IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v531y2019ics0378437119304273.html
   My bibliography  Save this article

Curve fitting on experimental data of a new hybrid nano-antifreeze viscosity: Presenting new correlations for non-Newtonian nanofluid

Author

Listed:
  • Irani, Mohammadhossein
  • Afrand, Masoud
  • Mehmandoust, Babak

Abstract

In this paper, the rheological behavior of a mixture of water and ethylene glycol containing a combination of multi-walled carbon nanotubes and aluminum oxide in a temperature range of 25 to 50 °C was investigated experimentally. Homogeneous and stable samples with different concentrations were made by suspending carbon nanotubes and aluminum dioxide in a 50–50 mixture of water and ethylene glycol using a two-step method. The viscosity of nanofluid samples at different shear rates was measured by the DV-I PRIME Brookfield digital viscometer, which uses a rotating cylinder method. The results showed that, despite the Newtonian behavior of the base fluid, all nanofluid samples showed a non-Newtonian behavior. It was also observed that non-Newtonian behavior of nanofluid follows the Power law model. Thus, using the curve fitting, the consistency index and the power law index were obtained. Moreover, mathematical correlations were proposed as a function of temperature and volume fraction for obtaining consistency index and the power-law index. Comparisons showed the accuracy of proposed correlations.

Suggested Citation

  • Irani, Mohammadhossein & Afrand, Masoud & Mehmandoust, Babak, 2019. "Curve fitting on experimental data of a new hybrid nano-antifreeze viscosity: Presenting new correlations for non-Newtonian nanofluid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
  • Handle: RePEc:eee:phsmap:v:531:y:2019:i:c:s0378437119304273
    DOI: 10.1016/j.physa.2019.04.073
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119304273
    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.2019.04.073?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tian, Zhe & Rostami, Sara & Taherialekouhi, Roozbeh & Karimipour, Arash & Moradikazerouni, Alireza & Yarmand, Hooman & Zulkifli, Nurin Wahidah Binti Mohd, 2020. "Prediction of rheological behavior of a new hybrid nanofluid consists of copper oxide and multi wall carbon nanotubes suspended in a mixture of water and ethylene glycol using curve-fitting on experim," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    2. Xiaohong, Dai & Huajiang, Chen & Bagherzadeh, Seyed Amin & Shayan, Masoud & Akbari, Mohammad, 2020. "Statistical estimation the thermal conductivity of MWCNTs-SiO2/Water-EG nanofluid using the ridge regression method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    3. Sarafraz, M.M. & Tlili, I. & Tian, Zhe & Bakouri, Mohsen & Safaei, Mohammad Reza, 2019. "Smart optimization of a thermosyphon heat pipe for an evacuated tube solar collector using response surface methodology (RSM)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    4. 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).

    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:531:y:2019:i:c:s0378437119304273. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.