Performance and parameter optimization design of microchannel heat sink with different cavity and rib combinations

Abstract

Microchannel heat sinks play a crucial role in dissipating heat in microelectronic systems in computer data centers. To enhance their thermal performance, this study proposes a combined microchannel design consisting of various cavity shapes and straight ribs, and analyzes its heat transfer and flow performance through numerical simulation. The heat transfer characteristics of microchannel heat sink with different straight rib structures are compared. Moreover, the four parameters including the relative length (α), relative width of the cavity (β), relative length of straight ribs (γ) and relative width of straight ribs (λ) are investigated, and the effects of Reynolds number variation on heat sink Nusselt number (Nu), friction coefficient (f) and thermal enhancement efficiency (η) are studied. The optimization process employs an artificial neural network and a multi-objective genetic algorithm to determine the optimal compromise solution and heat sink model, utilizing the Nusselt number and friction coefficient as evaluation indices. The results show that rectangular rounded straight rib is the straight rib structures with the best comprehensive thermal performance, with an average η approximately 9.7 % higher than that of the non-straight ribbed heat sink model. Furthermore, the variation in the four studied parameters yields distinct effects on the Nusselt number, friction coefficient, and thermal enhancement efficiency. Notably, the optimal performance is achieved when Nu = 13.59679 and f = 0.11855, with corresponding parameter values of α = 0.1575, β = 0.3931, γ = 0.0714, and λ = 1.2149. Ultimately, these results provide valuable insights into the structural optimization of microchannel heat sink cavity and straight rib combination models.

Keywords

• Microchannel
• Cavity rib combination
• Water thermal performance
• Artificial neural network
• Genetic algorithm