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Impact of the Turbulence Model and Numerical Approach on the Prediction of the Ammonia Homogenization in an Automotive SCR System
Abstract:
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. The simulations are carried out for an exhaust system with
a mixing element that creates turbulent swirl flow in the mixing
pipe. Numerical results are validated with back pressure
measurements at the mixer and CLD measurements of the spatial
distribution of the reduced NOx concentration at the
catalyst outlet.
The study proves the high impact of an advanced second-order
differencing scheme on the species transport. Furthermore it shows
that Reynolds-averaged k-ε models systematically underestimate the
turbulence level in the swirl flow and, in consequence, the
turbulent diffusion and uniformity of the ammonia vapor at the
catalyst. In contrast, a Reynolds-Stress model leads to improved
predictions by accounting for the anisotropic character of
turbulence in the swirl flow. In combination with detailed
submodels of the liquid phase dynamics and -evaporation a correct
prediction of the ammonia homogenization for a wide range of
operating conditions can be achieved. By this means a good
correlation with measured ammonia uniformity indices and the mixing
element"s back pressure behavior can be observed. The
described numerical method therefore allows for a predictive
evaluation and optimization of SCR-mixing systems.