Project

Conjugate Heat Transfer Simulation using Converge CFD

Aim- To study the conjugate heat transfer flow through a cylindrical pipe and to perform a grid dependence test. Also to study the effect of super-cycling stage interval on simulation results.

Governing equation- The equation used to solve this case is Navier-Stokes Unsteady equations. It comprises of 5 equations continuity, x-momentum, y-momentum, z-momentum, and energy equation.

Objective- The objective of this problem is to simulate fluid flow passing through a heated hollow aluminium cylinder.

Description- First the geometry to be simulated is created in Converge Studio and then the geometry is checked for any errors. The geometry is grouped into faces so that respective boundary conditions can be assigned and then the case setup is done. This is a transient simulation with end time 0.5sec. It is a turbulent flow simulation hence the RNG k-epsilon turbulence model is selected. The mesh size used is 2e-3m, 3e-3m, and 4e-3m in all directions. In this project, we are using a super-cycling stage interval of 0.05s, and so on. In the super-cycling method, the fluid solver is paused for some time allowing the solid solver to catch up.

Geometry-Cylinder lenght - 0.2m

OD - 0.02m

ID - 0.015m

Material- Fluid: Air

Solid: Aluminium

Boundary Condition-Inlet: Velocity 7.32m/s

Outlet: Pressure 101325 Pa

Solid outer wall: 10000 W/m2

Solid wall: Fixed wall no slip.

Interface: Forward boundary for the fluid region and reverse boundary for solid region.

Initial Condition- Pressure: 101325 Pa and temperature:300K

Mesh

2e-3m

3e-3m

4e-3m

Results-

Cell count

From the above line plot, it is clear that as the mesh size decreases the cell count increases.

Temperature comparison

From the above plot, we can see that the airflow gets heated up gradually as it moves through the pipe until the outlet, the temperature ranges from 356K to 361K for different mesh sizes.

For 2e-3m

Pressure

From the pressure plot, it is clear that the flow is taking place from left to right i.e inlet to outlet and no reverse flow is occurring.

Temperature

The temperature plot confirms the average temperature line plot which shows that the temperature of air increases as it moves towards the outlet.

Velocity

From the above velocity plot, we can see that the velocity increases as the air flows from inlet to outlet this is because of the increase in temperature along the pipe.

Y+

As the mesh becomes finer the y+ decreases.

For3e-3m

Pressure

From the pressure plot, it is clear that the flow is taking place from left to right i.e inlet to outlet and no reverse flow is occurring.

Temperature

The temperature plot confirms the average temperature line plot which shows that the temperature of air increases as it moves towards the outlet.

Velocity

From the above velocity plot, we can see that the velocity increases as the air flows from inlet to outlet this is because of the increase in temperature along the pipe.

Y+

For 4e-3m

Pressure

From the pressure plot, it is clear that the flow is taking place from left to right i.e inlet to outlet and no reverse flow is occurring.

Temperature

The temperature plot confirms the average temperature line plot which shows that the temperature of air increases as it moves towards the outlet.

Velocity

From the above velocity plot, we can see that the velocity increases as the air flows from inlet to outlet this is because of the increase in temperature along the pipe.

Y+

Conclusion

From the above graphs and plots, it can be concluded that the temperature at the outlet are very close to one another. So the solution is not grid-dependent.

To determine the effect of the super-cycling stage interval on simulation time, the simulation was performed with 3 super-cycling stage intervals 0.01s, 0.02s and 0.03s.

For 0.01s super-cycling stage interval, the simulation time is 597.19sec.

For 0.02s super-cycling stage interval, the simulation time is 593.36sec.

For 0.03s super-cycling stage interval, the simulation time is 591.35sec.

So from the above trend, we can see that as the super-cycling stage interval increases the simulation time decreases.

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