BDA30603 Heat Transfer Assignment Group Project Sample 2026 | UTHM

1.0 Introduction

Effective heat transfer regulation is crucial in contemporary electronic systems, particularly for applications needing high power density and continuous operation. As electronic components get more powerful and compact, the amount of heat generated in a small surface area grows dramatically. If this heat is not efficiently transported, the electronic chip’s operating temperature may rise above the designated maximum limit, which could result in reduced performance, thermal throttling, rapid material deterioration, or irreversible device failure. One of the most effective and popular electronic cooling techniques is the passive heat sink system, which runs without any external power input. The primary techniques for passive cooling are heat conduction through solid materials and heat dispersion to the surrounding air through natural convection. Because they don’t have any moving parts, passive heat sinks are simpler to build, less expensive, require less maintenance, and have greater long-term reliability than active cooling systems.

This group design project’s goal is to use a passive heat sink to cool an industrial electronic chip that generates 10 W of thermal energy. The system runs in a natural convection situation with an ambient temperature of 30°C, and the highest permitted chip temperature is 85°C. Because aluminum alloy 6061 offers a balance between high thermal conductivity and structural appropriateness, it was chosen as the heat sink material. The design must also adhere to physical limitations, such as a maximum base size of 60 mm × 60 mm and a maximum height of 50 mm. in order to assess and improve the performance of the heat sink. This study uses SolidWorks Flow Simulation to integrate theoretical heat transport analysis with numerical simulation.

1.1 Objectives

The following are the project’s goals:

1. To assess a passive heat sink system’s thermal performance 

• Using basic principles of heat transfer, such as natural convection into the surrounding air and conduction via the heat sink base and fins.

2. To calculate thermal resistances, effective surface area, and fin efficiency 

• Applied the parallel thermal resistance method using the rectangular fin configuration and material characteristics for aluminum alloy 6061.

3. Use SolidWorks Flow Simulation to verify the theoretical investigation.

• Under natural convection conditions, compare the results of numerical simulations with analytical temperature predictions.

4. To carry out a study on design optimization 

• Modifying the heat sink’s specific geometric features to improve cooling efficiency while adhering to size and temperature restrictions.

2.0 Literature review

The primary methods for regulating heat transmission in passive electrical cooling systems are conduction inside the heat sink material and natural convection from the heat sink surface to the surrounding air. According to basic heat transfer theory, the rate of heat dissipation is influenced by the convective heat transfer coefficient of air, exposed surface area, fin dimension, and material thermal conductivity. Because of its high thermal conductivity, low density, corrosion resistance, and ease of manufacturing, aluminum alloy 6061 is frequently used as heat sinks. Increasing the effective surface area of a heat sink with fins improves heat dissipation under natural convection circumstances, according to numerous studies. The most popular fin designs are rectangular straight fins because of their straightforward design, ease of production, and consistent thermal performance.

In addition, previous study has demonstrated that the effectiveness of extended surfaces is significantly influenced by fin efficiency. Fin efficiency accounts for the internal conduction resistance-induced temperature gradient along the fin. Fin thickness, fin length, heat conductivity, and convection coefficient all have an impact on the efficiency of rectangular fins. Fins that are too long or too narrow may be less effective and contribute less to the total amount of heat that is transmitted. Furthermore, research on natural convection heat sinks demonstrates that adding more fins improves the transfer of heat and increases total surface area. On the other hand, inadequate fin spacing can limit airflow, reduce buoyancy-generated convection currents, and lower cooling effectiveness. Therefore, the optimal fin configuration must strike a balance between increasing surface area and facilitating airflow.

In heat sink design, thermal resistance, fin efficiency, and operating temperature are frequently estimated using analytical methods, such as the parallel thermal resistance technique. SolidWorks Flow Simulation is now a useful method for verifying theoretical calculations thanks to advancements in computational tools. Heat conduction within materials and natural convection in air can be simulated using CFD while taking gravity effects into consideration. A more precise assessment of thermal performance is made possible by the combination of analytical computations and numerical simulation, which also offers parametric studies for design improvement.

3.0  Specification

The following table outlines the technical specifications and design constraints that the passive heat sink must satisfy to ensure safe and efficient thermal management of the electronic chip :  Table 3.0 Technical specification and design constraints

 4.0 Methodology

4.1 Phase 1 : Base Case Calculation

Reference Design Specifications (Base Case) for Manual Calculation :

Table 4.1 : Specification of fin

𝑚

CALCULATIONS :

1. ToFin getEfficiency, the _fin  ηefficiency^𝑓𝑖𝑛  by using the formula rectangular fins given in the table of efficiency:

η       = 𝑡𝑎𝑛ℎ 𝑚𝐿𝑐

To find m:                                            𝑓𝑖𝑛                        𝑚𝐿𝑐

Based on the table above, we can get the𝑚  value=  and2^𝑘𝑡ℎ  calculate the m. Hence, by substituting the value:

𝑚 =     (170²)⁽(⁸0⁾.002)

Since the value had completed ready,𝑚 hence: = 6 . 86 𝑚−1

η𝑓𝑖𝑛 = 𝑡𝑎𝑛ℎ( 60.9861 .(866.)86(0).(030 .)03)

η𝑓𝑖𝑛 =

2. TheAs the effective formula, area, we 𝐴know𝑒𝑓𝑓  that:

For base area, 𝐴𝑒𝑓𝑓 = 𝐴𝑏𝑎𝑠𝑒 + 𝑁𝐴𝑓𝑖𝑛. η𝑓𝑖𝑛   𝐴𝑏𝑎𝑠𝑒 = 60𝑚𝑚  × 60𝑚𝑚

For area of fin, 𝐴𝑏𝑎𝑠𝑒 formula:= 0. 0036

𝐴𝑓𝑖𝑛

𝐴𝑓𝑖𝑛 = 2𝑤𝐿𝑐

𝐴𝑓𝑖𝑛 = 2(0. 06)(0. 03)

𝐴𝑓𝑖𝑛 = 0. 0036𝑚²

Since the value had completed, hence:

𝐴𝑒𝑓𝑓 = 0. 0036 + (10)(0. 0036)(0. 9861)

𝐴𝑒𝑓𝑓 = 0 . 0391𝑚²

3. The convection of the resistance, 𝑅𝑐𝑜𝑛𝑣

𝑅𝑐𝑜𝑛𝑣 = ℎ𝐴1𝑒𝑓𝑓

𝑅𝑐𝑜𝑛𝑣 = (8)(0¹.0391)  𝑅𝑐𝑜𝑛𝑣 = 3. 1969     ℃/𝑊

4. The conduction resistance of the base, 𝑅𝑐𝑜𝑛𝑑

𝑅𝑐𝑜𝑛𝑑 = 𝑘𝑡.𝐴^{𝑏𝑎𝑠𝑒}𝑏𝑎𝑠𝑒

𝑅𝑐𝑜𝑛𝑑 = (170⁰)^.(⁰⁰⁵0.0036)  𝑅𝑐𝑜𝑛𝑑 = 0. 00817  ℃/𝑊

5. TheFormula chip oftemperature, chip _temperature: 𝑇^{𝑐ℎ𝑖𝑝}

𝑇𝑐ℎ𝑖𝑝  

𝑇𝑐ℎ𝑖𝑝 = 62 . 05

4.2  Phase 2 : Simulation

Table 4.2 Parameter of Base Case

 The three-dimensional model represents the baseline heat sink geometry created in SolidWorks. It includes a 60 mm × 60 mm aluminium base, ten rectangular fins and an attached silicon chip. The surrounding air domain is included to simulate natural convection accurately during CFD analysis.

The isometric view shows the steady-state surface temperature distribution across the heat sink. The hottest region appears at the chip–heat sink interface, while temperatures gradually decrease toward the fin tips, confirming effective heat conduction from the base into the fins.

From the front perspective, the temperature gradient clearly moves upward from the base to the fin tips. This visual confirms that thermal energy travels through the fins and dissipates into the surrounding air under natural convection conditions.

This additional viewing angle reinforces the consistency of the temperature pattern across the fin array. Uniform heat spreading along the base plate and stable thermal conduction from the chip into the heat sink are evident from this perspective.

The velocity cut plot illustrates airflow patterns around the heat sink. Rising warm air creates buoyancy-driven flow between the fins, with visible plumes indicating natural convection development. Maximum velocities occur near the fin tips where thermal gradients are strongest.

This fluid temperature slice shows how heat transfers from the solid heat sink into the surrounding air. Warmer air rises above the fins, while cooler ambient air enters from the sides and bottom, supporting continuous convective circulation.

A refined computational mesh was applied to capture thermal and fluid behavior accurately. Local mesh refinement around the fin surfaces ensures precise resolution of boundary layers and temperature gradients critical for natural convection simulation.

Streamlines depict the path of rising air due to buoyancy forces. The trajectories confirm vertical airflow development between the fins, demonstrating how natural convection removes heat from the system without external forcing.

This goal convergence plot tracks the maximum chip temperature over simulation iterations. The solution stabilizes at approximately 78.22°C, confirming a reliable steady-state result that meets the safety limit of 85°C.

4.3  Phase 3 : Design Optimization

In this project, Solidworks 3D is used to create the heat sink model and run the simulation. The objectives are to compare the maximum temperature from the specified parameter design with the best possible design.

ITERATION 1 :

Table 4.3 (a) Parameter of heat sink iteration 1

 Iteration 1 features a dense array of 66 pin-type rectangular fins on a smaller base (35 mm × 55 mm). The compact design aims to maximize surface area but may restrict airflow due to tight spacing between pins.

The isometric thermal plot reveals high base temperatures due to limited airflow between densely packed pins. Despite increased surface area, heat dissipation efficiency suffers from restricted natural convection pathways.

Front view highlights uneven cooling across the fin array. The central region retains more heat, suggesting poor air penetration through the tightly spaced pin configuration.

From above, the top view shows minimal temperature variation along the fin height, indicating that much of the fin surface remains underutilized due to stagnant air pockets.

The convergence graph shows the chip temperature stabilizing at a higher value than the base case, reflecting reduced cooling performance despite the higher fin count.

ITERATION 2 :

Table 4.3 (b) Parameter of heat sink iteration 2

The isometric thermal map shows better heat distribution compared to Iteration 1. Taller fins allow more vertical airflow, reducing hot spots near the base.

Front view confirms a smoother temperature gradient from base to tip, indicating more effective use of fin height for heat dissipation under natural convection.

The top view demonstrates consistent cooling across all fins, suggesting adequate spacing and airflow penetration throughout the array.

Temperature converges steadily, showing improved performance over Iteration 1 but still not as efficient as the optimized 8-fin design discussed in the parametric study.

ITERATION 3 :

Table 4.3 (c) Parameter of heat sink iteration 3

This iteration replaces rectangular fins with 25 cylindrical pin fins (6 mm diameter, 30 mm height). Pin fins offer isotropic airflow but require careful spacing to avoid choking convection.

The isometric thermal plot shows temperature distribution across the 25 cylindrical pin fins. Heat spreads evenly from the base into the pins, with the hottest region concentrated near the chip interface. Cooler zones appear toward the top of each pin, indicating effective heat dissipation through vertical airflow.

These multi-angle views provide a comprehensive look at how heat flows through the pin fin array. The front and left views show consistent cooling along the pin height, while the top view confirms uniform heat spreading across the base plate. The trimetric view reinforces the 3D nature of heat transfer, highlighting how each pin contributes to overall cooling efficiency.

This graph tracks the maximum chip temperature over simulation iterations for the pin fin design. The solution stabilizes at approximately 81.04°C, demonstrating a steady-state result that remains safely under the 85°C limit. The sharp initial rise reflects rapid heat buildup, followed by stabilization as natural convection balances the 10W heat load.

ITERATION 4 :

Table 4.3 (d) Parameter of heat sink iteration 4

This 3D model shows the final iteration with 12 rectangular fins on a 60 mm × 60 mm base. The design aims to test whether increasing fin count beyond the base case improves cooling or begins to restrict airflow. The mass of this configuration is recorded at 181.93 grams, reflecting the added material from extra fins.

The isometric thermal plot reveals how heat spreads across the 12-fin array. While the base remains relatively cool, higher temperatures concentrate near the middle of the fin height, suggesting airflow restriction between closely spaced fins limits full utilization of the increased surface area.

These multi-angle views confirm the temperature trend seen in the isometric view. The front and left views show consistent vertical gradients, while the top view highlights uneven cooling across the fin array. The trimetric view reinforces that the central region retains more heat due to reduced air penetration between tightly packed fins.

This graph tracks the maximum chip temperature over simulation iterations. The solution stabilizes at approximately 83.03°C, showing a steady-state result under natural convection. Although this design stays safely below the 85°C limit, the temperature rise compared to the base case suggests diminishing returns from adding more fins.

5.0 Result

This section presents the results obtained from both the manual calculations and the SolidWorks Flow Simulation carried out in this project. The results include a comparison between analytical and simulation temperatures for the base case design, visual observations from temperature and flow plots and the outcomes of the parametric study conducted in Phase 3.

5.1  Comparison Between Manual and Simulation Results (Base Case)

The base case heat sink design was first analysed using manual heat transfer calculations as presented in Section 4.1. The analytical method predicted a maximum chip temperature of 62.05°C, remaining below the maximum allowable operating temperature of 85°C.

The same base case geometry from Phase 2 was analysed using SolidWorks Flow Simulation under natural convection conditions. The maximum chip temperature obtained from the simulation is compared with the manual result as shown in Table 5.1.

Table 5.1 Comparison of Base Case Results for Phase 2

The comparison shows a noticeable difference between the analytical prediction and the simulation outcome for the base case heat sink. The manual calculation estimates a maximum chip temperature of 62.05°C, while the SolidWorks Flow Simulation produces a higher value of 78.22°C. This difference highlights the limitations of simplified analytical assumptions, since the numerical model accounts for three-dimensional heat conduction and realistic airflow behaviour under natural convection. The analytical approach remains useful as an initial estimation method, while the simulation result provides a more representative temperature distribution for the actual operating condition. Both values remain below the maximum allowable temperature of 85°C, confirming safe operation of the base case design.

5.2 Temperature Distribution of the Base Case Heat Sink

The temperature surface plots obtained from SolidWorks Flow Simulation illustrate the thermal distribution across the chip and heat sink assembly for the base case design simulated in Phase 2. The highest temperature is concentrated at the chip surface, while lower temperatures are observed along the fins and in the surrounding air region, indicating effective heat conduction and convection.

These plots visually demonstrate heat conduction from the chip into the heat sink followed by heat dissipation to the ambient air.

The isometric temperature surface plot presents the overall thermal behaviour of the base case heat sink assembly. The highest temperature region appears at the chip surface, indicating the primary heat source location. Heat spreads from the chip into the heat sink base and along the fins, forming a gradual temperature gradient across the structure. Lower temperatures are observed near the fin tips and surrounding air region, showing effective heat dissipation through natural convection.

The front view temperature plot clearly illustrates the temperature variation along the height of the heat sink fins. The peak temperature reaches 78.22°C at the chip surface, followed by a steady reduction along the fin length. This pattern confirms efficient heat conduction from the chip into the fins, combined with convective heat transfer from the fin surfaces to the ambient air. The smooth temperature transition indicates stable thermal performance under natural convection conditions.

5.3 Cut Plots Diagram (Temperature Distribution) and Flow Trajectories

5.3.1  Cut Plots Diagram (Temperature Distribution)

The flow trajectory plots from the base case simulation demonstrate the movement of air around the heat sink caused by natural convection.

The velocity cut plot demonstrates airflow movement generated by buoyancy effects around the heat sink. Heated air rises vertically between the fins, while cooler air enters from the surrounding region to replace it. This circulation pattern supports the presence of natural convection as the dominant cooling mechanism. The upward airflow paths indicate that the fin spacing allows sufficient air movement for passive heat removal.

The temperature cut plot of the fluid domain shows warmer air concentrated near the heat sink surfaces and cooler air farther from the fins. This temperature distribution confirms heat transfer from the solid surfaces into the surrounding air. The gradual temperature decay away from the heat sink reflects effective thermal interaction between the solid and fluid regions during steady-state operation.

5.3.2  Flow Trajectories

The flow trajectory plot visualises the continuous airflow paths formed around the heat sink under natural convection. Air rises along the fin channels and exits upward, forming consistent thermal plumes. Fresh ambient air moves inward from the sides, maintaining circulation around the heat sink. This behaviour confirms that the geometry supports stable airflow patterns suitable for passive cooling applications.

5.4 Parametric Study Results (Phase 3)

A parametric study was performed by modifying the fin configuration and number to observe the impact on maximum chip temperature. Several design iterations were simulated and compared against the base case.

Table 5.4 Summary of Parametric Study Results

The parametric study results demonstrate the influence of fin configuration on maximum chip temperature. The base case design records a temperature of 78.22°C, remaining within the acceptable operating range. Modified fin designs show varying thermal performance, with the rectangular filet fin configuration achieving the lowest temperature of 53.50°C. Designs with increased fin density or alternative geometries exhibit higher temperatures, indicating reduced cooling effectiveness under natural convection. These results emphasise the importance of fin shape and spacing in enhancing airflow and heat dissipation.

6.0 Discussion

6.1 Graphical Comparison of Parametric Study

Design Iteration Index : 

The impact of various heat sink shapes on the maximum chip temperature under natural convection cooling is shown graphically in Figure 6.1.1. With its typical rectangular fins, the base case design produced a maximum chip temperature of 78.22°C. Iteration 1, which had rectangular filet fins, had the best thermal performance out of the four changed designs, reaching a much lower temperature of 53.50°C. This is a significant decrease of about 25°C when compared to the base case, demonstrating how well filleted edges work to improve convective heat transfer and encourage smoother airflow. On the other hand, Iteration 2, which kept rectangular fins but changed their count or spacing, only slightly improved (70.60°C). More significantly, with temperatures rising to 81.04°C and 83.03°C, respectively, Iterations 3 and 4, both of which included pin fin configurations, performed worse than the base scenario. These findings show that pin fins are not ideal for passive cooling systems where buoyancy-driven airflow predominates, even though they are frequently advantageous in forced convection situations.

This result is further supported by the plot of maximum chip temperature against heat sink mass in Figure 6.1.2. Higher mass does not necessarily translate into better cooling, despite popular belief. Despite achieving the lowest working temperature, the most efficient design (Iteration 1) is also the lightest, weighing only 40 g. In contrast, the worst thermal performance is shown by the heaviest design (Iteration 4, ~180–200 g). This inverse connection highlights the fact that geometric compliance with airflow patterns is more important for thermal efficiency in natural convection than material volume or surface area alone. Heat trapping and higher chip temperatures can result from excessive or improperly oriented fins, such as those found in pin fin designs, obstructing the vertical thermal plumes required for efficient passive cooling.

All of these results are consistent with the temperature distribution and flow trajectory analyses from Section 5.3, which verify that steady, upward-moving air currents between well-spaced fins are supported in the base scenario. Iteration 1’s success indicates that natural convection can be greatly improved without adding weight or complexity by improving fin geometry, such as by adding fillets to lessen turbulence and flow separation. On the other hand, this natural circulation is disrupted by the addition of dense or misaligned features, such as pin fins, which reduces performance. Therefore, aerodynamic efficiency and alignment with buoyant flow routes are more important for passive cooling applications than sheer fin count or mass.

6.2  Discussion of Parametric Study 

𝑃𝑒𝑟𝑐𝑒𝑛𝑡𝑎𝑔𝑒 𝑒𝑟𝑟𝑜𝑟 = |𝑆𝑖𝑚𝑢𝑙𝑎𝑡𝑖𝑜𝑛 𝑡𝑒𝑚𝑝𝑒𝑟𝑎𝑡𝑢𝑟𝑒𝐶𝑎𝑙𝑐𝑢𝑙𝑎𝑡𝑒𝑑^|78.2262  ⁻𝑡𝑒𝑚𝑝𝑒𝑟𝑎𝑡𝑢𝑟𝑒−.05  ⁶²𝐶𝑎𝑙𝑐𝑢𝑙𝑎𝑡𝑒𝑑^.05| ×  𝑡𝑒𝑚𝑝𝑒𝑟𝑎𝑡𝑢𝑟𝑒100%                                                             | × 100%

𝑃𝑒𝑟𝑐𝑒𝑛𝑡𝑎𝑔𝑒 𝑒𝑟𝑟𝑜𝑟 =  𝑃𝑒𝑟𝑐𝑒𝑛𝑡𝑎𝑔𝑒 𝑒𝑟𝑟𝑜𝑟 = 26. 1 %

Natural convection is the primary heat transfer mechanism in the base case heat sink design, as the simulation results clearly show. A typical buoyancy-driven airflow can be seen in the velocity cut plot (Figure 5.3.1a), where cooler ambient air is brought in from the sides to replace the heated air that rises vertically through the channels between the fins. For passive cooling systems that don’t employ forced airflow or external fans, this circulation pattern verifies the existence of a stable convective loop. In addition, a thermal gradient that decreases with distance from the heat sink surface is depicted in the fluid temperature cut plot (Figure 5.3.1b). Effective conductive and convective heat transmission from the solid components into the surrounding fluid domain is indicated by the concentration of warmer air close to the fins and cooler air farther away. The thermal link between the solid and fluid sectors is validated by this slow temperature degradation under steady-state settings, which also bolsters the simulation setup’s dependability.

Organized thermal plumes rising from the fin array are further shown in the flow trajectory plot, along with a steady influx of ambient air from lateral directions. According to this behavior, the fin spacing in the basic case is ideal for natural convection because it is neither too sparse (which would reduce surface area for heat exchange) or too dense (which would impede airflow). Important information about how geometric changes impact thermal performance can be found in the parametric research (Section 5.4). The rectangular filet fin (Iteration 1) outperformed the base case (78.22°C) by achieving the lowest maximum chip temperature (53.50°C) of all examined configurations. This decrease is probably the result of smoother transitions at fin edges (caused by filleting), which could improve convective heat transfer by lowering flow resistance and increasing air circulation.

On the other hand, designs with pin fins (Iterations 3 and 4) produced chip temperatures that were higher (81.04°C and 83.03°C, respectively). This implies that pin fin geometries might not offer enough vertical flow channels for buoyant air to effectively escape under natural convection, resulting in thermal standstill. Similar to the base instance, Iteration 2 produced a little improvement (70.60°C) despite using rectangular fins, perhaps as a result of optimized fin count or spacing. Overall, these results highlight the importance of fin arrangement and form in passive cooling design. Increasing surface area may seem advantageous, but if it obstructs natural airflow, it may be detrimental. In order to maximize heat dissipation without external force, the ideal design must strike a compromise between surface area, fin spacing, and aerodynamic smoothness.     

7.0 Conclusion

Table 7.0 Comparison of maximum chip temperature for base case and design iterations

This project evaluated the thermal performance of a passive heat sink used for cooling an electronic chip under natural convection conditions. Analytical calculations and SolidWorks Flow Simulation confirm that the base case design operates below the maximum allowable chip temperature of 85 °C. The simulation predicts a higher temperature than the manual calculation due to the inclusion of three-dimensional heat conduction and realistic airflow behaviour, providing a more representative thermal response.

The parametric study highlights the strong influence of fin geometry and spacing on heat dissipation. Increasing fin quantity alone does not guarantee better cooling performance. Designs with dense fin arrangements show restricted airflow, reducing the effectiveness of natural convection. This behaviour appears clearly in Iteration 3 and Iteration 4, as both configurations produce higher maximum chip temperatures that approach the allowable limit.

Iteration 1 is selected as the final design recommendation based on its superior thermal performance. This configuration records the lowest maximum chip temperature of 53.50 °C, offering a large safety margin during operation. The rectangular pin fin geometry promotes smoother airflow and improves heat dissipation by supporting stable buoyancy-driven convection. The temperature distribution remains uniform across the fins, indicating efficient heat transfer from the chip to the surrounding air.

Overall, the findings show that effective passive cooling depends on balanced fin geometry rather than increased material volume. A design that supports airflow while maintaining sufficient surface area achieves better thermal performance. The combination of theoretical analysis and numerical simulation proves effective for guiding heat sink design optimization under natural convection conditions.