2022
DOI: 10.1016/j.applthermaleng.2022.118633
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Performance characterization of a solar-powered shell and tube heat exchanger utilizing MWCNTs/water-based nanofluids: An experimental, numerical, and artificial intelligence approach

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Cited by 59 publications
(25 citation statements)
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“…The greatest drop in heat resistance is 0.181 °C/W for numerical prediction, which is 5.78% lower than the experimental values. Zafar Said et al [31] and Stalin et al [32] confirmed that the introduction of high conductive nanoparticles within the working medium could enhance the heat transfer properties at a determined optimum weight fraction.…”
Section: Results Validationmentioning
confidence: 99%
“…The greatest drop in heat resistance is 0.181 °C/W for numerical prediction, which is 5.78% lower than the experimental values. Zafar Said et al [31] and Stalin et al [32] confirmed that the introduction of high conductive nanoparticles within the working medium could enhance the heat transfer properties at a determined optimum weight fraction.…”
Section: Results Validationmentioning
confidence: 99%
“…The proposed models can help to reduce the time and resources needed for experiments. Also, the models in the present study can be used in a variety of applications such as heat sinks [85][86][87] , heat pipes 88 , microchannels 89,90 , heat exchangers [91][92][93] , enclosures 94,95 , solar energy 9,96,97 and automotive industry [98][99][100][101] .…”
Section: Combinatorial (Combi) Algorithmmentioning
confidence: 99%
“…It was determined that hybrid nanofluid's collector energy efficiency is greater than that of other working fluids. An experimental investigation to analyze the performance of a solar-powered shell and tube heat exchanger using MWCNTs/ water-based nanofluids was performed by Said et al 24 . At 0.3% vol., the heat transfer coefficient was improved by 31.08%.…”
Section: Introductionmentioning
confidence: 99%