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

Open Access

Year : 2023 | Volume :11 | Special Issue : 08 | Page : 32-39
By

    Amol J. Asalekar

  1. D.V.A. Rama Sastry

1·¹ Research Scholar, Department of Mechanical Engineering, Koneru Lakshmaiah Educational Foundation, Green Fields, Vaddeswaram, Guntur, Andhra Pradesh, India
1·² Assistant Professor, School of Mechanical Engineering, MIT Academy of Engineering, Alandi Pune, Maharashtra-, India
2. Associate Professor, Department of Mechanical Engineering, Koneru Lakshmaiah Educational Foundation, Green Fields, Vaddeswaram, Guntur, Andhra Pradesh, India

Abstract

In 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.

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

This article belongs to Special Issue Conference International Conference on Innovative Concepts in Mechanical Engineering (ICICME – 2023)

How to cite this article: Amol J. Asalekar, D.V.A. Rama Sastry Prediction and Comparative Analysis of Thermal Conductivity of Jatropha Oil-based Hybrid Nanofluid by Multivariable Regression and ANN jopc 2023; 11:32-39
How to cite this URL: Amol J. Asalekar, D.V.A. Rama Sastry Prediction and Comparative Analysis of Thermal Conductivity of Jatropha Oil-based Hybrid Nanofluid by Multivariable Regression and ANN jopc 2023 {cited 2023 Nov 14};11:32-39. Available from: https://journals.stmjournals.com/jopc/article=2023/view=126248

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Conference Open Access Original Research
Volume 11
Special Issue 08
Received August 18, 2023
Accepted September 12, 2023
Published November 14, 2023