Reliable prediction of thermophysical properties of nanofluids for enhanced heat transfer in process industry: a perspective on bridging the gap between experiments, CFD and machine learning
Author:
Publisher
Springer Science and Business Media LLC
Subject
Physical and Theoretical Chemistry,Condensed Matter Physics
Link
https://link.springer.com/content/pdf/10.1007/s10973-023-12083-7.pdf
Reference123 articles.
1. Said Z, Sundar LS, Tiwari AK, Ali HM, Sheikholeslami M, Bellos E, Babar H. Recent advances on the fundamental physical phenomena behind stability, dynamic motion, thermophysical properties, heat transport, applications, and challenges of nanofluids. Phy Reports. 2022;946:1–94. https://www.sciencedirect.com/science/article/pii/S0370157321002775
2. Said A, Hachicha AA, Aberoumand S, Yousef BAA, Sayed, ET Bellos E. Recent advances on nanofluids for low to medium temperature solar collectors: energy, exergy, economic analysis and environmental impact. Progr Energy Combus Sci. 2021;84:100898. https://www.sciencedirect.com/science/article/pii/S0360128520301088
3. Ma T, Guo Z, Lin M, Wang Q. Recent trends on nanofluid heat transfer machine learning research applied to renewable energy. Renew Sustain Energy Rev. 2021;138:10494. https://www.sciencedirect.com/science/article/pii/S1364032120307802
4. Khanafer K, Vafai K. A review on the applications of nanofluids in solar energy field. Renew Energy. 2018;123:398–406. https://www.sciencedirect.com/science/article/pii/S0960148118301071
5. Buongiorno J, Hu LW, Kim SJ, Hannink R, Truong B, Forrest E. Nanofluids for enhanced economics and safety of nuclear reactors: an evaluation of the potential features, issues, and research gaps. Nucl Technol. 2008;162(1):80–91. https://doi.org/10.13182/NT08-A3934.
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