IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v540y2020ics0378437119303668.html
   My bibliography  Save this article

Mathematical and artificial brain structure-based modeling of heat conductivity of water based nanofluid enriched by double wall carbon nanotubes

Author

Listed:
  • Hemmat Esfe, Mohammad
  • Afrand, Masoud

Abstract

Mathematical modeling based on response surface method and also an artificial brain structure-based model was applied to predict thermal properties of a water-based nanofluid earned by a set of laboratory results. Functionalized DWCNTs were used to enrich the conventional fluid (Water in the present study). Using response surface method a two-variable experimental based correlation proposed as a function of concentration and temperature. Also, artificial neural network employed as a brain structure-based approach with two inputs (temperature and concentrations) and thermal conductivity ratio as the desired output. Using mathematical and artificial based methods help to improve the economic efficiency of experimental studies.

Suggested Citation

  • Hemmat Esfe, Mohammad & Afrand, Masoud, 2020. "Mathematical and artificial brain structure-based modeling of heat conductivity of water based nanofluid enriched by double wall carbon nanotubes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    • Handle: RePEc:eee:phsmap:v:540:y:2020:i:c:s0378437119303668
    DOI: 10.1016/j.physa.2019.04.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119303668
    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.2019.04.002?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. Karimipour, Arash & Hemmat Esfe, Mohammad & Safaei, Mohammad Reza & Toghraie Semiromi, Davood & Jafari, Saeed & Kazi, S.N., 2014. "Mixed convection of copper–water nanofluid in a shallow inclined lid driven cavity using the lattice Boltzmann method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 150-168.
    2. Sheikholeslami, Mohsen & Ganji, Davood Domiri, 2015. "Entropy generation of nanofluid in presence of magnetic field using Lattice Boltzmann Method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 417(C), pages 273-286.
    3. Sheikholeslami, Mohsen & Bandpy, Mofid Gorji & Ashorynejad, Hamid Reza, 2015. "Lattice Boltzmann Method for simulation of magnetic field effect on hydrothermal behavior of nanofluid in a cubic cavity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 58-70.
    4. 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.
    5. Mahmoudi, Ahmed & Mejri, Imen & Omri, Ahmed, 2016. "Study of natural convection cooling of a nanofluid subjected to a magnetic field," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 333-348.
    6. Hajmohammadi, M.R. & Toghraei, I., 2018. "Optimal design and thermal performance improvement of a double-layered microchannel heat sink by introducing Al2O3 nano-particles into the water," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 328-344.
    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. Toghaniyan, Abolfazl & Zarringhalam, Majid & Akbari, Omid Ali & Sheikh Shabani, Gholamreza Ahmadi & Toghraie, Davood, 2018. "Application of lattice Boltzmann method and spinodal decomposition phenomenon for simulating two-phase thermal flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 673-689.
    2. Hajmohammadi, M.R. & Haji Molla Ali Tork, M.H., 2019. "Effects of the magnetic field on the cylindrical Couette flow and heat transfer of a nanofluid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 234-245.
    3. Hemmat Esfe, Mohammad & Esfandeh, Saeed, 2020. "The statistical investigation of multi-grade oil based nanofluids: Enriched by MWCNT and ZnO nanoparticles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).
    4. Safaei, Mohammad Reza & Karimipour, Arash & Abdollahi, Ali & Nguyen, Truong Khang, 2018. "The investigation of thermal radiation and free convection heat transfer mechanisms of nanofluid inside a shallow cavity by lattice Boltzmann method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 515-535.
    5. Ruhani, Behrooz & Toghraie, Davood & Hekmatifar, Maboud & Hadian, Mahdieh, 2019. "Statistical investigation for developing a new model for rheological behavior of ZnO–Ag (50%–50%)/Water hybrid Newtonian nanofluid using experimental data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 741-751.
    6. Hajmohammadi, M.R. & Toghraei, I., 2018. "Optimal design and thermal performance improvement of a double-layered microchannel heat sink by introducing Al2O3 nano-particles into the water," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 328-344.
    7. Sheikholeslami, Mohsen & Bandpy, Mofid Gorji & Ashorynejad, Hamid Reza, 2015. "Lattice Boltzmann Method for simulation of magnetic field effect on hydrothermal behavior of nanofluid in a cubic cavity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 58-70.
    8. Alsabery, A.I. & Chamkha, A.J. & Saleh, H. & Hashim, I. & Chanane, B., 2017. "Effects of finite wall thickness and sinusoidal heating on convection in nanofluid-saturated local thermal non-equilibrium porous cavity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 20-38.
    9. Selimefendigil, Fatih & Öztop, Hakan F., 2020. "Effects of conductive curved partition and magnetic field on natural convection and entropy generation in an inclined cavity filled with nanofluid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    10. Bahrami, Mehrdad & Akbari, Mohammad & Bagherzadeh, Seyed Amin & Karimipour, Arash & Afrand, Masoud & Goodarzi, Marjan, 2019. "Develop 24 dissimilar ANNs by suitable architectures & training algorithms via sensitivity analysis to better statistical presentation: Measure MSEs between targets & ANN for Fe–CuO/Eg–Water nanofluid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 159-168.
    11. Ahmadi Balootaki, Azam & Karimipour, Arash & Toghraie, Davood, 2018. "Nano scale lattice Boltzmann method to simulate the mixed convection heat transfer of air in a lid-driven cavity with an endothermic obstacle inside," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 681-701.
    12. Alsarraf, Jalal & Moradikazerouni, Alireza & Shahsavar, Amin & Afrand, Masoud & Salehipour, Hamzeh & Tran, Minh Duc, 2019. "Hydrothermal analysis of turbulent boehmite alumina nanofluid flow with different nanoparticle shapes in a minichannel heat exchanger using two-phase mixture model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 275-288.
    13. Sheikholeslami, Mohsen & Gorji-Bandpy, Mofid & Ganji, Davood Domiri, 2015. "Review of heat transfer enhancement methods: Focus on passive methods using swirl flow devices," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 444-469.
    14. Lucia, Umberto & Grisolia, Giulia & Francia, Sabrina & Astori, Mariarosa, 2019. "Theoretical biophysical approach to cross-linking effects on eyes pressure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    15. Khaje khabaz, Moahamad & Eftekhari, S. Ali & Hashemian, Mohamad & Toghraie, Davood, 2020. "Optimal vibration control of multi-layer micro-beams actuated by piezoelectric layer based on modified couple stress and surface stress elasticity theories," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 546(C).
    16. 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.
    17. Solangi, K.H. & Kazi, S.N. & Luhur, M.R. & Badarudin, A. & Amiri, A. & Sadri, Rad & Zubir, M.N.M. & Gharehkhani, Samira & Teng, K.H., 2015. "A comprehensive review of thermo-physical properties and convective heat transfer to nanofluids," Energy, Elsevier, vol. 89(C), pages 1065-1086.
    18. Mahyari, Amirhossein Ansari & Karimipour, Arash & Afrand, Masoud, 2019. "Effects of dispersed added Graphene Oxide-Silicon Carbide nanoparticles to present a statistical formulation for the mixture thermal properties," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 98-112.
    19. Afrouzi, Hamid Hassanzadeh & Ahmadian, Majid & Moshfegh, Abouzar & Toghraie, Davood & Javadzadegan, Ashkan, 2019. "Statistical analysis of pulsating non-Newtonian flow in a corrugated channel using Lattice-Boltzmann method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    20. Li, Zhixiong & Sheikholeslami, M. & Ayani, M. & Shamlooei, M. & Shafee, Ahmad & Waly, Mohamed Ibrahim & Tlili, I., 2019. "Acceleration of solidification process by means of nanoparticles in an energy storage enclosure using numerical approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 540-552.

    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:540:y:2020:i:c:s0378437119303668. 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.