Heat sink performance in engineering applications relies on natural convection. Heat sinks flow excess heat from electronic components and other heat-producing devices by creating natural convection due to temperature differential between the heat sink surface and the surrounding fluid, usually air. The buoyancy effect causes warmer air to rise and cooler air to fall, creating natural convection currents. These currents move heat from the heat sink, keeping the system’s operating temperature within limits. Understanding and optimizing heat sink natural convection improves thermal performance, energy efficiency, and the reliability and lifetime of electronic gadgets and other heat-generating systems.

As the title of the project suggests, it is aimed at validating a numerical paper entitled “Revisit on the natural convection from horizontal multi-channel rectangular-fin heat sinks [1]”. The present problem focuses on the natural convection effects on heat sink fins.

• Reference [1]: Liou, Hung-Jyun, Shwin-Chung Wong, and Yi-Cheng Lin. “Revisit on the natural convection from horizontal multi-channel rectangular-fin heat sinks.” International Journal of Thermal Sciences171 (2022): 107232.

Figure 1: The experimental setup of Starner-McManus-Harahap Heat sink [1]

Simulation Process

Firstly, the microchannel heat sink is designed using Design Modelers software. A rectangular domain is set, representing the fluid region around it. ICEM software is utilized to divide the whole computational domain into cells. A structured grid consists of 2217120 cells.

Basically, the flow regime remains laminar while passing through the micro channels. The Boussinesq model is employed to correctly include natural convection effects.

Figure 2: . The computation domain for a symmetric 16-channel heat sink [1]

Post-Processing

By quantitative validation against published benchmark data, the heat sink CFD simulation shows astonishing precision. Using measured heat flux values and temperature differences between bulk fluid and ambient conditions, local heat transfer coefficients (hss) for every microchannel were computed. With a hss value of 3.07 W/m²K against the reference value of 3.11 W/m²K, Channel 1 showed just 1.3% variation. Keeping a minimum 1.1% error margin, Channel 2 also reported 3.45 W/m²K against the published 3.49 W/m²K. These near correlations confirm the reliability of the computational approach for heat sink thermal analysis.

Plotting velocity and temperature contours show unique natural convection patterns in the heat sink assembly. With strong plume growth above the heat sink structure, the top image’s velocity magnitude contour reveals maximum flow acceleration of 5.10E-01 m/s near the fin tips. At the fin bases, the temperature distribution (bottom image) shows peak values of 3.58E+02 K, which creates thermal stratification layers that generate buoyancy-induced flow. Validating the thermal management effectiveness of the design, the symmetric thermal plume generation and uniform temperature gradients across the fin array show ideal heat dissipation through the microchannels.

Figure 3: Distribution pattern of a) velocity field b) temperature in Natural Convection From Heat Sink Fins CFD Simulation