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Entropy Generation Analysis and Performance Evaluation of Turbulent Forced Convective Heat Transfer to Nanofluids

by Yu Ji 1, Hao-Chun Zhang 2,*, Xie Yang 1 and Lei Shi 1,*
1
Institute of Nuclear and New Energy Technology, Collaborative Innovation Center of Advanced Nuclear Energy Technology, Key Laboratory of Advanced Reactor Engineering and Safety of Ministry of Education, Tsinghua University, Beijing 100084, China
2
School of Energy Science and Engineering, Harbin Institute of Technology, Harbin 150001, China
*
Authors to whom correspondence should be addressed.
Academic Editor: Yan Jin
Entropy 2017, 19(3), 108; https://doi.org/10.3390/e19030108
Received: 21 January 2017 / Revised: 26 February 2017 / Accepted: 8 March 2017 / Published: 11 March 2017
(This article belongs to the Special Issue Entropy in Computational Fluid Dynamics)
The entropy generation analysis of fully turbulent convective heat transfer to nanofluids in a circular tube is investigated numerically using the Reynolds Averaged Navier–Stokes (RANS) model. The nanofluids with particle concentration of 0%, 1%, 2%, 4% and 6% are treated as single phases of effective properties. The uniform heat flux is enforced at the tube wall. To confirm the validity of the numerical approach, the results have been compared with empirical correlations and analytical formula. The self-similarity profiles of local entropy generation are also studied, in which the peak values of entropy generation by direct dissipation, turbulent dissipation, mean temperature gradients and fluctuating temperature gradients for different Reynolds number as well as different particle concentration are observed. In addition, the effects of Reynolds number, volume fraction of nanoparticles and heat flux on total entropy generation and Bejan number are discussed. In the results, the intersection points of total entropy generation for water and four nanofluids are observed, when the entropy generation decrease before the intersection and increase after the intersection as the particle concentration increases. Finally, by definition of Ep, which combines the first law and second law of thermodynamics and attributed to evaluate the real performance of heat transfer processes, the optimal Reynolds number Reop corresponding to the best performance and the advisable Reynolds number Read providing the appropriate Reynolds number range for nanofluids in convective heat transfer can be determined. View Full-Text
Keywords: nanofluids; turbulent flow; convective heat transfer; entropy generation; performance evaluation nanofluids; turbulent flow; convective heat transfer; entropy generation; performance evaluation
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Ji, Y.; Zhang, H.-C.; Yang, X.; Shi, L. Entropy Generation Analysis and Performance Evaluation of Turbulent Forced Convective Heat Transfer to Nanofluids. Entropy 2017, 19, 108.

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