Mixing efficiency

Objective: To perform steady-state simulations on the mixing tee geometry

In a table, compare the following values from the 3 cases.

• Cell count
• Average outlet temperature
• Number of iterations for convergence

Expected results:

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

For each simulation, show the convergence plot.

Given:

Temperature:

Cold inlet temperature:19⁰C.

Hot inlet temperature:36⁰C

Velocity:

hot inlet velocity=3m/s.

⋆Momentum Ratio= Velocity at Cold inlet/Velocity at Hot inlet

We have two different geometries of mixing Tee.

• Short mixing_tee:

• Long mixing_tee:

Theory:

Mixing problems, such as the design and scale-up of a mixer and quantification of mixing,
have been traditionally tackled by developing empirical design equations mainly due to the
the complexity of the fluid dynamics of mixing. Although this approach has proven to be
satisfactory for many applications, it is rather limited because it neglects the complexity of
flow in most mixing applications.

Applications: Mixing Tees are ideal for microbore or analytical gradient HPLC. These mixing tees are specifically designed for high-pressure applications.

Case setup:

Click on Project schematic. Drag and drop Fluid Flow (Fluent) onto Project Schematic.
Here, we will see the list of tasks we need to perform to solve a particular engineering system from a CFD standpoint.

Task and associated applications are given below:
1. Geometry- Spaceclaim> where we import, volume extraction, and suppress for physics will be done.
2. Mesh- Ansys Mesh>where Boundary naming, element size, and mesh generation on extracted fluid volume done.
3. Setup- Ansys Fluent> where the actual case setup is 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 k-epsilon and k-omega sst model--------

Cad cleanup:

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

As we can see above figure is the Solid model, since we are interested in performing Fluid flow analysis through the geometry it will be unnecessary to use this solid model unless we are interested in doing the Heat transfer problem. Hence, We need to extract fluid volume from the geometry. Spaceclaim provides lots of options to extract fluid volume.

How to extract volume??????

Prepare→Volume Extraction→Select Edge option→Make Edge Selection→Click on Complete→Uncheck Solid from Structure..

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Suppress for physics: To make sure that solid components of geometry not to be involved in the mesh generation process we use suppress for physics option where the solid part will be suppressed.

Mesh generation:

The size of the mesh element, which we are going to consider is 1.5e-3, due to limitations imposed by the academic license of Ansys on nos. of tetrahedral cells.

Naming the boundaries is done here in Ansys Mesh before generating mesh.

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

Mesh quality check :

Fluent setup:

At first, check the quality of the mesh before proceeding further.

Fluent setup

Before proceeding for the solution, Its Initialized by the Hybrid Initialization.

Results:

Residual Plots:

K-EPSILON

K-Epsilon model

The standard deviation of the K-epsilon model

Area weighted average temperature of K-epsilon

Temperature contour plot of the K-epsilon model

Velocity contour plot of the K-epsilon model

K-OMEGA SST

K-omega SST model

Area weighted average temperature of K-omega model

Standard deviation Temperature of K-omega model

Temperature contour plot for K-omega model

Velocity contour plot for K-omega model

Summary:

• From the above plots, we can say that the end results of both K-omega and K-epsilon model are almost the same.
• NO. of iterations for K-omega SST and K-epsilon model is the same, but K-omega has less accurate. Also, we can observe a lot of diffusions in a contour plot of the K-omega model.
• Hence for the rest of the cases, we will consider the K-epsilon model for greater accuracy and faster convergence rate.

• CASE1:

Cad cleanup will be the same as the previous case.....

Mesh generation

Mesh check quality

Fluent Setup:

• Short Tee MR-2,Hot inlet Velocity 3m/s

Momentum ratio=2,Hot inlet velocity=3m/s,Hot inlet temperature=36⁰C

Cold inlet velocity=6m/s, Cold inlet tempertaure=19⁰C

Results:

Residual plots:

K-epsilon model

Temperature contour plot

Velocity contour plot

• Short Tee MR-4, Hot inlet Velocity 3m/s

Momentum ratio=4,Hot inlet velocity=3m/s,Hot inlet temperature=36⁰C

Cold inlet velocity=12m/s, Cold inlet tempertaure=19⁰C

Results:

Residual plots

Temperaature contour plot:

Velocity contour plot:

• Case2:

Cad Cleanup:

Long mixing tee volume extraction

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Extracted fluid volume

Mesh generation:

The element size will be going to consider for the case study is 1.5e-3.

Mesh quality:

Fluent Setup:

• Long Tee MR-2,Hot inlet Velocity 3m/s

Momentum ratio=2,Hot inlet velocity=3m/s,Hot inlet temperature=36⁰C

Cold inlet velocity=6m/s, Cold inlet tempertaure=19⁰C

Results:

Residual plots:

K-epsilon model

Temperature contour plot

Velocity contour plot

• Long Tee MR-4, Hot inlet Velocity 3m/s

Momentum ratio=4,Hot inlet velocity=3m/s,Hot inlet temperature=36⁰C

Cold inlet velocity=12m/s, Cold inlet tempertaure=19⁰C

Results:

Residual plots:

K-epsilon model

Temperature contour plots

Velocity contour plots

Conclusion:

Hence, we successfully studied a case study of a given model and are summarised in the below table:

	Short Tee		Long Tee
	MR-2	MR-4	MR-2	MR-4
Cell counts	211573	211573	288241	288241
Avg outlet temp	30.31	27.56	30.42	27.47
No. of iterations	170	180	140	160

• Since we are interested only in the fluid volume, the Average outlet temperature on case1 for MR2 is more(30.31 deg c) irrespective of mixing tee lengths.

• Momentum ratio plays a quite important role in mixing effectiveness. Increased inlet cold velocity improves the mixing ability. Hence, we got the desired output temperature as we can observe in the above table. The area-averaged temperature at the outlet we found in Case-2 is somewhat lower than we found in the other cases. But it takes more numbers of iterations to achieve convergence.