Investigation of Double-Layered Wavy Microchannel Heatsinks Utilizing Porous Ribs with Artificial Neural Networks

Microchannel heatsinks with compact designs and high efficiencies have proved to be beneficial in cooling applications. In this study, a new double layered microchannel heatsink is introduced that uses wavy patterns and porous ribs to increase thermal performance and temperature uniformity. Artificial Neural Network is employed for finding the best performers and the effects of waviness on Nusselt number, pressure drop, and maximum temperature difference at the bottom of the microchannel in 100 < Re < 800. The Artificial Neural Network was trained using CFD results. Even though the pressure drops increase using the wavy design, the thermal performance is affected positively. Nusselt number increases more than 55% for Re = 800 and 13.5% for Re = 300. The increase in thermal performance is associated with the introduction of Dean vortices, especially at higher Re. In the proposed design, a much lower maximum bottom temperature, as low as 1.2°C, is achieved, which is beneficial for keeping the thermal stresses minimum. The Thermal efficiency factor of 1.34 is reported for the best performer wavy microchannel. However, it is observed that better Thermal efficiency factors are attained by using a wavy channel at the top layer and keeping the bottom layer straight