2D simulations with Reynolds Stress turbulence model
Hypothesis and Goals
The Reynolds Stress model(RSM) is the most elaborate turbulence model that FLUENT provides. Abandoning the isotropic eddy-viscosity hypothesis, the RSM closes the Reynolds-averaged Navier-Stokes equations by solving transport equations for the Reynolds stresses, together with an equation for the dissipation rate. This means that five additional transport equations are required in 2D flows.
Since the RSM accounts for the effects of streamline curvature, swirl, rotation, and rapid changes in strain rate in a more rigorous manner than one-equation and two-equation models, it has greater potential to give accurate predictions for 180-degree-turning flow in the hydraulic flocculator.
Simulations using RSM was compared to results from the current k-epsilon realizable (rke) model.
Methods and Procedures
FlUENT settings can be found in the report summaries for k-epsilon realizable model and Reynolds stress model
Note that as opposed to k-epsilon realizable solver, RSM is quite sensitive to different specification methods of both inlet and outlet boundary conditions.
Results and Discussion
A comparison of the contours of energy dissipation rate, stream function and static pressure from RSM and rke are shown below.
Energy dissipation map from Reynolds Stress Model (2D)
As shown above, results from the two turbulence models appear similar in terms of the lengths and shapes of the energy dissipation zone and the range of the energy dissipation value, while more detailed minor discrepancies indicates the differences of the two models in terms of their underlying assumptions and methodology.
Further Research
- RSM is quite sensitive to turbulence specification method of both inlet and out boundary conditions, thus more simulation experiments and research on the underlying methodology are needed to investigate about this parameter.
- The current comparison between RSM and RKE is quite preliminary. Comparisons of other pertinent parameters are necessary for better understanding of the models and how to choose between them for our specific flow.