Stochastic Levenberg–Marquardt Neural Network Implementation for Analyzing the Convective Heat Transfer in a Wavy Fin
The present research examines the steady, one-dimensional thermal distribution and heat transfer of a wavy fin. This heat transfer analysis considers convective effects as well as temperature-dependent thermal conductivity. Furthermore, a novel implementation of a neural network with backpropagated...
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| Published in: | Mathematics (Basel) Vol. 11; no. 10; p. 2401 |
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| Main Authors: | , , , , |
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| Language: | English |
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| ISSN: | 2227-7390, 2227-7390 |
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| Abstract | The present research examines the steady, one-dimensional thermal distribution and heat transfer of a wavy fin. This heat transfer analysis considers convective effects as well as temperature-dependent thermal conductivity. Furthermore, a novel implementation of a neural network with backpropagated Levenberg–Marquardt algorithm (NN-BLMA)-based machine learning intelligent strategies is provided to interpret the heat transfer analysis of a convective wavy fin. The non-linear ordinary differential equation (ODE) of the study problem is converted into its non-dimensional form using the similarity transformation technique. The dimensionless equation obtained is then numerically explored via the Runge–Kutta–Fehlberg scheme. A data set for varying the pertinent parameters is generated, and an artificial neural network model is designed to estimate the heat transfer behavior of the wavy fin. The effectiveness of the proposed NN-BLMA is subsequently endorsed by analyses using a regression model, mean square error, and histograms. The findings of comprehensive computational parametric studies illustrate that the presented technique, NN-BLMA is an effective convergent stochastic numerical solver employed for the heat transfer model of the convective wavy fin. The wavy fin’s temperature dispersion optimizes as the thermal conductivity parameter rises. Heat transfer rate is higher in wavy fin compared to rectangular fin. |
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| AbstractList | The present research examines the steady, one-dimensional thermal distribution and heat transfer of a wavy fin. This heat transfer analysis considers convective effects as well as temperature-dependent thermal conductivity. Furthermore, a novel implementation of a neural network with backpropagated Levenberg-Marquardt algorithm (NN-BLMA)-based machine learning intelligent strategies is provided to interpret the heat transfer analysis of a convective wavy fin. The non-linear ordinary differential equation (ODE) of the study problem is converted into its non-dimensional form using the similarity transformation technique. The dimensionless equation obtained is then numerically explored via the Runge-Kutta-Fehlberg scheme. A data set for varying the pertinent parameters is generated, and an artificial neural network model is designed to estimate the heat transfer behavior of the wavy fin. The effectiveness of the proposed NN-BLMA is subsequently endorsed by analyses using a regression model, mean square error, and histograms. The findings of comprehensive computational parametric studies illustrate that the presented technique, NN-BLMA is an effective convergent stochastic numerical solver employed for the heat transfer model of the convective wavy fin. The wavy fin's temperature dispersion optimizes as the thermal conductivity parameter rises. Heat transfer rate is higher in wavy fin compared to rectangular fin. |
| Audience | Academic |
| Author | Sowmya, G. Kumar, R. S. Varun Gamaoun, Fehmi Alsulami, M. D. Sarris, I. E. |
| Author_xml | – sequence: 1 givenname: R. S. Varun surname: Kumar fullname: Kumar, R. S. Varun – sequence: 2 givenname: M. D. orcidid: 0000-0003-1971-7282 surname: Alsulami fullname: Alsulami, M. D. – sequence: 3 givenname: I. E. orcidid: 0000-0002-6542-0490 surname: Sarris fullname: Sarris, I. E. – sequence: 4 givenname: G. surname: Sowmya fullname: Sowmya, G. – sequence: 5 givenname: Fehmi surname: Gamaoun fullname: Gamaoun, Fehmi |
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| SubjectTerms | Air conditioning Algorithms Analysis artificial neural network Artificial neural networks Convective heat transfer Dimensionless numbers Electric properties fin Heat conductivity Heat exchangers Heat transfer Influence Investigations Machine learning Mathematics Neural networks Nonlinear differential equations Parameters Productivity Radiation Regression models Runge-Kutta method Temperature dependence temperature distribution Thermal conductivity wavy fin Wavy fins |
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| Title | Stochastic Levenberg–Marquardt Neural Network Implementation for Analyzing the Convective Heat Transfer in a Wavy Fin |
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