IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v536y2019ics0378437119314360.html
   My bibliography  Save this article

Statistical and experimental investigation on flow boiling heat transfer to carbon nanotube-therminol nanofluid

Author

Listed:
  • Sarafraz, M.M.
  • Abad, A. Taghavi Khalil

Abstract

In the present work, statistical, regression and experimental studies were conducted to assess the plausible application of an oil-based carbon nanotube nanofluid for high-temperature applications such as solar thermal receivers. Nanofluid was prepared at wt. %=0.1 and wt. %=3 using two-step procedure and was stabilized using ultrasonic together with the addition of surfactant. As a criterion for the stability of nanofluid, the zeta potential value was measured. Results showed that during flow boiling heat transfer, two distinguished heat transfer regions were identified namely forced convective and nucleate boiling heat transfer domains. Likewise, the presence of carbon nanotube within the oil increased the convective heat transfer coefficient (HTC) together with a significant increase in the nucleate boiling HTC. An increase in the heat and mass fluxes were found to enhance the flow boiling HTC both in convective and nucleate boiling regions. The sub-cooling temperature was also found to increase the HTC in convective and nucleate boiling regions due to the enhancement in thermo-physical properties of nanofluid. With an increase in the mass flux, the pressure drop of the system was increased. Heat flux was also enhanced the pressure drop within the system due to the increase in the rate of bubble generation and vapor blanket formation. Likewise, with an increase in the mass concentration of nanoparticles, higher pressure drop was registered in convective and nucleate boiling regions. Thermal performance index of the system showed that carbon nanotube can increase the thermo-hydraulic performance of the system by 56% in comparison with pure therminol 66. Equations were developed to predict the ONB points at various temperatures with A. A. D.% of ±0.9% to ±4.2% obtained with non-linear regression.

Suggested Citation

  • Sarafraz, M.M. & Abad, A. Taghavi Khalil, 2019. "Statistical and experimental investigation on flow boiling heat transfer to carbon nanotube-therminol nanofluid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    • Handle: RePEc:eee:phsmap:v:536:y:2019:i:c:s0378437119314360
    DOI: 10.1016/j.physa.2019.122505
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119314360
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2019.122505?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Godson, Lazarus & Raja, B. & Mohan Lal, D. & Wongwises, S., 2010. "Enhancement of heat transfer using nanofluids--An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(2), pages 629-641, February.
    2. Hemmat Esfe, Mohammad & Rostamian, Hossein & Esfandeh, Saeed & Afrand, Masoud, 2018. "Modeling and prediction of rheological behavior of Al2O3-MWCNT/5W50 hybrid nano-lubricant by artificial neural network using experimental data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 625-634.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ma, Ting & Guo, Zhixiong & Lin, Mei & Wang, Qiuwang, 2021. "Recent trends on nanofluid heat transfer machine learning research applied to renewable energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    2. Salman, B.H. & Mohammed, H.A. & Munisamy, K.M. & Kherbeet, A. Sh., 2013. "Characteristics of heat transfer and fluid flow in microtube and microchannel using conventional fluids and nanofluids: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 848-880.
    3. Tawfik, Mohamed M., 2017. "Experimental studies of nanofluid thermal conductivity enhancement and applications: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 1239-1253.
    4. Amaris, Carlos & Vallès, Manel & Bourouis, Mahmoud, 2018. "Vapour absorption enhancement using passive techniques for absorption cooling/heating technologies: A review," Applied Energy, Elsevier, vol. 231(C), pages 826-853.
    5. Ajbar, Wassila & Parrales, A. & Huicochea, A. & Hernández, J.A., 2022. "Different ways to improve parabolic trough solar collectors’ performance over the last four decades and their applications: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    6. Janusz T. Cieśliński & Dawid Lubocki & Slawomir Smolen, 2022. "Impact of Temperature and Nanoparticle Concentration on Turbulent Forced Convective Heat Transfer of Nanofluids," Energies, MDPI, vol. 15(20), pages 1-22, October.
    7. Pawel Rozga & Abderrahmane Beroual & Piotr Przybylek & Maciej Jaroszewski & Konrad Strzelecki, 2020. "A Review on Synthetic Ester Liquids for Transformer Applications," Energies, MDPI, vol. 13(23), pages 1-33, December.
    8. Al-Rashed, Abdullah A.A.A., 2019. "Optimization of heat transfer and pressure drop of nano-antifreeze using statistical method of response surface methodology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 531-542.
    9. Xu, Yanyan & Xue, Yanqin & Qi, Hong & Cai, Weihua, 2021. "An updated review on working fluids, operation mechanisms, and applications of pulsating heat pipes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    10. Hemmat Esfe, Mohammad & Abbasian Arani, Ali Akbar & Esfandeh, Saeed & Afrand, Masoud, 2019. "Proposing new hybrid nano-engine oil for lubrication of internal combustion engines: Preventing cold start engine damages and saving energy," Energy, Elsevier, vol. 170(C), pages 228-238.
    11. He, Wei & Zhang, Jifang & Guo, Rui & Pei, Chenchen & Li, Hailong & Liu, Shengchun & Wei, Jie & Wang, Yulin, 2022. "Performance analysis and structural optimization of a finned liquid-cooling radiator for chip heat dissipation," Applied Energy, Elsevier, vol. 327(C).
    12. Che Sidik, Nor Azwadi & Aisyah Razali, Siti, 2014. "Lattice Boltzmann method for convective heat transfer of nanofluids – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 864-875.
    13. Wu, Zan & Sundén, Bengt, 2014. "On further enhancement of single-phase and flow boiling heat transfer in micro/minichannels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 11-27.
    14. Moghadam, Iman Panahi & Afrand, Masoud & Hamad, Samir M. & Barzinjy, Azeez A. & Talebizadehsardari, Pouyan, 2020. "Curve-fitting on experimental data for predicting the thermal-conductivity of a new generated hybrid nanofluid of graphene oxide-titanium oxide/water," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 548(C).
    15. Rasikh Tariq & Changhong Zhan & Nadeem Ahmed Sheikh & Xudong Zhao, 2018. "Thermal Performance Enhancement of a Cross-Flow-Type Maisotsenko Heat and Mass Exchanger Using Various Nanofluids," Energies, MDPI, vol. 11(10), pages 1-19, October.
    16. Azmi, W.H. & Sharma, K.V. & Mamat, Rizalman & Najafi, G. & Mohamad, M.S., 2016. "The enhancement of effective thermal conductivity and effective dynamic viscosity of nanofluids – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 1046-1058.
    17. Javadi, F.S. & Saidur, R. & Kamalisarvestani, M., 2013. "Investigating performance improvement of solar collectors by using nanofluids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 232-245.
    18. Chen, Zhixiong & Ashkezari, Abbas Zarenezhad & Tlili, Iskander, 2020. "Applying artificial neural network and curve fitting method to predict the viscosity of SAE50/MWCNTs-TiO2 hybrid nanolubricant," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    19. Alnaqi, Abdulwahab A. & Sayyad Tavoos Hal, Sina & Aghaei, Alireza & Soltanimehr, Mehdi & Afrand, Masoud & Nguyen, Truong Khang, 2019. "Predicting the effect of functionalized multi-walled carbon nanotubes on thermal performance factor of water under various Reynolds number using artificial neural network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 493-500.
    20. Sharma, Anuj Kumar & Tiwari, Arun Kumar & Dixit, Amit Rai, 2016. "Rheological behaviour of nanofluids: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 779-791.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:536:y:2019:i:c:s0378437119314360. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.