Week 1- Mixing Tee

1. Title – Mixing Tee Effectiveness

2. Objective –

• To clean the geometry and mesh it in pre-processing.
• To solve the model with the best solver in Ansys solver.
• To generate contour and line plots and analyze them in post-processor.

3. Introduction –

Computational fluid dynamics is a branch of fluid mechanics, which uses mathematics, physics, and computational software to visualize how fluid flows and affects its medium and its neighbors. In CFD mostly computers are used to predict the fluid flow phenomena based on some governing equations like conservation of momentum – Navier stokes equation, conservation of energy, etc. In this study, we will simulate fluid the effect using Ansys fluent software. Ansys fluent is an essential tool in the CAE domain, which allows you to perform all three major steps of any simulation pre-processing, solving, and post-processing. Ansys fluent facilitates modeling flow, turbulence, heat transfer, and chemical reactions. With Ansys, we can make accomplice more in less time and with less training.

Mixing tee is a device that uses specifically engineered internal geometry to mix two fluid streams into one steam, efficiently. In this study, we are going to find the effectiveness of combining tee. Hot air and cold air are going to be mixed in mixing tee. They will have different velocities. We will use two different mixing tees distinguished by length and analyze the effect of length on mixing.

Fluid is a substance i.e. having the ability to flow or deform(angular) continuously under the action of shear
force(no matter how much small the force). Generally, liquids and gases fall into this category of fluids.

4. Types of fluids -

1. Ideal fluid – it is a fluid that shows non-viscous, incompressible, and zero surface tension in nature.
2. Real fluid – possesses viscosity
3. Newtonian fluid - which obeys NLV(Ex: oil, water, air, etc.)
4. Non-newtonian fluid – which does not obey NLV (Ex: blood. paints etc.)
5. Ideal plastic fluid – in which shear stress is more than the yield value and obeys NLV.( Ex: toothpaste, gels, etc)
6. Compressible fluid – a fluid in which the density of fluid changes with a change in the pressure or volume called
compressible fluids. (Ex: air)
7. Incompressible fluid - a fluid in which the density of a fluid does not change w.r.t. change in pressure and volume

5. Procedure -

There are three significant steps to perform any type of simulation as follows pre-processor – it includes geometry clean up and generating the best quality mesh. Solving includes applying boundary conditions, initialization, and convergence. The last step is post processor which includes generating plots, contours, and vectors to analyze results. In this study, we are going to follow all three steps to find out the effectiveness of mixing tee. The following steps are to be followed –

1. Open a new project, by clicking on Fluid flow (Fluent) in the Ansys workbench.

2. Now click on geometry to import the mixing tee model. It will redirect to Spaceclaim, Ansys’s geometry model manipulator.

3. We are to analyze the mixing of two fluids, so there is a role of parts other than two pipes. To suppress that we need to extract the volume of the tee. Go to prepare a menu and click on volume extract. Switch to edge selection and select three outer edges and click on the green check button

4. Hide solid by unchecking it from the structure menu to see the volume, which we have extracted. Suppress solid by clicking on the option suppress for physics.

5. Exit from Spaceclaim and click on the mesh to open the mesh menu.

6. Now click on the mesh option and choose to generate the mesh. It will generate mesh according to some predefined criteria. Element size can be selected but it is going to affect simulation time. A section plane can be created to see the inner portion of geometry.

7. Select the option element quality to see, how many elements are defying quality. Quality is measured on a scale of 0 to 1. In our graph, most of the elements are near 1 so we can say it is good quality.

8. Exit mesh and open setup. Now click on double precision and solver processes=4 then click on start.

9. Go to the physics menu and select a dense model. It will open a menu, choose the realizable k-epsilon model and close it.

10. Click the material and choose 'Air' the as working fluid. Check working fluid by clicking on the cell zone conditions option, if it is air then proceed.

11. Now go to the boundaries option to set boundary conditions. Select inlet_x and click on the option edit. It will open a menu, where all the parameters can be set whether it is thermal, radiation, momentum, etc. Put the velocity value as 3m/s and go to the thermal parameter to set the temperature as 36C, for hot fluid.

12. Repeat the same procedure for cold fluid coming, velocity –6 m/s, temperature – 19C.

13. We want to generate a temperature report of the outlet and we want a standard deviation of temperature also. Go to the Solutions tab and select definition and select area-weighted average. In the opened menu select temperature as the field variable. Similarly, select standard deviation in the definitions menu.

14. Now click on initialization to calculate approximate velocity and pressure values.

15. Change the number of iterations to 150 and click on calculate. If the solution is not converged, then iterations can be increased.

16. Exit setup and double-click on the result to open the CFD post.

17. Now insert an XY plane in the wall by clicking on a plane in the location option of the insert.

5. Results –

Case 1 – This short mixing tee is used, which was mixing two fluids at temperatures 6C and 19C. The velocity of hot fluid was 3m/s and cold fluid was 6m/s. we used two different turbulent solvers for it first was realized k-epsilon and the second was k-omega SST.

In this case, k-epsilon is giving better results because the solution converged after a few iterations, whereas after using the k-omega model solution was not converged. K-omega is preferred in studying fluid behavior near the wall, but here it is not the case. So, the k-epsilon model is recommended to study fluid far from the wall i.e. flow region, in further cases.

Plot and contours from the k-epsilon model

Fig. Temperature Contour

Plot and contours from the k-omega model

Fig. Temeprature Contour

Fig. Velocity Contour

Case 2 - In this case long mixing tee is used, which was mixing two fluids at temperatures 36C and 19C. The velocity of hot fluid was 3m/s and cold fluid was 12m/s.

k-epsilon (MR2)

k-omega (MR2)

k-epsilon (MR4)

K-OMEGA (MR4)

Parameters	Cell Count	Average outlet temperature	Number of iterations to converge
Case 1	40039	30.20C	160
Case 2	56670	29C	157

Mesh Independent Study –

Mesh-independent test allows meshing refinement without affecting results. After some tests, we can be ensured by a solution that mesh refinement won’t affect the result. The following graphs are showing the results after mesh refinement on the short mixing tee, earlier element size is used as 0.0195 and now it got 0.001.

Fig. Residuals

Fig. Average Temperature vs Iterations

Fig. Standard Deviation of Temperature vs Iteration

6. Conclusion –

Ansys fluent is high-performance CFD software recognized for accuracy, robustness, etc. it is not confined to only aerospace and mechanical domain, it has various applications like to simulation of calculation of airflow on aircraft wings, combustion in furnaces, bubble columns in oil refineries, combustion in IC engine, etc. In this study, we performed a simulation on the simple geometry of mixing tee and got insights into various features of fluent. we can conclude by analyzing the graph that If the momentum ratio is increased, outlet temperature will decrease and there is no effect of velocity even though the length is increased.