Abstract
This study aimed to present the design methodology of microjet heat sinks with unequal jet spacing, using a machine learning technique which alleviates hot spots in heat sinks with non-uniform heat flux conditions. Latin hypercube sampling was used to obtain 30 design sample points on which three-dimensional Computational Fluid Dynamics (CFD) solutions were calculated, which were used to train the machine learning model. Radial Basis Neural Network (RBNN) was used as a surrogate model coupled with Particle Swarm Optimization (PSO) to obtain the optimized location of jets. The RBNN provides continuous space for searching the optimum values. At the predicted optimum values from the coupled model, the CFD solution was calculated for comparison. The percentage error for the target function was 0.56%, whereas for the accompanied function it was 1.3%. The coupled algorithm has variable inputs at user discretion, including gaussian spread, number of search particles, and number of iterations. The sensitivity of each variable was obtained. Analysis of Variance (ANOVA) was performed to investigate the effect of the input variable on thermal resistance. ANOVA results revealed that gaussian spread is the dominant variable affecting the thermal resistance.
Highlights
Many investigations were conducted over different designs to improve the heat transfer effects in the heat sink within the constraints such as maximum pumping power, maximum pressure drop, a constant flow rate of cooling fluid, constant heat flux, constant interface area, or constant cross-sectional area
Peng et al [10] performed a comparative analysis between traditional microchannel heat sink (TMC) and multi-jet microchannel (MJMC) heat sink, using numerical techniques
Parno et al [24] implemented a Design and Analysis of Computer Experiments (DACE) surrogate model with Particle Swarm Optimization (PSO) to optimize the solution of the groundwater problem
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Many investigations were conducted over different designs to improve the heat transfer effects in the heat sink within the constraints such as maximum pumping power, maximum pressure drop, a constant flow rate of cooling fluid, constant heat flux, constant interface area, or constant cross-sectional area. Peng et al [10] performed a comparative analysis between traditional microchannel heat sink (TMC) and multi-jet microchannel (MJMC) heat sink, using numerical techniques They found that temperature uniformity improves significantly with the help of an increasing number of jets. Husain et al [11] compared the effect of different flow spent schemes with and without extraction ports They presented that fluid removed from edges in unconfined flows have higher temperature uniformities and lower pressure drop. Mathematics 2021, 9, 2167 by Hadad et al [23] investigated the shape optimization of a water-cooled impingement micro-channel heat sink, including manifolds
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