FAR EASTERN BRANCH OF THE RUSSIAN ACADEMY OF SCIENCES
INSTITUTE OF APPLIED MATHEMATICS KHABAROVSK DIVISION
Far Eastern Mathematical Journal
Numerical Analysis of Mass Transfer and Phase Change Problems Using Neural Networks |
Kuznetsov K. S. |
2025, issue 2, P. 218-231 DOI: https://doi.org/10.47910/FEMJ202515 |
Abstract |
| Problems related to phase change and mass transfer are characterized by high nonlinearity, moving boundaries and sharp changes in parameters, which complicates their numerical solution by traditional methods. The aim of this work is to study the possibility of using a new method Physics Informed Neural Networks, which uses neural networks to approximate unknowns, to solve such problems. The method was applied to solve Stefan problems for one and two phases, as well as to numerically analyze the problem of the motion of a gas bubble surrounded by a liquid. The method demonstrated good agreement with other solutions for Stefan problems and made it possible to simulate the bubble motion, although with some errors. There is significant potential for further development of this method for solving heat and mass transfer problems. |
Keywords: phase change, mass transfer, Stefan problem, neural networks. |
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References |
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