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Digital Twin Modeling for the Analysis of Thermal and Mechanical Effects of Mutual Coupling in Power Transformer Windings
Author(s) -
Jalberth F. Araujo,
Filipe L. M. Andrade,
Edson G. Costa,
Henrique D. Silva
Publication year - 2025
Publication title -
ieee access
Language(s) - English
Resource type - Magazines
SCImago Journal Rank - 0.587
H-Index - 127
eISSN - 2169-3536
DOI - 10.1109/access.2025.3611116
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
In this work, digital twins are proposed to analyze the thermal and mechanical effects of mutual coupling in power transformer windings. To achieve this, construction data from two transformers were used to create computational models in the Comsol Multiphysics platform, enabling four case studies: thermal performance analysis, mechanical performance analysis, investigation of thermal expansion forces, and evaluation of thermal behavior under winding deformations. The results reveal a strong correlation between thermal and mechanical performance, a topic that has been scarcely explored in literature. The coupled simulations show that thermal stresses generate radial displacements even in scenarios where axial displacements would be expected. Furthermore, the analysis demonstrates that deformations, particularly in the radial direction, can significantly alter the thermal performance of the windings, increasing the hot-spot temperature by up to 11.9%. These findings provide new insights into the interplay between thermal and mechanical phenomena in transformer windings, supporting the development of more reliable designs, advanced monitoring strategies, and improved identification of potential failure causes.

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