Prediction and Comparative Analysis of Thermal Conductivity of Jatropha Oil-based Hybrid Nanofluid by Multivariable Regression and ANN

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Year : September 22, 2023 | Volume : 11 | Issue : 08 | Page : –

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By

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    Amol Asalekar

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Abstract

nIn the present study, a multivariable regression (MR) and artificial neural network (ANN) method was used to predict the thermal conductivity of Jatropha oil-based ZnO-Ag hybrid nanofluid. Firstly, the ZnO-Ag hybrid nanoparticles were synthesized and mixed in the jatropha oil to prepare various nanofluids at different volume concentrations (F) ranging from 0.05 to 0.20%. The stability and thermal conductivity of the prepared nanofluids were investigated. Wide ranges of temperature and volume concentration as input data were used to predict the output parameters as thermal conductivity. In comparison with the multivariable regression, the artificial neural network (ANN) models, predict thermal conductivity values that are remarkably similar to the experimental values by offering a lower mean square error. This approach also aids with the issue of guesswork in figuring out the neural network layer’s hidden structure.

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Keywords: ANN, Thermal conductivity, hybrid nanofluid, Jatropha oil

n[if 424 equals=”Regular Issue”][This article belongs to Journal of Polymer and Composites(jopc)]

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[/if 424][if 424 equals=”Special Issue”][This article belongs to Special Issue under section in Journal of Polymer and Composites(jopc)][/if 424][if 424 equals=”Conference”]This article belongs to Special Issue Conference International Conference on Innovative Concepts in Mechanical Engineering (ICICME – 2023) [/if 424]

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How to cite this article: Amol Asalekar Prediction and Comparative Analysis of Thermal Conductivity of Jatropha Oil-based Hybrid Nanofluid by Multivariable Regression and ANN jopc September 22, 2023; 11:-

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How to cite this URL: Amol Asalekar Prediction and Comparative Analysis of Thermal Conductivity of Jatropha Oil-based Hybrid Nanofluid by Multivariable Regression and ANN jopc September 22, 2023 {cited September 22, 2023};11:-. Available from: https://journals.stmjournals.com/jopc/article=September 22, 2023/view=0/

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References

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Conference Open Access Original Research

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Journal of Polymer and Composites

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[if 344 not_equal=””]ISSN: 2321–2810[/if 344]

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Volume 11
Issue 08
Received August 18, 2023
Accepted September 12, 2023
Published September 22, 2023

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