Week 1- Mixing Tee

Introduction:

In the field of fluid dynamics where predicting the right results with right assumptions is a really big deal. For resolving this CFD is a tool that is doing the same via solving several governing equations like conservation of momentum – Navier stokes equation, conservation of energy etc. at the same time. It is a sub-part of fluid dynamics that visualise the flow of fluid and its relative physics. So, we are solving the fluid challenge of mixed tee with Ansys software by starting from pre-processing and ends with post-processing by doing solving in between both of them. This is a problem that is basically based on the missing of 2 same phase fluids of different temperature. On the basis of the velocities of the fluid flow and the time that given them to mix according to the given geometry. We have to analyse the temperature distribution at the output.

Procedure

To get the desirable results we go through 3 major steps in the same sequel and based on the steps we followed during whole setup we got the results.

1. First of all, open the workbench
2. Drag the Fluid Flow (fluent) part in the Project schematic window
3. So via going through Geometry option open the Space claim
4. Go to the open – new – go to geometry location – select open command
5. By following step 4 we will able to open the geometry in the space claim
6. Now choose the required volume from the whole geometry to do further process efficiently.
7. After doing that new volume is created in the structure Tree and after that supress physics of previous geometry, so that it cant be go in further steps.
8. After verifying the model close the window.
9. Now open Ansys Meshing window and let the geometry upload.
10. Then firstly name all the parts of the model.
11. Then from the Tree right click on mesh and tap “Generate mesh”
12. Set the sizing of the meshing from its detail and then repeat the step 11.
13. After verifying the mesh, close the Ansys Meshing window.
14. Now open Ansys fluent window by clicking over ‘Setup’ and let the geometry upload.
15. For verifying the check click of ‘Checks’ option and see the results in console.
16. Go to the General and set the case accordingly as mentioned in the challenge
17. As we are dealing with temperature so mark the Energy option and chose the viscous flow option to define the fluid flow.
18. After this set the Boundary conditions.
19. The initialize the case
20. Set the total no. of iteration
21. Generated the graphs that we want to observe during the case run
22. Click calculate to make simulation run
23. As the simulation completed close the tab and do the postprocessing as analyse the contours and plots.
24. For this select the plane slice that is situated in the centre of the geometry and over it we have to perform the contour analysis.
25. Close the tab after extracting useful results.
26. Save the case and cut the software.

Results:

As we run the complete simulations for the different combinations, So we get to that we done the 5 case run to get complete data that demands in the challenge.

Cases:

1. Long tee with momentum ratio 2 and temp hot-36 and cold-19 with k-epsilon
2. Long tee with momentum ratio 4 and temp hot-36 and cold-19 with k-epsilon
3. Long tee with momentum ratio 2 and temp hot-36 and cold-19 with k-epsilon
4. Long tee with momentum ratio 4 and temp hot-36 and cold-19 with k-epsilon
5. Long tee with momentum ratio 4 and temp hot-36 and cold-19 with k-omega

All the plots and contours are bind in a word file that is attached with this solution. Kindly find the word file to get elaborated solution.

Mesh Independent Study:

As I do the mesh independent study for the Long tee with momentum ratio 2 and temp hot-36 and cold-19 case and the important details that comes out during the run is as following:

• As the mesh size decreases the convergence comes respectively late
• As the mesh size decreases accuracy of the result increases respectively
• As the mesh size increases the separation boundaries in the contours are hard to visualize.
• Mesh refinement is inversely proportional to the time that the simulation taken to complete the run

This is all because as the mesh size decreases the cell counts in the geometry increases due to that during the simulation system has to solve governing equations in many extra cells also that increases the time but as it is solving more randomly so the accuracy of the result is increased.

Effect of length and momentum ratio on results:

As currently we are dealing with the mixed tee problems in which there are two input channels that have two temperatures and angled at about perpendicular to each other. At the meeting interface both the input streams are supposed to mix and share their temperatures that gives the in between temperature of the mixed fluid at the outlet. So, we are interested in finding the effectiveness of mixing of the fluid flows to get less standard deviation. So, we are working on the length of the passage after the missing interface and velocity of the cold channelled fluid and we got following results:

• As the length of the passage increased the standard deviation decreases that means the fluid is mixing more properly that can be seen in the contours also that the temperature separation is not much but yes, its little less be found at the outlet section and vies-versa.
• Other than this momentum ration has very big impact over the convergence of the temperature at the outlet.

Momentum ratio = (velocity at cold inlet flow / velocity at hot inlet flow)

So, by the above results it can be analyse that as the momentum ratio increase the velocity difference also increased between the cold and hot inlet flow. As the hot flow velocity is constant according to the challenge’s data that means relatively we are only increasing the cold flow velocity with increasing momentum ratio.

So As momentum ration increased, the cold flow inlet velocity also going to increased respectively, that means at the interface more turbulence will generates that we know is a effective parameter to enhance mixing of fluids. Same we see at the outlet also.

Comparison Table

Parameter	Cell count	Avg. Outlet Temp.	No. of iteration to Converge
Case 1	61186	30.3	122
Case 2	61186	27.6	150
Case 3	50012	30.5	115
Case 4	50012	27.9	175

Word file with all snapshots is attached below.

Thankyou

Anubhav