Optimizing flow properties of the different nanofluids inside a circular tube by using entropy generation minimization approach

被引：0
作者：
Behnam Mohseni-Gharyehsafa
Amir Ebrahimi-Moghadam
V. Okati
Mahmood Farzaneh-Gord
Mohammad Hossein Ahmadi
Giulio Lorenzini
机构：
[1] Shahrood University of Technology,Faculty of Mechanical Engineering
[2] Islamic Azad University,Young Researchers and Elite Club, Mashhad Branch
[3] Chabahar Maritime University,Faculty of Marine Engineering
[4] Università degli Studi di Parma,Dipartimento di Ingegneria e Architettura
来源：
Journal of Thermal Analysis and Calorimetry | 2019年 / 135卷
关键词：
Nanofluid; EGM method; Optimization;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The use of nanofluids as working fluid is one of the represented methods in efficiency enhancement of various systems. One of the most important subjects in nanofluid utilization is finding the optimal conditions. In this study, the efforts have been made to find optimal condition of forced convection nanofluid flow inside a circular tube. The flow is assumed turbulent, and optimization process is carried out for two metallic oxide nanoparticles (Al2O3, CuO) and one nonmetallic oxide nanoparticle (SiO2), dispersed in a 60:40% ethylene glycol/water base fluid. The optimization process has been performed based on the second law of thermodynamic and entropy generation minimization approach. The process has been focused on finding the optimal values for volume fraction, Reynolds number, diameter of particles and average flow temperature. Results show that two metallic oxide nanofluids generate less entropy compared with nonmetallic oxide nanofluid. In addition, comparing these two metallic oxide nanofluids, the maximum amount of total entropy generation is 20% lower when CuO nanoparticles added to the base fluid instead of Al2O3.
引用
收藏
页码：801 / 811
页数：10
相关论文
共 112 条
  • [21] Pantoja J(2012)Heat transfer enhancement analysis of tube receiver for parabolic trough solar collector with pin fin arrays inserting Int J Heat Mass Transf 77 403-413
  • [22] Moreira J(2014)Hybrid optimization algorithm for thermal analysis in a solar parabolic trough collector based on nanofluid Energy 53 4757-4767
  • [23] Reyes JA(2010)Entropy generation during Al Int J Heat Mass Transf 111 804-816
  • [24] Hosseinnezhad R(2017)O Int J Heat Mass Transf 89 694-706
  • [25] Akbari OA(2015)/water nanofluid flow in a solar collector: effects of tube roughness, nanoparticle size, and different thermophysical models Int J Heat Mass Transf 222 159-166
  • [26] Hassanzadeh Afrouzi H(2016)A new frontier of nanofluid research—application of nanofluids in heat pipes J Mol Liq 5 587-596
  • [27] Biglarian M(1980)Tube-in-tube helical heat exchangers performance optimization by entropy generation minimization approach Energy 10 21-29
  • [28] Koveiti A(1989)Entropy generation minimization for the thermal decomposition of methane gas in hydrogen using genetic algorithms ASME AES 10 125-139
  • [29] Toghraie D(2010)The shape effects of nanoparticles suspended in HFE-7100 over wedge with entropy generation and mixed convection Clim Dyn 85 3036-3045
  • [30] Esfahani JA(2011)Heat transfer and entropy generation analysis of turbulent flow of TiO Sol Energy 157 514-531
12345678910