Mixing efficiency
Title: Steady-state simulations of Mixing Tee pipe with the help of AnsysFluent.
1. Introduction
Mixing Tee is used to perform effective mixing of two fluid, to achieve certain conditions of Temperature and velocity at the outlet of the pipe. For example Air conditioning of a room to attain suitable temperature in a room.
The aim of this project is to compare the effect of the length of pipe on mixing efficiency as well as the effect of momentum ratio on outlet temperature.
2. Solving & Modelling approach
To perform steady-state simulation of Mixing Tee with the help of ANSYS Fluent, Two cases need to be performed as stated below.
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.
Here,
Momentum Ratio = velocity at cold inlet/velocity at hot inlet
2.1 Geometry
Model-1: Short pipe Mixing Tee geometry in Ansys SpaceClaim. Model-2: Long pipe Mixing Tee geometry in Ansys SpaceClaim.
As we are interested in finding only the outlet temperature of a fluid in this simulation, we need to extract the wet volume from these models using the volume extract feature from the SpaceClaim. Using the volume extract tool, we get a computational fluid domain as shown below.
1. Short Tee computational fluid domain 2. Long Tee computational fluid domain
2.2 Meshing
After extracting the computational fluid domain from the model, the next step is to discretize the fluid domain. ANSYS meshing tool is used to generate a mesh in the model.
2.2.1 Mesh Independency study
Before finalizing meshing for any model it is very important to see the effect of mesh sizing on any simulation, as too fine mesh leads to higher computational time and too coarse mesh leads to error in the simulation results. Hence here in this project before finalizing mesh sizing numerous simulations were performed to see the effect of sizing on simulation results.
Below shows the two residuals curve for long pipe Tee with around 80k and 192k mesh elements, performed with the k-epsilon model with a momentum ratio of 2. The simulations result from both the cases were very similar. It can also be seen from the residuals curves that model with higher mesh elements tends to converse slowly as compared to model with less elements. The outlet Temperature in both the cases was around 30 °C and the standard deviation was also around 1 °C. Hence, we can conclude that for this particular case body sizing of 0.003m, which gives 80k mesh elements is acceptable.
1) Residuals with 80k mesh elements 2) Residuals with 192k mesh elements
The method used for meshing in these cases is tetrahedron mesh. Body sizing of 0.003 m is used to generate finite volumes. By applying these configurations, the number of elements generated is around 58k and 80k in Short Tee and Long Tee model respectively.
3. Pre-processing and solver setting
The next step in the simulation after generating fine meshing is to set-up the physical properties for the case.
The Energy equation needs to be enabled, as we are interested in solving for the Temperature distribution.
- Type of solver: Pressure-based
- Simulation method: Steady-state simulation
- Material properties of fluid (Air)
Density: 1.225 kg/m3
Cp (Specific heat): 1006.43 J/kg-k
Thermal Conductivity: 0.0242 w/m-k
Viscosity: 1.7894e-05 kg/m-s
- Inlet-x velocity: 3 m/s (Inlet x is along the pipe axis)
- Inlet-x Temperature: 36°C
- Inlet-y velocity: 6 m/s (For MR=2) & 12m/s (For MR=4) (Inlet y is perpendicular to the pipe axis)
- Inlet-y Temperature: 19°C
- Outlet: Pressure type, 0 gauge pressure.
- Walls: wall type with no slip.
*MR = Momentum Ratio
Two report definition files need to be generated from the surface report definition namely Area-weighted average and Standard Deviation, as we are interested in finding the temperature distribution in pipe and outlet temperature to see the effectiveness of the mixing Tee.
3.1 Turbulence model
The selection of the viscous model is a complex process and varies for different types of applications and modeling. Here, in this project to select a turbulent model between Kε-Realizable and Kω-SST, two simple case simulations are performed for a short Tee pipe with MR=2. From the results, it can be concluded that although results from both the simulations are similar, the Kε-Realizable model converges faster compares to Kω-SST model as can be seen from the residuals plot below.
1) Residuals plot for Kε-Realizable model 2) Residuals plot for Kω-SST model
4. Results
After setting up a case and providing appropriate initial and boundary conditions, numbers of simulations are performed mainly for the comparison of results both short and long Tee geometry as well as the effect of momentum ratio on the outlet temperature.
4.1 Results of short pipe Tee model
4.1.1 Results of short pipe Tee model (MR =2)
1) Residuals plot for momentum ratio=2.
2) Average outlet temperature curve for momentum ratio=2. 3) Standard deviation curve for momentum ratio=2.
4.1.2 Results of short pipe Tee model (MR =4)
1) Residuals plot for momentum ratio=4.
2) Average outlet temperature curve for momentum ratio=4. 3) Standard deviation curve for momentum ratio=4.
4.2 Results of Long pipe Tee model
4.2.1 Results of Long pipe Tee model (MR =2)
1) Residuals plot for momentum ratio=2.
2) Average outlet temperature curve for momentum ratio=2. 3) Standard deviation curve for momentum ratio=2.
4.2.2 Results of Long pipe Tee model (MR =4)
1) Residuals plot for momentum ratio=4.
2) Average outlet temperature curve for momentum ratio=4. 3) Standard deviation curve for momentum ratio=4.
4.3 Comparison of simulation results from the 2 cases.
| Short Tee Geometry (MR=2) | Short Tee Geometry (MR=4) | Long Tee Geometry (MR=2) | Long Tee Geometry (MR=4) | |
| Number of elements | 57994 | 57994 | 80101 | 80101 |
|
Average outlet temperature |
30.27 °C | 27.59 °C | 30.35 °C | 27.55 °C |
|
Number of iterations for convergence |
125 Iterations | 175 Iterations | 125 Iterations | 150 Iterations |
4.4 Post-processing
After performing all the simulations, to analyze the result it is very important for any CFD simulation to perform post-processing as it gives clear visualization of the results. This section provides a few post-processing results of the above-performed simulations.
4.4.1 Velocity and temperature contour plots on the cut planes along the length of the pipe.
1) For Short Mixing Tee (MR=2)
2) For Short Mixing Tee (MR=4)
3) For Long Mixing Tee (MR=2)
4) For Long Mixing Tee (MR=4)
4.4.2 Velocity and temperature contour plots on the cut planes across the length of the pipe.
1) For Short Mixing Tee (MR=2)
2) For Short Mixing Tee (MR=4)
3) For Long Mixing Tee (MR=2)
4) For Long Mixing Tee (MR=4)
5. Conclusion
After performing numerous simulations with different sizes of Mixing Tee as well as with different momentum ratios, a few conclusions can be drawn from this study of CFD simulations.
1) From this study, it can be concluded that the Kε-Realizable model is more suitable for this application as compared to Kω-SST. Since Kω-SST model gives a higher standard deviation. hence, being less accurate. Also Kω-SST model takes more time to converse as compared to the Kε-Realizable model.
2) Once two flow stream mixes adequately enough then the Length of the Mixing Tee does not affect the outlet temperature. As can be seen from the above results for both Mixing Tees with the same momentum ratio, outlet temperature is very similar. Hence, it can be recommended to use a short tee mixing pipe to save the cost of the material.
3) Momentum Ratio or the velocity of cold air has a significant effect on the outlet temperature or the effectiveness of mixing Tee for the same length of the Tee. As can be seen from both the cases of short and long tee outlet temperature drops significantly with doubling the velocity of cold inlet air.