Predicting the thermal distribution in a convective wavy fin using a novel training physics-informed neural network method

Fins are widely used in many industrial applications, including heat exchangers. They benefit from a relatively economical design cost, are lightweight, and are quite miniature. Thus, this study investigates the influence of a wavy fin structure subjected to convective effects with internal heat gen...

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Vydáno v:	Scientific reports Ročník 14; číslo 1; s. 7045 - 14
Hlavní autoři:	Chandan, K., Saadeh, Rania, Qazza, Ahmad, Karthik, K., Varun Kumar, R. S., Kumar, R. Naveen, Khan, Umair, Masmoudi, Atef, Abdou, M. Modather M., Ojok, Walter, Kumar, Raman
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London Nature Publishing Group UK 25.03.2024 Nature Publishing Group Nature Portfolio
Témata:	639/4077 639/705 Boundary conditions Fin Heat exchangers Heat transfer Humanities and Social Sciences Industrial applications Internal heat generation Machine learning multidisciplinary Neural networks Nonlinear systems Ordinary differential equations Physics Physics-informed neural networks Science Science (multidisciplinary) Thermal conductivity Wavy fin Internal heat generation Fin Heat transfer Physics-informed neural networks Wavy fin
ISSN:	2045-2322, 2045-2322
On-line přístup:	Získat plný text
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