Simulation of Thermal Mixing in T joint in Ansys Fluent
AIM
To simulate and study the physical parameters T joint pipe using Ansys fluent
OBJECTIVE
- To set up steady-state simulations to compare the mixing effectiveness
- Use the k-epsilon and K omega SST model
- Use the momentum ratio for each case
- To plot the velocity contour, temperature contour, velocity line plot and the temperature line plot along and across the length of the pipe
- To discuss the effect of length of the pipe and moment ratio
- To perform mesh independent study of one case
T joint geometry
T joint is a type of pipe fitting which is T shaped having an either single and dual outlet or dual inlet and single outlet configuration. It is a common piping component typically used to combine or separate flow of fluid
Here in this project, two cases of geometry are used and one of it is shorter than the other
PROCEDURE
- Open the workbench and drag the fluent flow into the project schematic.
- Open the SpaceClaim by right-clicking on to the geometry. ○.Open the geometry from the saved location ○.Click on Prepare and extract volume using wedge option ○.uncheck the solids and left click to suppress it and close it.
- Mesh ○.Give the names to every part by face selection. ○.Edit the element size 0.003 and generate the mesh ○.Finally, update the mesh.
- Solution Step ○.Click check mesh if the console doesn\'t show any warning then mesh is ok ○.Select the k-epsilon and after one simulation then select the k-omega SST model ○.Give the boundary condition as given data ○.Go to the solution and select the report for temperature like standard deviation- temperature ○.Initialize the domain ○.Run the solution 250 iteration
- CFD post ○.Uncheck the outlet and inlet. ○.select the plane to plot the contour of temperature and velocity. ○.Plot the line plot for temperature and velocity by using line and chart.
Turbulence Model
Two model models are selected for this simulation namely k epsilon and k omega
Geometry
Short tee with
Element size=0.003
Nodes=`8350
No of elements=39817
Mesh quality
As can be seen from the above figure the majority of the element have above 70% of mesh quality. This provides a signal to proceed to simulation.
Setup details
Solver type: Pressure based
Fluid: Air
The energy equation is enabled since simulation involves observing the variance in temperature.
Boundary conditions:
- Hot inlet velocity :3m/s
- Hot inlet temperature :36 °C.
- Cold inlet velocity :6m/s
- Cold inlet temperature:19 °C.
- Outlet pressure :0 gauge pressure.
- Turbulence Model: 1)k-epsilon 2)k-omega
- No of iterations:250
Results
Residuals:
Residual is the difference in the quantity between subsequent quantity. This means that more the residual is low the less the results will change if you will continue to iterate.
k-epsilon
k-omega
Well from the above figure it can be inferred that that k epsilon converged way faster at 120 iterations wheres as k-omega converged with 140 iterations.
The standard deviation of outlet temperature
Both have shown similar figures with only small variance
k-epsilon giving an average deviation of 2.076 and k-omega of 2.079 and the one to be considered is on the basis of the lower value.
Area weighted average of temperature
k-epsilon
k-omega
Here as well the profile of both figures are same with just a very small difference between the.K-epsilon model gave 30.256°C and k-omega model gave the temperature of 30.31°C. After a few iterations, both of the models gave constant values.
Temperature contour along the pipe
k-epsilon
k-omega
Over here observing the two contour for k-epsilon and k-omega both figures shows that diffusions well that\'s because the mesh is courser as the element size is 0.002, but as we observe at the outlet there is lesser diffusion in case of k-epsilon.
Model selection:
k-epsilon model is most reliable because of the following the reason
☆It was quicker as lesser iteration was taken by k-epsilon.
☆The low standard of deviation which itself justifies the accuracy of temperature.
☆if we look at the temperature contour of the both model although both models same mesh, k epsilon have clear fine profile after the t junction.
Thermal mixing
Part 1
The thermal mixing is simulated in using short pipe with 2 case in which case 1 constitutes momentum ratio 2 and case 2. having moment ratio 4
Geometry:
○T-Junction short pipe
Details of meshing
○ Element size:0.003
○Nodes :8350
○No of elements:39817
3d view of the mesh
Mesh quality
Setup details:
★ Everything is similar to Part 1 expect few steps
a)Turbulence model is:k-epsilon
b)Boundary condition
○.Hot inlet velocity and temperature:3m/s,36. ○.Cold inlet velocity :6m/s in case 1 and 12 m/s in case 2 ○.Temperture:19 ○.No of itertation:250
Results:
Residual
case 1
case 2
Both of the cases displays similar results showing constant value after 120 iterations.
The standard deviation of outlet temperatures
Case 1
Case 2
For case 1 it is 2.076 and for case 2 it is 1.06
Area weighted average temperature
Case 1
Case 2
There is a significant difference in terms of average temperature at the outlet, Case 1 gave a temperature of 30.25 while case 2 gave approximately 3 lower than the former one with 27.63. Considering that the standard deviation is lower in case of moment ratio 4 and also that the average temperature is lower than case 2 we can say that case 2 had a better mixing.
Temperature Contour:
case 1
case 2
A noticeable difference can be spotted by viewing both the figures that there is better mixing case 2.It is because case 2 the inlet cold velocity is higher than case 1, hence pushing the hot air down thereby reducing the temperature and resulting in mixing. if scrutinized more the temperature top after the T junction is more than lower which validate that in this simulation there was better mixing.
Velocity contour
case 1
case 2
It can be clearly seen from the figures that in case 2 that cold air velocity pushes the hot air downward. This ultimately results in mixing better and validates the reason for temperature contour.
Temperature line plot
case 1
Case 2
This line tells mixing performance across the whole length of the pipe. A sudden drop in temperature indicates the T junction where it most significant in case 2.As proceeded along the pipe it is observed that the temperature slowly reaches a constant. if put an eye on the plot the second case shows a flattening in the curve which provides a proof better mixing than case1.
Velocity line plot
Case 2
The above plots show velocity along the length of the pipe. The two fluids mix and ends a net resultant velocity after the crossing T junction.
Part 2
The thermal mixing is simulated in using a Long pipe with 2 case in which case 1 constitutes momentum ratio 2 and case 2. having moment ratio 4
Geometry:
○T-Junction short pipe
Details of meshing
○ Element size:0.003
○Nodes:11689
○No of elements:56373
3d view of the mesh
Mesh quality: Majority of elements have 70% quality
Setup details:
★ Everything is similar to Part 1 expect a few steps
a)Turbulence model is:k-epsilon
b)Boundary condition
○.Hot inlet velocity and temperature:3m/s,36. ○.Cold inlet velocity :6m/s in case 1 and 12 m/s in case 2 ○.Temperture:19 ○.No of itertation:250
Results:
Residual
Case 1
Case 2
Both of them took nearly 150 iterations to converge
The standard deviation of temperature
Case 1
Case 2
Case 2 gives a lower standard deviation of 0.402 than case 2 with 1.56.Case 2 is favored as as simply because of lower standard deviation.
Area average related velocity
Case 1
Case 2
Case 1 gives a value 30.316°C while case 2 gave a value of 27.52°C
Temperature contour plot
Case 1
Case 2
The temperature contour results are similar to that of the short pipe the only difference is that in comparison to the short the long pipe has longer due to which there is effective mixing.
Velocity contour
case 1
case 2
When compared to short pipe the velocity is more constant after T junction that cause more efficient mixing.
Line plot of temperature
Case 1
Case 2
This line tells mixing performance across the whole length of the pipe. A sudden drop in temperature indicates the T junction where it most significant in case 2.As proceeded along the pipe it is observed that the temperature slowly reaches a constant.AS the length is larger the shorter pipe it provides enough room to thoroughly mix.
Line plot for velocity
Case 1
Case 2
The above plots show the trajectory of velocity along the length of the pipe. The two fluids mix and end up a net resultant velocity after the crossing T junction.
Conclusion:
Table:
Effects of length on thermal mixing:
Yes, the increase in length does show variance in all the parameters. The increment in length caused more efficient. The area average related outlet temperature increased to a greater extent in the longer pipe and we also saw changes in standard deviation as it got reduced The above all comparisons solidifies the reason that the relation with length and thermal is directly proportional.but it the changes were very minimal we cant totally depend on it. There are other factors also like temperature variance at the inlets and material of the pipe.
Effect of momentum ratio:
The momentum ratio does actually caused to build up a proportional relationship with the thermal mixing and the above the comparison of contour and line plots supports the statement. The results showed that the reduction in average temperature in both short and longer pipe The high-velocity contacts with the low-velocity high-temperature inlet fluid and neutralizes its effect more efficiently with increment in momentum ratio.
Part 4
Mesh independence test
Three cases with each having different element sizes are taken for mesh independent test.
Description
Geometry ○T junction short pipe
Mesh details
Case 1
○Element size: 0.04
○Nodes:2827
○No of elements:12728
Case 2
○Element size:0.005
○Nodes:3142
○No of elements:14274
Case 3
○Element size:0.002
○Nodes:21330
○No of elements:105858
3 d view
case 1
Case 2
Case2
Mesh quality
The mesh quallity,it can be seen that in all the three case majority of the elements have 70% of quality
Case 1
Case 2
Case 3
Setup details
Solver type: Pressure based
Fluid: Air
The energy equation is enabled since simulation involves observing the variance in temperature.
Boundary conditions:
- Hot inlet velocity :3m/s
- Hot inlet temperature:36 °C.
- Cold inlet velocity :12m/s
- Cold inlet temperature:19 °C.
- Outlet pressure :0 gauge pressure.
- Turbulence Model: k-epsilon
- No of iterations:250
Results comparisons
Residual plot
Case 1
Case 2
Case 3
The is a huge deviation in each iteration in the first case the profile of each parameter is very sporadic and the amount of iteration it took is 120 following the second case with 110 and then finally the least amount taken is the case 3 with 100 iteration
Standard deviation outlet temperature
Case 1
Case 2
Case 3
The order of standard deviation of temperature is same as the Residual plot ie Case 1>>Case 2>>Case 1
Area average related temperature
Case 1
Case 2
Case 3
All the three cases gave nearly the same values
case 3:27.58°C
case 2:27.546°C
case 1:27.52°C
Temperature Contour
Case 1
Case 2
Case 3
The best thermal mixing out of all the three cases is displayed by the third case. It is clearly visible that in case 1 and case 2 there is large diffusion this is because of mesh being very coarse and so is improper thermal mixing.Well in case 3 the mesh is very fine that made the Temperature contour to showcase efficient thermal mixing
Velocity Contour
Case 1
Case 2
Case 3
The clarity in contour more in case 3 and depicts the phenomena way more lucid.Quality of depicts of physical phenomena in case 2 is less than case 3 but greater than the case 1
Temperature line plot
Case 1
Case 2
Case 3
Velocity contour
Case 1
Case 2
Case 3
The line plot of velocity and temperature displayed similar track as the with that of the contour plot so
Conclusion
The equation to get solved better and to have accurate results, it is necessary to use fine mesh, well the reason behind is that is the more no of element mean the capacity to capture information becomes high.
The finer the mesh the better is the display of the data and hence better is the simulation