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

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Advanced Engineering Optimization Through Intelligent Techniques

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 949))

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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.

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Authors and Affiliations

  1. Government Engineering College, Kozhikode, India

    Ayamannil Sajeeb

  2. National Institute of Technology, Calicut, India

    Perikinalil Krishnan Rajendrakumar

Authors
  1. Ayamannil Sajeeb
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  2. Perikinalil Krishnan Rajendrakumar
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Correspondence to Ayamannil Sajeeb .

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Editors and Affiliations

  1. Sardar Vallabhbhai National Institute of Technology, Surat, Surat, Gujarat, India

    R. Venkata Rao

  2. Cracow University of Technology, Kraków, Poland

    Jan Taler

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Sajeeb, A., Rajendrakumar, P.K. (2020). Assessment of Viscosity of Coconut-Oil-Based CeO2/CuO Hybrid Nano-lubricant Using Artificial Neural Network. In: Venkata Rao, R., Taler, J. (eds) Advanced Engineering Optimization Through Intelligent Techniques. Advances in Intelligent Systems and Computing, vol 949. Springer, Singapore. https://doi.org/10.1007/978-981-13-8196-6_62

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