carried out for a SCR system with a swirl mixer on a cold flow test bench for two different volume flows. From the measured velocity signals different components of the Reynolds-tensor were derived.

The combustion efficiency of large gas engines is limited by knocking combustion. Due to fact that the quality of the fuel gas has a high impact on the self-ignition of the mixture, it is the aim of this work to model the knocking combustion for fuel gases with different composition using detailed chemistry. A cycle-resolved knock simulation of the fast burning cycles was carried out in order to assume realistic temperatures and pressures in the unburned mixture Therefore, an empirical model that predicts the cyclic variations on the basis of turbulent and chemical time scales was derived from measured burn rates and implemented in a 1D simulation model. Based on the simulation of the fast burning engine cycles the self-ignition process of the unburned zone was calculated with a stochastic reactor model and correlated to measurements from the engines test bench. A good agreement of the knock onset could be achieved with this approach.