2021
DOI: 10.1002/htj.22116
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Numerical investigation of the thermo‐hydraulic performance of water‐based nanofluids in a dimpled channel flow using Al2O3, CuO, and hybrid Al2O3–CuO as nanoparticles

Abstract: In this study, the authors study the impact of spherical dimple surfaces and nanofluid coolants on heat transfer and pressure drop. The main objective of this paper is to evaluate the thermal performance of nanofluids with respect to different Reynolds numbers (Re) and nanoparticle compositions in dimpled channel flow. Water‐based nanofluids with Al 2 O 3, CuO, and Al 2 O 3–CuO nanoparticles are considered for this investigation with 1%, 2%, and 4% volume fraction for each nanofluid. The simulations are cond… Show more

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Cited by 21 publications
(9 citation statements)
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References 77 publications
(101 reference statements)
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“…This allows us to conclude that the addition of nanoparticles in the fluid base increases the pressure drop across the elbow. The behavior has been observed by a previous numerical study 43 …”
Section: Resultssupporting
confidence: 74%
“…This allows us to conclude that the addition of nanoparticles in the fluid base increases the pressure drop across the elbow. The behavior has been observed by a previous numerical study 43 …”
Section: Resultssupporting
confidence: 74%
“…Al-Obaidi et al 28 numerically examined the pressure drop and heat transfer within circular pipes of different configurations by using a FLUENT CFD solver. A similar study was published by Ahmed et al 29 on the impact of dimpled channels filled with nanofluids on heat transfer thermal performance. Their results showed that dimpled channels produced higher heat transfer coefficients of around (35%-46%) than the smooth channel.…”
Section: Introductionsupporting
confidence: 66%
“…Viscosity of nanofluid is 13,14,17,21,22,24 To predict the streamline curvature near the wall, the renormalization group (RNG), the k-ε model is taken up. The governing equations for part of continuity, part of the momentum, and part of energy conservation, k and ε model is articulated as follows:…”
Section: Characterization Of Nanofluidsmentioning
confidence: 99%
“…The specific heat of a nanofluid 13,14,17,21,22,24 false(Cpfalse)nf=(1ϕ)false(ρCpfalse)f+ϕfalse(ρCpfalse)npρnf.…”
Section: Introductionmentioning
confidence: 99%
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