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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
Open accessAbstract
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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“Flow cross-sectional area is non-perfectly or perfectly rectangular.”
From Compact and microchannel heat exchangers: A comprehensive review of air-side friction factor and heat transfer correlations (2018) · cites this paper as [76]
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“No. of geometries tested to obtain the correlations is 15.”
From Compact and microchannel heat exchangers: A comprehensive review of air-side friction factor and heat transfer correlations (2018) · cites this paper as [76]
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“In excellent agreement with the experimental data”
From Compact and microchannel heat exchangers: A comprehensive review of air-side friction factor and heat transfer correlations (2018) · cites this paper as [76]
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“Valid over a range of geometries of FPI = 10 - 13.”
From Compact and microchannel heat exchangers: A comprehensive review of air-side friction factor and heat transfer correlations (2018) · cites this paper as [76]
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Research works printed but not linked: 20
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Cited by
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Qasem, N. A. A., & Zubair, S. M. (2018) · Energy Conversion and Management · doi:10.1016/j.enconman.2018.06.104 · Cited by 134
Metadata
- Authors
- Khoshvaght Aliabadi, M., Gholam Samani, M., Hormozi, F., & Haghighi Asl, A.
- Affiliations
- Semnan University, I. R. Iran
- Semnan University (IR)
- ORCID
- Hormozi, F
- Venue
- Brazilian Journal of Chemical Engineering
- Publisher
- FapUNIFESP (SciELO)
- Published
- 2011-09
- Volume
- 28
- Issue
- 3
- Pages
- 505-520
- ISSN
- 0104-6632 (ISSN-L)
- OpenAlex
- W2128724404
- Cited by
- 43
- References
- 0
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 3 · 2023: 3 · 2022: 3 · 2021: 1 · 2020: 3 · 2019: 3 · 2018: 7 · 2017: 3 · 2016: 2 · 2015: 1 · 2014: 5 · 2013: 3
- FWCI
- 4.54
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc
- Locations
- Brazilian Journal of Chemical Engineering (publishedVersion, cc-by-nc)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (publishedVersion, other-oa)
- Americanae (AECID Library) (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Engineering › Mechanical Engineering › Heat Transfer and Optimization
- Physical Sciences › Engineering › Mechanical Engineering › Heat Transfer Mechanisms
- Physical Sciences › Engineering › Computational Mechanics › Heat Transfer and Numerical Methods
- Keywords
- Colburn factor, Fanning friction factor, fin spacing, fin height, fin length, fin thickness, Reynolds number effects
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- The paper
- Khoshvaght Aliabadi, M., Gholam Samani, M., Hormozi, F., & Haghighi Asl, A. (2011). 3D-CFD simulation and neural network model for the j and f factors of the wavy fin-and-flat tube heat exchangers. Brazilian Journal of Chemical Engineering. https://doi.org/10.1590/s0104-66322011000300016
