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Erschienen in:
Large Eddy Simulation Modeling in 2D Lid-Driven Cavity Kapitel lesen Erstes Kapitel lesen

2021 | OriginalPaper | Buchkapitel

Generation of Temperature Profile by Artificial Neural Network in Flow of Non-Newtonian Third Grade Fluid Through Two Parallel Plates

verfasst von : Vijay Kumar Mishra, Sumanta Chaudhuri, Jitendra K. Patel, Arnab Sengupta

Erschienen in: Proceedings of International Conference on Thermofluids

Verlag: Springer Singapore

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Abstract

Generation of temperature profile of third grade fluid in flow through parallel plates maintained at uniform heat flux is reported. Exact solution of heat transfer problem with third grade fluid is very difficult due to high level of nonlinearity. Viscous dissipation considerations make it even more difficult. In the present problem, least square method (LSM) has been employed to solve the governing equations. The velocity and temperature profile computed by LSM is used to train the artificial neural network (ANN). Once ANN is trained, it is able to give temperature profile corresponding to any velocity profile fed into the ANN. This work demonstrates the scope of ANN use to solve these types of complicated and problem of practical use. Artificial neural network (ANN) is employed in the solving of the problem with scaled conjugate gradient (SCG) as training algorithm.

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Nächstes Kapitel Fluid Flow and Heat Transfer Characteristics for an Impinging Jet with Various Angles of Inclination of Impingement Surface
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Metadaten
Titel
Generation of Temperature Profile by Artificial Neural Network in Flow of Non-Newtonian Third Grade Fluid Through Two Parallel Plates
verfasst von
Vijay Kumar Mishra
Sumanta Chaudhuri
Jitendra K. Patel
Arnab Sengupta
Copyright-Jahr
2021
Verlag
Springer Singapore
Buch
Proceedings of International Conference on Thermofluids

Print ISBN: 978-981-15-7830-4

Electronic ISBN: 978-981-15-7831-1

Copyright-Jahr: 2021

DOI
https://doi.org/10.1007/978-981-15-7831-1_4

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