Week 6 - CHT Analysis on a Graphics card
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.
Heat Transfer in a Solid - 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, proportional to the temperature gradient
Heat Transfer in a Fluid - 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 the compression which in-turn generates
the 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 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
modelling 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 modelling 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 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.
Geometry setup:
1. Use Spaceclaim to edit the geometry of the downloaded model of the graphics card which is in the enclosure.
2. Click on share prep to view any edges in interference so that conformal mesh can be achieved between different
components.
3. Share topology has to be enabled between the different components so that necessary information can be shared between
different zones of the mesh.
Mesh setup:
1. Before generating a base mesh, let's name the different components of the graphic card so it is easier to find them while
setting up fluent.
2. Base, processor and fins are basic name selections which will help us in the simulation.
3. Click generate mesh to create a base mesh, body sizing can be applied for the 3 solid components.
4. after creating body sizing for the 3 components, generate mesh as that it is considered as a base mesh having more than
1 lakh elements which help us in finding accurate solutions.
5. After creating the mesh, exit Mesh setup to simulate in fluent.
Fluent setup:
Setting up the physics :
Setting up the physics for CHT analysis on a graphics card in ANSYS fluent.
For this case we are using pressure-based steady state solver
Velocity formulation - Absolute
Model setup
Energy
Viscous - k-omega
Materials :
We are using different material for all the component
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 : steel
Density = 8050 kg/m^3
Specific heat = 502 j/kg-k
Thermal conductivity = 16.27 w/m-k
Setting up the source terms :
For this case we consider that, our processor is a source terms and it generating 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 enabled it and set the energy source to 1.
Calculation for the Energy source
Let the processor consume 83 W of power to work.
Dimension of the processor = 8*8*1 mm^3
So, Energy produced by the processor is 1296875000 w/m^3.
Inlet
Air is used as a fluid
Velocity = 1 m/sTemperature = 300 K
Outlet
Pressure = Gauge pressure (0 pa)
Results:
1. Base Mesh:
Inlet velocity= 1m/s
Mesh:
Main enclosure: 3.9mm
Fins size: 2mm
Processor: 1.5mm
Base: 2mm
Enclosure and graphic card:
Processor and Fins:
Base:
Mesh quality:
2. Plots:
1. Wall HTC and Max temperature of the processor:
2. Wall HTC at fins and base:
3. Potential hotspots at fins and base:
4. Wall HTC and max temperature of the graphic card:
5. Residuals and average temperature plot:
2. Refined mesh:
1. Mesh:
Main enclosure: 3.35mm
Fins size: 0.6mm
Processor: 0.2mm
Base: 0.8mm
Enclosure and graphic card:
Processor and Fins:
Base:
Mesh quality:
a. Inlet velocity= 1m/s
Plots:
1. Wall HTC and Max temperature of the processor:
2. Wall HTC at fins and base:
3. Potential hotspots at fins and base:
4. Wall HTC and max temperature of the graphic card:
5. Residuals and average temperature plot:
Maximum temperature: 1892K
Wall HTC: 264.8 W/m^2 K
Average of temperature: 1521.7 K
b. Inlet velocity: 2.5m/s
Plots:
1. Wall HTC and Max temperature of the processor:
2. Wall HTC at fins and base:
3. Potential hotspots at fins and base:
4. Wall HTC and max temperature of the graphic card:
5. Residuals and average temperature plot:
Maximum temperature of processor: 1192 K
Wall HTC of processor: 1341 W/m^2 K
Average of temperature: 921.97 K
c. Inlet velocity: 5m/s
Plots:
1. Wall HTC and Max temperature of the processor:
2. Wall HTC at fins and base:
3. Potential hotspots at fins and base:
4. Wall HTC and max temperature of the graphic card:
5. Residuals and average temperature plot:
Maximum temperature of processor: 902 K
Wall HTC of processor: 1341 W/m^2 K
Average of temperature: 675.6 K
Conclusion:
| Baseline - 1m/s | Refined -1m/s | Refined - 2.5m/s | Refined - 5m/s | |
| Max temperature Processor (K) | 1887 | 1892 | 1192 | 902 |
| Wall Heat transfer coefficient processor (W/m2K) | 264.8 | 1128 | 1341 | 1341 |
A converged solution for the given sets of input was observed on the basis of repetitive plots in the Residual plot. The
processor acted as a source of heat input and thus one of the hotspots for such study
With an increase in velocity, we saw a considerable drop in temperature and a substantial rise in heat transfer coefficient
which shows that high-velocity air can be an effective mode of heat dissipation in graphics card
From the temperature distribution, we can see hotspots in the fin and base near the surface that is in contact with the
processor. Based on the thermal conductivity of the material this temperature is distributed accordingly amongst the
component. We see a few high-temperature zones on fin away from processor depicting their high susceptibility to heat due
to their geometry.
Also, the difference in baseline and refined mesh is considerable and thus we can conclude that more refined mesh provides a
better solution and can be used in optimizing the design for such applications.From the residual plot, the change in the
gradients is very small with which we can conclude that the solution has converged.
From the temperature plot of the coarse mesh, the high-temperature points are found at fins, processor, and base area near
the processor. As the wall heat transfer coefficient is a wall phenomenon and fins dissipate a large amount of heat which
results in higher heat transfer co-efficient but the coarse mesh heat transfer for fins and other components in the graphics
card has the same values. Hence refinement of mesh is done for fins and base of the fin and base of the graphic card in order
to calculate the wall heat transfer coefficient at the fins and base.
The high-temperature regions are found at the center of the fins, base, and the processor walls. With further iterations, the
temperature is distributed to other regions in the graphics card in the direction of the inlet airflow. Conduction occurs where
there is a contact region between the solids in this case it is between processor and fins and processor and base. Convection
occurs when the heat generated in the components of the graphic card is removed by the inlet airflow. The maximum
temperature in the components is inversely proportional to the inlet airflow velocity. With the increase in the airflow velocity,
the heat removal process by convection is faster. And also recirculation of air (vortex) at appropriate places will increase the
heat transfer efficiencies hence greater amount of heat is removed by convection.