3D-CFD simulation and neural network model for the j and f factors of the wavy fin-and-flat tube heat exchangers
A three dimensional (3D) computational fluid dynamics (CFD) simulation and a neural network model are presented to estimate the behaviors of the Colburn factor (j) and the Fanning friction factor (f) for wavy fin - and - flat tube (WFFT) heat exchangers. Effects of the five geometrical factors of fin pitch, fin height, fin length, fin thickness, and wavy amplitude are investigated over a wide range of Reynolds number (600<Re<7000). The CFD simulation results express that the geometrical parameters of wavy fins have significant effects on the j and f factors as a function of Reynolds number. The computational results have an adequate accuracy when compared to experimental data. The accuracy of the calculations of the j and f factors are evaluated by the values of the absolute average relative deviation (AARD), being respectively 3.8% and 8.2% for the CFD simulation and 1.3% and 1% for the neural network model. Finally, new correlations are proposed to estimate the values of the j and f factors with 3.22% and 3.68% AARD respectively.
| Main Authors: | , , , |
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| Format: | Digital revista |
| Language: | English |
| Published: |
Brazilian Society of Chemical Engineering
2011
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| Online Access: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322011000300016 |
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