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Assessment of Viscosity of Coconut-Oil-Based CeO2/CuO Hybrid Nano-lubricant Using Artificial Neural Network

  • Ayamannil SajeebEmail author
  • Perikinalil Krishnan Rajendrakumar
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 949)

Abstract

In the present work, coconut-oil-based hybrid nano-lubricants are prepared by dispersing CeO2 and CuO nanoparticles in three different proportions 75/25, 50/50, and 25/75. Experimental studies on the viscosity of hybrid nano-lubricants have been carried out by varying the concentration of combined nanoparticles in weight % from 0 to 1% and temperature ranging from 30 to 60 °C for each proportion of CeO2/CuO nanoparticles. A new empirical correlation and an optimal artificial neural network (ANN) for each proportion of CeO2/CuO nanoparticles in terms of temperature and concentration are devised to assess the viscosity ratio of hybrid nano-lubricant, using 48 experimental data. The results showed that the output of correlation and optimal ANN have a margin of deviation of 2 and 1%, respectively, and hence, the optimal artificial neural network is better in predicting the viscosity of hybrid nano-lubricant in comparison with empirical correlation.

Keywords

ANN Hybrid nano-lubricant Viscosity Coconut oil Correlation 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Ayamannil Sajeeb
    • 1
    Email author
  • Perikinalil Krishnan Rajendrakumar
    • 2
  1. 1.Government Engineering CollegeKozhikodeIndia
  2. 2.National Institute of TechnologyCalicutIndia

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