Forecasting the thermal conductivity of a nanofluid using artificial neural networks
Forecasting the thermal conductivity of a nanofluid using artificial neural networks
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Cham: Springer International Publishing
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English
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Cham: Springer International Publishing
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In this study, the influence of incorporating MWCNT on the thermal conductivity of paraffin was evaluated numerically. Input variables including mass fraction (0.005–5%) and temperature (25–70 °C) were introduced as input and nanofluid thermal conductivity was considered as an output parameter. Thermal conductivity was modeled numerically through t...
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Forecasting the thermal conductivity of a nanofluid using artificial neural networks
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TN_cdi_proquest_journals_2557851347
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2557851347
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ISSN
1388-6150
E-ISSN
1588-2926
DOI
10.1007/s10973-020-10183-2
