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Modeling thermal conductivity of Ag/water nanofluid by applying a mathematical correlation and artificial neural network

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  • Mahdi Ramezanizadeh
  • Mohammad Alhuyi Nazari

Abstract

Due to the significance importance of effective thermal conductivity of heat transfer fluids in various renewable energy system, such as geothermal and solar thermal plants, using naofluids can result in augment in the efficiency. Metallic nano particles dispersion in a pure fluid leads to considerable enhancement in the thermal conductivity. The improvement in the thermal conductivity is dependent on various factors. In the present research, two machine learning algorithms, a correlation and Group Method of Data Handling, are applied to predict thermal conductivity of silver/water nanofluid. Temperature, concentration and size of solid particles are considered as the input data. According to statistical comparison of the models, employing GMDH artificial neural network results in more precise and appropriate model. The coefficients of correlation, R-squared values, for the proposed correlation and ANN-based models are 0.948 and 0.99 respectively.

Suggested Citation

  • Mahdi Ramezanizadeh & Mohammad Alhuyi Nazari, 2019. "Modeling thermal conductivity of Ag/water nanofluid by applying a mathematical correlation and artificial neural network," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 14(4), pages 468-474.
    • Handle: RePEc:oup:ijlctc:v:14:y:2019:i:4:p:468-474.
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    File URL: http://hdl.handle.net/10.1093/ijlct/ctz030
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    Cited by:

    1. Ali Komeili Birjandi & Morteza Fahim Alavi & Mohamed Salem & Mamdouh El Haj Assad & Natarajan Prabaharan, 2022. "Modeling carbon dioxide emission of countries in southeast of Asia by applying artificial neural network [Energy and exergy analyses of single flash geothermal power plant at optimum separator temp," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 17, pages 321-326.
    2. Anwar Saeed & Ebrahem A Algehyne & Musaad S Aldhabani & Abdullah Dawar & Poom Kumam & Wiyada Kumam, 2022. "Mixed convective flow of a magnetohydrodynamic Casson fluid through a permeable stretching sheet with first-order chemical reaction," PLOS ONE, Public Library of Science, vol. 17(4), pages 1-15, April.

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