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      3D-CFD simulation and neural network model for the j and f factors of the wavy fin-and-flat tube heat exchangers

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          Abstract

          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.

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          Most cited references25

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          Compact Heat Exchangers

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            A comparative study on the air-side performance of wavy fin-and-tube heat exchanger with punched delta winglets in staggered and in-line arrangements

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              Enhanced heat transfer due to curvature-induced lateral vortices in laminar flows in sinusoidal corrugated-plate channels

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                Author and article information

                Journal
                bjce
                Brazilian Journal of Chemical Engineering
                Braz. J. Chem. Eng.
                Brazilian Society of Chemical Engineering (São Paulo, SP, Brazil )
                0104-6632
                1678-4383
                September 2011
                : 28
                : 3
                : 505-520
                Affiliations
                [01] Semnan orgnameSemnan University orgdiv1Petroleum and Gas Engineering orgdiv2School of Chemical I. R. Iran fhormozi@ 123456semnan.ac.ir
                Article
                S0104-66322011000300016 S0104-6632(11)02800316
                10.1590/S0104-66322011000300016
                007e804b-9161-48c1-9e93-4479cbaeaeea

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                : 03 August 2010
                : 18 March 2011
                : 04 February 2011
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 25, Pages: 16
                Product

                SciELO Brazil

                Categories
                Process Systems Engineering

                j factor,f factor,Neural network,CFD simulation,Wavy fin-and-flat tube

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