Week 6 - CHT Analysis on a Graphics card

Conjugate heat transfer analysis on a graphics card.

Objectives:

1. Run the simulation by varying the velocity from 1m/sec to 5m/sec for at least 3 velocities and discuss the results.
2. Find out the maximum temperature and heat transfer coefficient attained by the processor.
3. Prove that the simulation has achieved convergence with appropriate images and plots.
4. Identify potential hotspots on the model.

Introduction and Theory :

Conjugate heat transfer:

The Conjugate Heat Transfer (CHT) analysis type allows for the simulation of heat transfer between solid and fluid domains by exchanging thermal energy at the interfaces between them. Typical applications of this analysis type exist as, but are not limited to, the simulation of heat exchangers, cooling of electronic equipment, and general-purpose cooling and heating systems.

Examples:
HVAC, Heat Exchanger, Tank, Internal Combustion Engine, Heat Sink, Boiler, Reactor, Heat Pipe, Turbocharger.

Conduction:
Diffusion of heat due to temperature gradients in solids. A measure of the amount of conduction for a given gradient is heat conductivity. Conduction is described by Fourier’s law defining the conductive heat flux, q, as proportional to the temperature gradient.

Convection:
When heat is carried away by moving fluid. The flow can either be caused by external influences, forced convection, or by buoyancy forces, natural convection. Due to the fluid motion, there are three contributions to the heat transfer:

1. Convective contribution:
   Depending on the properties of the fluid and its region of flow, the domination of conduction and convection varies.
2. Viscous effects:
   Due to the fluid flow, the viscosity creates heat. This effect is often neglected due to its negligible value but should be taken into account for high-velocity cases.
3. Density effects:
   When the density becomes related to the temperature, the domain will have different densities at different locations based on the temperature distribution. This variation in density can cause compression which in-turn generates heat.

The contemporary conjugate convective heat transfer model was developed after computers came into wide use in order to substitute the empirical relation of proportionality of heat flux to temperature difference with the heat transfer coefficient which was the only tool in theoretical heat convection since the times of Newton. This model, based on a strictly mathematically stated problem, describes the heat transfer between a body and a fluid flowing over or inside it as a result of the interaction of two objects. The physical processes and solutions of the governing equations are considered separately for each object in two subdomains. Matching conditions for these solutions at the interface provide the distributions of temperature and heat flux along the body–flow interface, eliminating the need for a heat transfer coefficient. Moreover, it may be calculated using these data.

Applications:

Starting from simple examples in the 1960s, the conjugate heat transfer methods have become a more powerful tool for modeling and investigating natural phenomena and engineering systems in different areas ranging from aerospace and nuclear reactors to thermal goods treatment and food processing, from complex procedures in medicine to atmosphere/ocean thermal interaction in meteorology, and from relatively simple units to multistage, nonlinear processes. A detailed review of more than 100 examples of conjugate modeling selected from a list of 200 early and modern publications shows that conjugate methods are now used extensively in a wide range of applications. That also is confirmed by numerous results published after this book's appearance (2009) that one may see, for example, at the Web of Science. The applications in specific areas of conjugate heat transfer at periodic boundary conditions and in exchanger ducts are considered in two recent books.

Governing Equations:

Computational domain:

Names selections

Mesh setup:

1. For simplyfying the meshing process the fluent's robust meshing Platform is used.
2. An inital coarse mesh was created using default values
3. Later a refined mesh is also consdiderd for further simulations
4. After creating the mesh, exit the Mesh setup to simulate in fluent.

Coarse Mesh

Refined Mesh

The meshing Steps are given below

1 - import geometry

2 - Add local sizing if needed

3 - Generate surface Mesh

After surface mesh ensure a good skewness value is obtained.

4 - Describe geometry

5 - Update boundaries

6 - Create regions

7 - Update regions

8 - Add boundary layers

9 - Create Volume Mesh

Fluent setup:

Setting up the physics:

Setting up the physics for CHT analysis on a graphics card in ANSYS fluent.

• Pressure-based steady-state solver.
• Velocity formulation – Absolute
• Turn on Energy
• Viscous – SST K omega

Assigning materials :

For fluid: Air

• Density = 1.225 kg/m^3
• Viscosity = 1.7894e-05 kg/ms

For Fins: copper

• Density = 8978 kg/m^3
• Specific heat = 381 j/kg-k
• Thermal conductivity = 387.6 w/m-k

For Processor: Silica

• Density = 2328 kg/m^3
• Specific heat = 710 j/kg-k
• Thermal conductivity = 150 w/m-k

For Base: User-defined material - FR4

• Density = 1850 kg/m^3
• Specific heat = 1150 j/kg-k
• Thermal conductivity = inplane 10 w/m-k, through plane 1 w/mk

Setting up the source terms :

For this case, we consider that our processor is a source term and it generates heat. So, for setting up the source term go to Zones - Cell zones - and click on the processor for editing which is in the Solid. After that select the material to gold and click on the source terms to enable it and set the energy source to 1. an arbitrary value of 1296875000 W/m3 was selected as the volumetric heat generation which corresponds to 83W power for the processor.

Boundary Conditions:

Inlet: Velocity inlet: 1,3,5 m/s

Outlet: Pressure outlet: Gauge Pressure : 0

Results:
Case 0 - Coarse Mesh, Inlet Velocity = 1 m/s:

Convergence plot

Hotspot Regions

Wall Heat Transfer Coefficient

mid plane plots

Case 1 - Refined Mesh, Inlet Velocity = 1 m/s:

Convergence plot

Hotspot Regions

Wall Heat Transfer Coefficient

mid plane plots

Case 2 - Refined Mesh, Inlet Velocity = 3 m/s:

Convergence plot

Hotspot Regions

Wall Heat Transfer Coefficient

mid plane plots

Case 3 - Refined Mesh, Inlet Velocity = 5 m/s:

Convergence plot

Hotspot Regions

Wall Heat Transfer Coefficient

mid plane plots

Summary

Case	Velocity [m/s]	The temperature at Processor [K]	The temperature at Fins [K]	HTC at Processor side walls [W/m^2K]	HTC at Fins [W/m^2K]
0	1	515.14034	512.68823	4.5098762	16.853292
1	1	514.45053	512.00305	4.5480367	16.876224
2	3	412.7818	409.95287	7.9240839	35.633422
3	5	384.11579	381.2093	14.263403	48.677611

CONCLUSION

1. As the number of elements increases the accurate results of temperature distribution is obtained
2. From the above table, it is fairly notable that, the net temperature of components of graphics cards decreases with an increase in inlet velocity.
3. Hence it can be inferred that a higher inlet velocity results in better cooling and lower the average temperature thus keeping the components safe from damage.
4. Furthermore, it can be observed that the temperature of components increases as the inlet velocity decreases from 5 m/s to 1m/s, also proving that higher velocity results in better cooling.