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Modeling and prediction of thermal conductivity ratio of metal-oxide based nano-fluids using artificial neural network and power law

Treść / Zawartość
Identyfikatory
Warianty tytułu
Konferencja
The International Chemical Engineering Conference 2021 (ICHEEC): 100 Glorious Years of Chemical Engineering and Technology, September 16–19, 2021
Języki publikacji
EN
Abstrakty
EN
In this study, the thermal conductivity ratio model for metallic oxide based nano-fluids is proposed. The model was developed by considering the thermal conductivity as a function of particle concentration (percentage volume), temperature, particle size and thermal conductivity of the base fluid and nano-particles. The experimental results for Al2O3, CuO, ZnO, and TiO2 particles dispersed in ethylene glycol, water and a combination of both were adopted from the literature. Artificial neural network (ANN) and power law models were developed and compared with the experimental data based on statistical methods. ANOVA was used to determine the relative importance of contributing factors, which revealed that the concentration of nano-particles in a fluid is the single most important contributing factor of the conductivity ratio.
Rocznik
Strony
159–--163
Opis fizyczny
Bibliogr. 13 poz.,
Twórcy
  • Mechanical Engineering Department, National Institute of Technology Srinagar, India
autor
  • Mechanical Engineering Department, National Institute of Technology Srinagar, India
autor
  • Chemical Engineering Department, National Institute of Technology Srinagar, India
Bibliografia
  • 1. Chandrasekar M., Suresh S., Senthilkumar T., 2012. Mechanisms proposed through experimental investigations on thermo-physical properties and forced convective heat transfer characteristics of various nano-fluids – A review. Renewable Sustainable Energy Rev., 16, 3917–3938. DOI: 10.1016/j.rser.2012.03.013.
  • 2. Choi S., Eastman J.A., 1995. Enhancing thermal conductivity of fluids with nano-particles. 1995 International mechanical engineering congress and exhibition. San Francisco, CA, United States, 12–17 November 1995, 99–105.
  • 3. Koo J., Clement K., 2004. A new thermal conductivity model for nano fluids. J. Nanopart. Res., 6, 577–588. DOI: 10.1007/s11051-004-3170-5.
  • 4. Kumar N., Sonawane S.S., Sonawani S.H., 2018. Experimental study of thermal conductivity, heat transfer and friction factorof Al2O3 based nano-fluids. Int. Commun. Heat Mass Transfer, 90, 1–10. DOI: 10.1016/j.icheatmass transfer.2017.10.001.
  • 5. Lee J.-H., Hwang K.S., Jang S.P., Lee B.H., Kim J.H., Choi S.U.S., Choi C.J., 2008. Effective viscosities and thermal conductivities of aqueous nano-fluids containing low volume concentration (percentage volume) of Al2O3 nano-particles. Int. J. Heat Mass Transfer, 51, 2651–2656. DOI: 10.1016/j.ijheatmasstransfer.2007.10.026.
  • 6. Lee J., Lee H., Baik Y.-J., Koo J., 2015. Quantitative analyses of factors affecting thermal conductivity of nano fluids using an improves transient hot-wire method apparatus. Int. J. Heat Mass Transfer, 89, 116–123. DOI: 10.1016/j.ijheatmasstransfer.2015.05.064.
  • 7. Mohanraj M., Jayaraj S., Muraleedharan C., 2012. Applications of artificial neural networks for refrigeration, air-conditioning and heat pump systems – A review. Renewable Sustainable Energy Rev., 16, 1340–1358. DOI: 10.1016/j.rser.2011.10.015.
  • 8. Putra N., Roetzel W., Das S.K., 2003. Natural convection of nano-fluids. Heat Mass Transfer, 39, 775–784. DOI: 10.1007/s00231-002-0382-z.
  • 9. Sayes C.M., Liang F., Hudson J.L., Mendez J., Guo W., Beach J.M., Moore V.C., Doyle C.D., West J.L., Billups W.E., Ausman K.D., Colvin V.L., 2006. Functionalization density dependence of single-walled carbon nano-tubes cytotoxicity in vitro. Toxicol. Lett., 161, 135–142. DOI: 10.1016/j.toxlet.2005.08.011.
  • 10. Sundar L.S., 2014. Thermal conductivity and viscosity of stabilized ethylene glycol and water mixture Al2O3 nanofluids for heat transfer applications: An experimental study. Int. Commun. Heat Mass Transfer, 56, 86–95. DOI: 10.1016/j.icheatmasstransfer.2014.06.009.
  • 11. Wang X.-Q., Mujumdar A.S., Yap C., 2006. Thermal characteristics of tree-shaped microchannel nets for cooling of a rectangular heat sink. Int. J. Therm. Sci., 45, 1103–1112. DOI: 10.1016/j.ijthermalsci.2006.01.010.
  • 12. Wang X., Xu X., Choi S.U.S., 2005. Thermal conductivity of nanoparticles –fluid mixture. J. Thermophys. Heat Transfer, 13, 474–480. DOI: 10.2514/2.6486.
  • 13. Yiamsawasd T., Dalkilic A.S., Wongwises S., 2012. Measurement of the thermal conductivity of titania and alumina nano-fluids. Thermochim. Acta, 545, 48–56. DOI: 10.1016/j.tca.2012.06.026.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-682e0625-e7a0-46a5-9158-c3dffb7f0acc
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