Mixing Tee(Ansys Fluent)
Objective:
For this challenge, we have created two versions of the mixing tee. One of them is longer than the other.
The first job is to set up steady-state simulations to compare the mixing effectiveness when hot inlet temperature is 360C & the Cold inlet is at 190C.
Use the k-epsilon and k-omega SST model for the first case and based on your judgment use the more suitable model for further cases. Giving the reason for choosing a suitable model is compulsory.
- Case 1
- Short mixing tee with a hot inlet velocity of 3m/s.
- Momentum ratio of 2, 4.
- Case 2
- Long mixing tee with a hot inlet velocity of 3m/s.
- Momentum ratio of 2, 4.
Theory:
Mixing tee is flow is flow control device. It mixes the two different fluid streams into the combined fluid stream i.e, it has two inlets and one outlet. Mixing tees are widely used in the petrochemical industry.
Problem Set-up:
Let us start with analyzing the best method to converge the solution, understanding the k-epsilon and k-omega SST model for the first case:
1)Geometry: After clicking Fluid Flow(Fluent) in Ansys Workbench, open geometry to import mixing tee model. It will redirect to SpaceClaim.
2)Fluid volume extraction: We are analyzing the mixing of two fluids, as there is the role of a specific part hence we need to extract the volume of a tee.
3)Suppress the actual model, as we do not have to make any conduction simulation in this project:
4)Mesh: After opening Ansys meshing we will name the surfaces of Geometry and then generate the mesh.
5) After the complete loading of domain geometry, it will represent it in a graphical user interface as follows:
6)
- In the domain panel by using the check button we check our analysis is preferable or not. After clicking the check mesh quality, it prints the information in the Console window.
- Then we will set the physics of the domain by keeping the general setting as it, i.e Solver type-Pressure based, Velocity formation- Absolute, Solver time- Steady.
- Next activate models and turn on the energy equations. Activating the energy equations allows the temperature-dependent problem to be solved.
- In the viscous model select 'K-epsilon' for our first simulation. Turbulence modeling is a complex area, the choice of model depends on the application. Accept the remaining default settings.
- In materials click 'FLUENT Database' to add new material. In this case, our working fluid is air sp we keep the default material. Then, in the cell zone define the material and type as Fluid.
- In 'Boundary condition' click on inlet_x and set the parameter velocity as 3 m/s and temperature as 36°. For inlet_y velocity as 12 m/s and temperature as 19°.
- In Reports, press 'New' for surface report monitoring. Select Area weighted average for temperature and then for velocity and enable "report file" and "report plot".
- The final step is to initialize, select Hybrid initialization and check the console window that says initialization done. Enter the no. of iteration and press 'Calculate. Then after the calculation is done we will get the required plots and information.
PLOTS:
1. K-epsilon:
- Convergence Plot
2. K-omega SST:
- Convergence Plot
Similarly, we will Compare Temperature and Velocity Contour for both the method:
K-epsilon:
- Temperature Contour
- Velocity Contour
K-Omega SST:
- Temperature Contour
- Velocity Contour
In the above contour, we can see flow differences in K-epsilon and k-omega SST. Let us understand why they are different.
K-epsilon:
- K-epsilon turbulence model is the most commonly used model in CFD to simulate the mean flow characteristics for turbulent flow conditions. It is a two-equation model that gives a description of turbulence by means of two transport equations(PDE's). The first transport variable is turbulent kinetic energy and the second transport variable is the rate of dissipation of turbulent kinetic energy.
- K-epsilon focuses on the mechanism that affects the turbulent kinetic energy.
K-Omega SST:
- k-omega SST is a two-equation eddy viscosity model that is used for many aerodynamics applications. It is a hybrid model combining the Wilcox omega and k-epsilon models. A blending function activates the Wilcox model near the wall and k-epsilon in the free stream. This ensures that the appropriate model is utilized through the flow field.
Main Difference:
- K-omega model is well suited for simulation flow in the viscous sub-layer. On the other hand, k-epsilon is ideal for predicting flow in the regions away from walls.
- The K-omega exhibit less sensitivity to the free stream conditions than any other turbulence models.
In this particular case we are not dealing with walls, therefore we are going to use the K-epsilon method for further simulation.
CASE 1-a:
Short Mixing Tee:
Inlet velocity- 3m/s
Momentum ratio- 4
- Convergence Plot
The solution is converging at around 125 iterations.
Area weighted average outlet temperature:
The average temperature at the outlet is 27.594307°C.
Area weighted average velocity:
The average velocity at the outlet is 6.049474 m/s.
- Temperature Contour
- Velocity Contour
CASE 1-b:
Short Mixing Tee:
Inlet velocity- 3m/s
Momentum ratio- 2
- Convergence Plot
The solution is converging at around 135 iterations.
Area weighted average outlet temperature:
The average temperature at the outlet is 30.364227°C.
Area weighted average velocity:
The average velocity at the outlet is 4.5059489 m/s.
- Temperature Contour
- Velocity Contour
CASE 2-a:
Long Mixing Tee:
Inlet velocity- 3m/s
Momentum ratio- 4
Mesh:
- Convergence Plot
The solution is converging after 150 iterations.
Area weighted average outlet temperature:
The average temperature at the outlet is 27.489294°C.
Area weighted average velocity:
The average velocity at the outlet is 6.0181235 m/s.
- Temperature Contour
- Velocity Contour
CASE 2-b:
Long Mixing Tee:
Inlet velocity- 3m/s
Momentum ratio- 2
- Convergence Plot
The solution is converging after 175 iterations.
Area weighted average outlet temperature:
The average temperature at the outlet is 30.40744°C.
Area weighted average velocity:
The average velocity at the outlet is 4.4989516 m/s.
- Temperature Contour
- Velocity Contour
Mesh Independence:
- Mesh independence(or Grid independence) study is something we can perform to determine the dependence of the results on the mesh density.
- Compare the results for various runs for different sizing of the meshing elements. In order to pass, mesh independence results should obtain with proper precision.
Output Table:
| Element Size(Short tee with Momentum ratio-4 was considered) | CELL COUNT | AVERAGE OUTLET TEMPERATURE | NUMBER OF ITERATION FOR CONVERGENCE |
| 0.010219(Default) | 12583 | 27.58965°C | 145 |
| 0.004 | 22284 | 27.562590°C | 138 |
| 0.002 | 105858 | 27.594307°C | 125 |
Conclusion:
- The k-epsilon model predicts flow virtually far from the boundaries and the k-omega model predicts near the walls. As for this case we needed a flow simulation turbulent model far from the walls we used k-epsilon.
- After conducting simulations, as element number increases the convergence time also increases.
- To get better mixing at outlet high velocity of flow is very effective. Therefore, a higher momentum ratio gives better mixing of hot and cold fluid streams at the outlet.
- Finally, in the above case, it is very important to use a short mixing tee with a momentum ratio of 4 to get precise results.
References: