Mixing Tee Efficiency

Mixing Tee Efficiency

Objective: For this challenge, we have created two versions of the mixing tee. One of them is longer than the other.

Your 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.

1. Case 1
   • Short mixing tee with a hot inlet velocity of 3m/s.
   • Momentum ratio of 2, 4.
2. Case 2
   • Long mixing tee with a hot inlet velocity of 3m/s.
   • Momentum ratio of 2, 4.

Momentum ratio = velocity at cold inlet / velocity at hot inlet

In a table, compare the following values from the 2 cases.

1. Cell count
2. Average outlet temperature
3. Number of iterations for convergence

Expected results:

1. Velocity and temperature contour plots on the cut planes along and across the pipe.
2. Velocity and temperature line plots along and across the length of the pipe.
3. Perform Mesh independent study for any one case.
4. Discuss the effect of length and momentum ratio on results.

For each simulation, you need to show the convergence plot

Aim: The function of mixing Tee is to provide proper mixing of quantities to get the desired result at the outlet.

In the above figure, by controlling the velocity of the chilled air, one can get the desired temperature in the room.

Steps in Simulation:

Open Ansys Workbench. Drag and drop Fluid Flow (Fluent) onto Project Schematic.

Here, we will see Steps we need to follow to solve a particular engineering system from a CFD standpoint.

1. Geometry: Spaceclaim, where we import the geometry, volume extraction and subpress for physics will be done.
2. Mesh: Ansys Mesh, where Boundary naming, element sizing and mesh generation with required grid size will be done.
3. Setup: Ansys Fluent, where actual case setup will be done.
4. Solution: Ansys Fluent, where runtime results visualization done.
5. Results: CFD-Post, where Post Processing of Results will be done.

Short Tee with Steady-State Model:

1) CAD Cleanup:

Import Short Tee geometry into Spaceclaim, Spaceclaim is CAD cleanup software that can be used to prepare CAD models for simulation setup. It could be for CFD or FEA.

As we can see above figure is the Solid model, since we are interested in performing Fluid Flow analysis through the geometry, hence we have extracted fluid volume from the Geometry. Spaceclaim provides lots of option to extract the Geometry.

We have used option Subpress for Physics to make sure that solid component of geometry not to be involved in thr Mesh generation process.

2) Mesh generation:

Boundary naming is done in Ansys Mesh before Mesh generation.

Mesh Generation and element quality check is as below:

Make sure element metrics or element quality should not be lower than 5%.

3)Fluent Setup:

CASE 1

• Short mixing tee with a hot inlet velocity of 3m/s.
• Momentum ratio of 2

SETUP	Short TEE (MR=2 & Inlet Hot Velocity=3m/s)
	K-epsilon	K-omega
Solver Type	Pressure Based	Pressure Based
Velocity Formulation	Absolute	Absolute
Time	Steady	Steady
Viscous Model	Realizable k-epsilon with standard wall function	k-omega SST model
Material	Air	Air
Cell zones Volume_volume	Fluid type: Air	Fluid type: Air
Boundaries	Inlet x (velocity inlet) Velocity Magnitude 3m/s Temperature – 36 degree c. Inlet y (velocity inlet) Velocity Magnitude 6m/s Temperature – 19 degree c. Outlet x (Pressure outlet) Gauge Pressure – 0 pas. Walls – Stationary walls	Inlet x (velocity inlet) Velocity Magnitude 3m/s Temperature – 36 degree c. Inlet y (velocity inlet) Velocity Magnitude 6m/s Temperature – 19 degree c. Outlet x (Pressure outlet) Gauge Pressure – 0 pas. Walls – Stationary walls

Before proceeding the simulation the solution is being initialize by Hybrid Initialization.

4) Results:

For K-omega model:

Residuals Plot

Iterations taken to Converge: 225(approximately)

Average weighted area Plot to find the outlet Temperature

The above Plot shows that the Temperature of the Mixture at Outlet is 300.5 Kelvin.

Standard Deviation Plot to find the Effictiveness of Mixing at the outlet

Line Plot (This can be done by selecting subline option)

1)For Temperature distribution

2)For Velocity Distribution

Contour Plots

1)For Temperature distribution

2)For Velocity Distribution

For K-epsilon model:

Residuals Plot

Average weighted area Plot to find the outlet Temperature

Standard Deviation Plot to find the Effectiveness of Mixing at the outlet

Line Plot (This can be done by selecting streamline option)

1)For Temperature distribution

2)For Velocity Distribution

Contour Plots

1)For Temperature distribution

2)For Velocity Distribution

Summary:

	Short Tee (MR=2)
	k-epsilon	k-omega
Cell count	42664	42664
Avg. Outlet Temperature	303.5k	300.5 kelvin
Standard Deviation	1.8	3.5
No of Iterations	150 (approximately)	225 (approximately)

Short mixing tee with a hot inlet velocity of 3m/s. Momentum ratio of 4

SETUP	Short TEE (MR=4 & Inlet Hot Velocity=3m/s)
	K-epsilon	K-omega
Solver Type	Pressure Based	Pressure Based
Velocity Formulation	Absolute	Absolute
Time	Steady	Steady
Viscous Model	Realizable k-epsilon with standard wall function	k-omega SST model
Material	Air	Air
Cell zones Volume_volume	Fluid type: Air	Fluid type: Air
Boundaries	Inlet x (velocity inlet) Velocity Magnitude 3m/s Temperature – 36 degree c. Inlet y (velocity inlet) Velocity Magnitude 12m/s Temperature – 19 degree c. Outlet x (Pressure outlet) Gauge Pressure – 0 pas. Walls – Stationary walls	Inlet x (velocity inlet) Velocity Magnitude 3m/s Temperature – 36 degree c. Inlet y (velocity inlet) Velocity Magnitude 12m/s Temperature – 19 degree c. Outlet x (Pressure outlet) Gauge Pressure – 0 pas. Walls – Stationary walls

Before proceeding the simulation the solution is being initialized by Hybrid Initialization.

4) Results:

For K-omega model:

Residuals Plot

Iterations taken to Converge: 150(approximately)

Average weighted area Plot to find the outlet Temperature

The above Plot shows that the Temperature of the Mixture at Outlet is 300.5 Kelvin.

Standard Deviation Plot to find the Effictiveness of Mixing at the outlet

Line Plot (This can be done by selecting subline option)

1)For Temperature distribution

2)For Velocity Distribution

Contour Plots

1)For Temperature distribution

2)For Velocity Distribution

For K-epsilon model:

Residuals Plot

Iterations to Converge the solutions= 75 (Approximately)

Average weighted area Plot to find the outlet Temperature

Outlet Temperature after mixing is 301 kelvin(Approximately)

Standard Deviation Plot to find the Effectiveness of Mixing at the outlet

Standard Deviation is 1(Approximately). That means mixing is Good.

Line Plot (This can be done by selecting streamline option)

1)For Temperature distribution

2)For Velocity Distribution

Contour Plots

1)For Temperature distribution

2)For Velocity Distribution

Summary:

	Short Tee (MR=4)
	k-epsilon	k-omega
Cell count	45840	45840
Avg. Outlet Temperature	300.5k	300.5 kelvin
Standard Deviation	1	1
No of Iterations	75 (approximately)	150 (approximately)

Conclusion:

1) For Momentum Ratio 2 and 4, the Standard Deviation of the k-epsilon model is lower than the k-omega model. Hence the k-epsilon model has better mixing efficiency than the k-omega model

2) For Momentum Ratio 2 and 4, the k-epsilon model takes less number of iterations than the k-omega model. Hence the K-epsilon model is faster to Converge the solutions.

From the above two conclusions the K-epsilon model has not only more accurate but also takes less computation time to converge. Therefore, we can use the k-epsilon model for future calculations.

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Fluent Setup:

CASE 2

• Long mixing tee with a hot inlet velocity of 3m/s.
• Momentum ratio of 4.

Long Tee with Steady-State Model:

1) CAD Cleanup:

Import Short Tee geometry into Spaceclaim, Spaceclaim is CAD cleanup software that can be used to prepare CAD models for simulation setup. It could be for CFD or FEA.

As we can see above figure is the Solid model, since we are interested in performing Fluid Flow analysis through the geometry, hence we have extracted fluid volume from the Geometry. Spaceclaim provides lots of option to extract the Geometry.

We have used option Subpress for Physics to make sure that solid component of geometry not to be involved in thr Mesh generation process.

2) Mesh generation:

Boundary naming is done in Ansys Mesh before Mesh generation.

Mesh Generation and element quality check is as below:

Make sure element metrics or element quality should not be lower than 5%.

4) Results:

For K-epsilon model:

Residuals Plot

Iterations to Converge: 100(Approximately)

Average weighted area Plot to find the outlet Temperature

The outlet mixing temperature is 300.5 kelvin

Standard Deviation Plot to find the Effectiveness of Mixing at the outlet

Standard Deviation is 0.9 (Approximately)

Line Plot (This can be done by selecting streamline option)

1)For Temperature distribution

2)For Velocity Distribution

Contour Plots

1)For Temperature distribution

2)For Velocity Distribution

Summary:

	Long Tee (MR=4)
	k-epsilon	k-omega
Cell count	72260	---
Avg. Outlet Temperature	300.5k	---
Standard Deviation	0.9	---
No of Iterations	100 (approximately)	---

Short mixing tee with a hot inlet velocity of 3m/s. Momentum ratio of 2

Before proceeding the simulation the solution is being initialized by Hybrid Initialization.

4) Results:

For K-epsilon model:

Residuals Plot

Iterations to Converge the solutions= 250 (Approximately)

Average weighted area Plot to find the outlet Temperature

Outlet Temperature after mixing is 303.5 kelvin(Approximately)

Standard Deviation Plot to find the Effectiveness of Mixing at the outlet

Standard Deviation is 1(Approximately). That means mixing is Good.

Line Plot (This can be done by selecting streamline option)

1)For Temperature distribution

2)For Velocity Distribution

Contour Plots

1)For Temperature distribution

2)For Velocity Distribution

Summary:

Summary of Comparison between Momentum Ratio 2 and 4:

Parameter	MR=4	MR=2
Cell counts	2,01,537	2,01537
No. of iterations	100	100
Standard Deviation	0.9	1.3
Outlet temperature	300.5 k	303.5 k

Conclusion:

• A short Tee is preferred rather than Long Tee because Short tee has better mixing efficiency and low outlet Temperature than long Tee.
• The Tee Mixing Effectiveness increases when the velocity of the cold inlet fluid increases. Hence Momentum Ratio 4 has better effectiveness than 2.
• The outlet Temperature is also decreasing when the Momentum Ratio increases.
• Hence Momentum Ratio=4 is preferred over Momentum Ratio=2 due to the above-mentioned reasons.
• From the Grid independence test, we can conclude that the finer the size of the mesh, the better the accuracy of the solution. This is because the size of the cells decreases and the number of cells increases, and error is linearly proportional to the cell size, so the error also decreases. Hence at the finer grid size, we got better mixing efficiency. But at the same time, computational time increases significantly.

Animation Video:

https://youtu.be/Dw6LARdLiuA