Project 1- Conjugate Heat Transfer Analysis on a graphics card.

• Objectives :

  1. Find out the maximum temperature attained by the processor.

  2. Prove that the simulation has achieved convergence with appropriate images and plots.

  3. Find out the heat transfer coefficient at appropriate areas of the model.

  4. Identify potential hotspots on the model.

• Inroduction :

The analysis of heat transfer of solid and liquid domains by exchange of thermal energy at the interfaces between them is called as Conjugate Heat Transfer Analysis. Heat transfers in solids occur by conductions while in liquids it occurs by convection. At solid-liquid interface heat transfer takes place by convection. CHT analysis is used in simulation of heat exchangers, engine equipments, cooling of electronic equipment and general purpose heating and cooling systems. CHT analysis provides temperature distribution in solid and liquid interface. It also provides velocity and pressure distribution of the liquid inside the solid. Results of CHT analysis become input to structural simulations as thermal loads. Conjugate heat transfer (CHT) analysis can accurately predict heat transfer by simultaneous solving all the relevant solid and flow field heat transfer processes. The CHT approach has an advantage over Finite Element thermal analysis in that wall heat transfer coefficients and their local variations on surfaces are directly calculated within the model rather than based on simplified empirical calculations. The CHT approach therefore has benefits for those applications where heat transfer is either non-uniform or difficult to calculate empirically.

• Geometry :

This is a standard design of a graphics card setup. It contains three essential components namely processor, fins and base. The heat is generated in processor core and fins are used for heat disipation to avoid overheating of processor. The base board supports remaining small components over it. An rectangular enclosure is created across the graphics card assembly. This enclosure helps us in visualizing the fluid flow across the domain. Share topology is enabled as we need to run the simulation for conjugate heat transfer. The following are the images of different components indiviually and assembled together :

Figure shows the processor of graphics card.

Figure shows the fins of graphics card.

Figure shows the base board of graphics card.

Figure shows the assembly of graphics card.

Figure shows the enclosure around the graphics card.

• Case Setup :

1. Steady State Solver with absolute velocity.
2. K-epsilon standard viscous model with energy equation.
3. Materials : Fluid - Air; Solid - Aluminium, Copper and Gold.
4. For solid components : Processor - Gold; Fins - Copper; Base - Aluminum.
5. Heat Source : In this case processor is the heat generating component. So we have to give it a source term. In cell zones select processor and select gold as the material and select source term. As the size of processor is small i.e 64mm^3, we assume the power of 10 watt is consumed by the processor to run. So 10/(64*10^9) W/m^3 = 1.5625e8 W/m^3 is the heat generated. Enter this value as the heat source term for processor.
6. Boundary Conditions : Inlet - Velocity = 5 m/s.

Outlet - Pressure = 0 Pa.

Wall - Symmetry.

Processor - No slip wall.

• Case I :

Element size - 10.28 mm.

Number of Nodes - 15732.

Number of Elements - 84083.

Number of Iterations - 500.

Figure of the baseline mesh generated for case 1.

Figure of conformal mesh between solid and fluid interface.

• Plots -

Plot of residuals for case 1.

Temperature contour of whole graphics card assembly.

Temperature contour of processor.

Temperature contour of fins.

Temperature contour of base.

Temperature contour over a plane inside the enclosure.

Velocity contour over a plane inside the enclosure.

Wall heat transfer coefficient contour.

Wall heat tranfer coefficient contour zoomed in near the graphics card.

• Results : Case I

1. Maximum Temperature attained by the processor is 359.8 K.
2. The simulation has reached convergence after 125 iterations. As the plot of residuals clearly shows a repetitive pattern and the tempertaure doesn\'t rise after that point.
3. Heat transfer coefficient is maximum near walls.
4. Hotspot in ths case is processor as it is the only heat generating componnent.

• Case II :

Element size - 4 mm.

Body Sizing - 0.6 mm.

Number of Nodes - 86219.

Number of Elements - 491689.

Number of Iterations - 500.

Fine mesh generated using body sizing option for case 2.

Conformal mesh at solid and fluid interface for case 2.

• Plots:

Plot of residuals for case 2.

Temperature contour of graphics card assembly for case 2.

Temperature contour of processor for case 2.

Temperature contour of fins for case 2.

Temperature contour of base for case 2.

Temperature contour plotted over a plane inside the enclosure.

Velocity contour plotted over a plane inside the enclosure.

Wall heat transfer coefficient contour.

Wall heat tranfer coefficient contour zoomed in near the graphics card.

• Results : Case II

1. Maximum Temperature attained by the processor is 343.8 K.
2. The simulation has reached convergence after 130-140 iterations. As the plot of residuals clearly shows a repetitive pattern and the tempertaure doesn\'t rise after that point.
3. Heat transfer coefficient is maximum near walls.
4. Hotspot in ths case is processor as it is the only heat generating componnent.

• Conclusion :

1. Mesh refining visibly impacts the results as the values of temperature and velocity vary in both cases.
2. Computational time taken for second case is much more than that of required for first case.
3. The processor and its components can work without facing issues of heating if operated with 10 W.
4. The fins made up of copper do good work for heat dissipation.
5. Increase in velocity of air will help in faster cooling of the graphics card.