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STEADY STATE CONJUGATE HEAT TRANSFER (CHT) ANALYSIS ON A MODEL OF A GRAPHICS CARD USING ANSYS FLUENT …
Ramkumar Venkatachalam
updated on 29 Jan 2022
STEADY STATE CONJUGATE HEAT TRANSFER (CHT) ANALYSIS ON A MODEL OF A GRAPHICS CARD USING ANSYS FLUENT
Our aim is to simulate a steady state conjugate heat transfer (CHT) analysis on a model of graphics card by appropriately choosing the materials of components of a graphics card using ANSYS FLUENT.
ANSYS FLUENT academic version CFD package is used to carry out the simulation. It is a user friendly interface which provides high productivity and easy-to-use workflows. Workbench contains all workflow needed for solving a problem such as pre-processing, solving and post-processing.
Structure of ANSYS FLUENT simulations
The basic steps for a simulation are as follows,
Conjugate Heat Transfer
Conjugate heat transfer is a combination of conduction and convection. It’s a heat transfer which involves the interaction of conduction within a solid body and convection between the solid surface and fluid volumes.
Typical example is a heat exchanger as in the figure the cold fluid enters the tubes and takes heat from the hot air flowing around the tube via natural convection. Some of the applications which involve conjugate heat transfers are building roofs, open water, chimney etc.
Heat Transfer Coefficient (HTC)
It’s a measure of convective heat transfer between fluid volume and solid medium around which the fluid flows.
Heat transfer coefficient is defined by the newton’s law of cooling. It is proportionality constant between heat flux (q) and temperature difference (ΔT) between the solid medium and the surrounding fluid. The SI unit of heat transfer coefficient (HTC) is watts per square meter kelvin (W/m2K).
For convective heat transfer coefficient calculation, usually T2 is temperature of the solid surface and T1 is temperature of the fluid around the surface or we can also call it as reference temperature. The choice of reference/ fluid temperature is important as the temperature near and away from the wall would be different depending on the flow due to thermal boundary layer.
There are two heat transfer coefficient for a flow through a pipe i.e. Internal HTC and External HTC
For External flows, fluid temperature will be the free stream temperature.
For Internal flow, fluid temperature will be the mass flow average temperature as the temperature profile inside a tube will be parabolic.
Nusselt Number
It is the ratio of convective heat transfer to the fluid heat conduction heat transfer under the same conditions.
Nu = qconvection /qconduction
Convective heat transfer, qconvection = h*ΔT,
where h = Convective heat transfer coefficient, ΔT = Temperature difference
Conductive heat transfer, qconduction = (k*ΔT)/ L,
where k = Thermal Conductivity of the fluid, ΔT = Temperature difference, L = characteristic length.
So, Nusselt Number, Nu = h*L
k
Nusselt Number is also a function of Reynolds number and Prandtl number.
Dittus-Boelter equation – It’s an equation to calculate the Nusselt number for internal turbulent flow.
Graphics card and its components
Fig: Fins Fig: Processor
Fig: Base
Fig: Graphics card Model and its components
Problem – CHT analysis on a Model of Graphics Card
Steady state CHT analysis on a model of Graphics card by varying the flow velocities from 1m/s to 5m/s with processor as the constant energy source and discuss the results.
Calculation
Reference values – Graphics Card
Processor Dimension = 8x8x1 mm3 Wall Dimension for convection = 8x1 mm2
Steady State Simulation
Fluid Zone
Fluid chosen for the problem – Air
Density = 1.225 kg/m3, Cp (Specific Heat) = 1006.43 j/kg-k, Thermal Conductivity = 0.0242 W/m-k
Solid Zone - Materials chosen for each component of graphics card
Base - Aluminum (Al)
Density = 2719 kg/m3, Cp (Specific Heat) = 871 j/kg-k, Thermal Conductivity = 202.4 W/m-k
Fins - Copper (Cu)
Density = 8978 kg/m3, Cp (Specific Heat) = 381 j/kg-k, Thermal Conductivity = 387.6 W/m-k
Processor – Silicon (Si)
Density = 2328 kg/m3, Cp (Specific Heat) = 710 j/kg-k, Thermal Conductivity = 150 W/m-k
Inputs
Constant Energy Source (Processor) = 10 / 0.000000064 (Assumption = 10 W)
= 156250000 W/m3
3. PROCEDURE
4. NUMERICAL ANALYSIS (Software used – ANSYS 2018 R1)
The 3D geometry of Graphics Card is imported in SpaceClaim and the cleanup is done as per the figure given below.
3D Geometry with the flow domain – Ahmed Body
Fig: Baseline Mesh
Fig: Element Quality
Fig: Final Mesh for the complete domain
Fig: Element Quality
Fig: Boundaries for the complete domain
Fig: Boundaries for the graphics card model
4. Energy equation was switched on for the analysis process as we are interested in temperature of the system.
5. k-omega SST turbulence models were used for the analysis.
6. The fluid material chosen is air.
7. The surface of the solid volume is chosen as Aluminum, Copper and Silicon.
8. Convergence and monitor are checked for absolute criteria of 0.001 for all the residuals.
9. Solution methods – SIMPLE Scheme used for Pressure-Velocity coupling and the methods for Spatial Discretization are as per the below image.
10. Hybrid initialization is done and numbers of iterations are set for running the steady simulation.
11. Temperature contours are set in order to monitor the variation during run time.
12. Reference Values such as respective velocities, Area = 0.000032 mm2 and temperature = 300 K are set.
Initial Setup and Boundary Condition
Zone |
Type |
Boundary Condition |
Additional conditions (if any) |
Inlet |
Velocity - Inlet |
Velocity – 1, 3, 5 m/s |
Steady State, Pressure Based, Absolute
Switched ON Energy equation
Turbulence Model – k-omega SST |
Outlet |
Pressure - Outlet |
Gauge pressure of 0 Pa |
|
Symmetry |
Symmetry |
Symmetry |
|
Wall |
Wall |
Stationary wall without slip |
Fig. Cell Zone Conditions & Boundaries
Fig. Inlet Boundary – Velocity – 5m/s
Fig. Wall Boundary – Energy Source
5. RESULTS
Fig: Convergence Criteria – Residual
Fig: Velocity Contour on Plane
Fig: Velocity Vector on Plane
Fig: Maximum Temperature of the Processor
Fig: Potential Hotspots of the Model
Fig: Maximum Surface HTC of the Processor
Fig: Convergence Criteria – Residual
Fig: Velocity Contour on Plane
Fig: Velocity Vector on Plane
Fig: Maximum Temperature of the Processor
Fig: Potential Hotspots of the Model
Fig: Maximum Surface HTC of the Processor
Fig: Convergence Criteria – Residual
Fig: Velocity Contour on Plane
Fig: Velocity Vector on Plane
Fig: Maximum Temperature of the Processor
Fig: Potential Hotspots of the Model
Fig: Maximum Surface HTC of the Processor
Comparison between all three cases
6. CONCLUSION
7. REFERENCES
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