Artificial neural network for prediction of thermal conductivity of rGO–metal oxide nanocomposite-based nanofluids
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-021-06366-z.pdf
Reference91 articles.
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3. Das SK, Choi SUS, Patel HE (2006) Heat transfer in nanofluids—a review. Heat Transf Eng 27:3–19. https://doi.org/10.1080/01457630600904593
4. Suganthi KS, Rajan KS (2017) Metal oxide nanofluids: review of formulation, thermo-physical properties, mechanisms, and heat transfer performance. Renew Sustain Energy Rev 76:226–255. https://doi.org/10.1016/j.rser.2017.03.043
5. Kumar V, Pandya N, Pandya B, Joshi A (2019) Synthesis of metal-based nanofluids and their thermo-hydraulic performance in compact heat exchanger with multi-louvered fins working under laminar conditions. J Therm Anal Calorim 135:2221–2235. https://doi.org/10.1007/s10973-018-7304-x
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