2021
DOI: 10.3390/math9172167
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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 Swa… Show more

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Cited by 5 publications
(1 citation statement)
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“…Feed forward back propagation neural network was considered in this work which consists of Input, Hidden and output layer each. 53 In the input layer, neurons were 3, and the targeted values were heat transfer parameters (Q, h, Re, Nu, and ff). The ANN was performed with the help of Mat Lab.…”
Section: Estimation By Annmentioning
confidence: 99%
“…Feed forward back propagation neural network was considered in this work which consists of Input, Hidden and output layer each. 53 In the input layer, neurons were 3, and the targeted values were heat transfer parameters (Q, h, Re, Nu, and ff). The ANN was performed with the help of Mat Lab.…”
Section: Estimation By Annmentioning
confidence: 99%