Conjugate heat transfer CHT analysis on computer graphics card by using Ansys Fluent

Aim: Conjugate Heat Transfer (CHT) analysis on a computer graphics card.

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.

Introduction:

The term conjugate heat transfer is used to describe processes which involve variations of temperature within solids and fluids, due to thermal interaction between the solids and fluids. A typical example is the heating or cooling of a solid object by the flow of air in which it is immersed.

Conjugate heat transfer corresponds with the combination of heat transfer in solids and heat transfer in fluids. In solids, conduction often dominates whereas in fluids, convection usually dominates. Conjugate heat transfer is observed in many situations. For example, heat sinks are optimized to combine heat transfer by conduction in the heat sink with the convection in the surrounding fluid.

Heat Transfer by Solids and Fluids:

1. Heat Transfer in a Solid

In most cases, heat transfer in solids, if only due to conduction, is described by Fourier’s law defining the conductive heat flux, q, proportional to the temperature gradient:

`Q = - K*A*ߡ.T`

For a time-dependent problem, the temperature field in an immobile solid verifies the following form of the heat equation:

`ρCp ( ∂T)/(∂t) = ∇.(k∇T)+Q`

2 . Heat Transfer in a Fluid

Due to the fluid motion, three contributions to the heat equation are included:

1. The transport of fluid implies energy transport too, which appears in the heat equation as the convective contribution. Depending on the thermal properties on the fluid and on the flow regime, either the convective or the conductive heat transfer can dominate.
2. The viscous effects of the fluid flow produce fluid heating. This term is often neglected, nevertheless, its contribution is noticeable for fast flow in viscous fluids.
3. As soon as a fluid density is temperature-dependent, a pressure work term contributes to the heat equation. This accounts for the well-known effect that, for example, compressing air produces heat.

Heat transfer in solids and heat transfer in fluids are combined in the majority of applications. This is because fluids flow around solids or between solid walls, and because solids are usually immersed in a fluid. An accurate description of heat transfer modes, material properties, flow regimes, and geometrical configurations enables the analysis of temperature fields and heat transfer. Such a description is also the starting point for a numerical simulation that can be used to predict conjugate heat transfer effects or to test different configurations in order, for example, to improve thermal performances of a given application.

In this case heat is generated at processor and it transfer towards other surrounding components and due to this it effects the parts performance. So we are trying to analyse the heat distribution with the help of ansys fluent software.

What is computer graphics card?

A Graphics Card is a piece of computer hardware that produces the image you see on a monitor. The Graphics Card is responsible for rendering an image to your monitor, it does this by converting data into a signal your monitor can understand. The better your graphics card the better, and smoother an image can be produced. This is naturally very important for gamers and video editors.

Figure 1: schematic representation of graphics card

Parts of graphics card:

1. Processor or GPU
2. Fins or heat sinks
3. Base plate or PCB

The main aim of this study to find out maximum temperature distribution through the processor and its effect on its surrounding parts like fins, base plate and other small components.

Methodology:

To achieve the objective of this study following steps are used;

Step 1: pre-processing:

• Importing of geometry: In this step the geometry is imported directly in space claim and creating the fluid volume inside the exhaust manifold.

Figure 2: Geometry of graphics card

(A) (B) (C)

Figure 3: parts of graphics card as (A) PCB, (B) Heat sink and (C) Processor

• Meshing:

Here we performed two types of simulation. First is Base line mesh simulation and second is refine mesh simulation. In this case we used ‘Shared topology’ method to generate the conformal mesh between solid and fluid surfaces.

Case 1: Base line mesh:

The methodology used for meshing is automatic method with element size of 3mm. After generating mesh 163182 elements and 31299 nodes are formed. In mesh if more elements is generated smoothly, results are to more accurate from previous simulations.

Figure 4: structured mesh of graphics card and mesh metric plot

The mesh metric plot of element quality is shown in figure 3. It identified the elements as per their quality. From figure 4, we can say that elements have their high quality is shown in the range of 0.63 - 1.0 and elements of lower quality is very less. Hence mesh is acceptable range.

Name creation for boundaries:

Inlet --- Left side surface,

Outlet --- Right side surface,

Symmetry --- remaining all four surfaces.

Step 2: setup

1. Setting up physics

Solver –steady state, pressure based used.

Model--- in this study we used K-ε turbulent model for set up.

Material properties---

Air: Density=1 kg/m³ and Dynamic viscosity= 0.02 kg-m/s, is used for fluid volume.

• Processor: cupper material
• Fins: Aluminium
• Base plate: steel material
• Enclosure: air flow

Heat generation: In this case we assume that 1.5e8 w/m^3 heat generated at processor.

Boundary condition---inlet velocity= 5m/s and temperature = 300K, outlet = 1 atm pressure,

Setting up solution:

Hybrid initialization is used for this study.

Step 3: Post- processing

In post-processing we saw the simulated results of plots, contours, and animations. In post-processing we can also create the locations at which results are simulated.

Results: the generated outputs are shown below…

Case 2: Refined mesh

• Element size: For processor = 0.25mm
  • Fins, base plate and Enclosure = 2mm
• Nodes: 83113
• Element: 429270

Figure 4: structured mesh of graphics card and mesh metric plot

Results:

Mesh	Temperature (K)	Velocity (m/s)	Wall heat transfer coefficient (w/m^2.k)
Base line mesh	378.16	5.78	1102.29
Refine mesh	373.08	5.81	1108.32

Conclusions:

1. From above results we can say that temperature is mostly conducted through fins and it is being decreased through convection heat transfer.
2. If we refined the element size in meshing, we found more accurate results. here we compare both simulations results:
3. From above results the maximum temperature at processor in case 1 is 378.16 K and case 2 is 373.08 K.
4. The convergence in case 1 at 240 iterations and in case 2 at 95 iterations.
5. Potential hot-spot is generated in PCB because Processor is directly attached with PCB.