2019
DOI: 10.1002/htj.21606
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Application of neural network on heat transfer enhancement of magnetohydrodynamic nanofluid

Abstract: The applications of neural networks (NNs) on engineering problems have been increased for obtaining high precision results. In this study, a new type of NN known as the group method of data handling (GMDH) is applied to obtain a formulation of a heat transfer rate.

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Cited by 42 publications
(12 citation statements)
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“…Generally, the higher-order approximation to the solution can be provided by equation (18). For instance, the firstorder approximation can be shown as…”
Section: Review Of the Global Residue Harmonic Balance Methodsmentioning
confidence: 99%
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“…Generally, the higher-order approximation to the solution can be provided by equation (18). For instance, the firstorder approximation can be shown as…”
Section: Review Of the Global Residue Harmonic Balance Methodsmentioning
confidence: 99%
“…. , k) and ω k , substituting equations (18) into (12) and collecting the coefficients of p, one should get…”
Section: Review Of the Global Residue Harmonic Balance Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…Nano uids are a solid-liquid mixture of material including nanometer-sized solid particles in a traditional uid [22]. In recent years, nano uids are used in many engineering applications such as heat transfer systems and machining processes due to their excellent heat transfer capabilities and tribological properties [23][24][25]. The literature review presented that the use of nano uids in metal cutting enhances the heat transfer, which leads to reduced cutting forces, coe cient of friction, power consumption, tool wear, and cutting temperature [9,10].…”
Section: Introductionmentioning
confidence: 99%
“…Karkaba et al [67] employed large space exploration applications to optimize the design of vortex generators for maximum performance and heat transfer enhancement. Gerdroodbary [68] formulated a model using neural networking to predict the heat flux for magnetohydrodynamic nanofluid flow. Jovic et al [69] explored the potentiality of adaptive neuro-fuzzy methodology in the predicting of heat transfer enhancement for the mini channel heat sink with higher accuracy.…”
Section: Introductionmentioning
confidence: 99%