Shu Niu, Shuai Li, Jizhong Liang, Guodong Li, Fan Hu, Hai Zhan, Yujie Zhu, Xianhao Fan, Chuanyang Li. Study on the Thermal Aging Region Growth Model of Epoxy Resin Based on the Phase-Field Method[J]. Chinese Journal of Electrical Engineering, 2025, 11(3): 60-67. DOI: 10.23919/CJEE.2025.000149
Citation: Shu Niu, Shuai Li, Jizhong Liang, Guodong Li, Fan Hu, Hai Zhan, Yujie Zhu, Xianhao Fan, Chuanyang Li. Study on the Thermal Aging Region Growth Model of Epoxy Resin Based on the Phase-Field Method[J]. Chinese Journal of Electrical Engineering, 2025, 11(3): 60-67. DOI: 10.23919/CJEE.2025.000149

Study on the Thermal Aging Region Growth Model of Epoxy Resin Based on the Phase-Field Method

  • Epoxy resin is widely used in electrical insulation because of its excellent mechanical and insulating properties; however, its performance can degrade over time owing to thermal aging. This study focuses on developing a thermal aging region growth model for epoxy resin using the phase-field method. The reliability of the model is validated by applying a 20 MV/m electric field and observing the evolution of aging regions and the distribution of the internal energy density. A Gaussian-distributed aging region near the electrodes confirmed that the model accurately captured the uniform growth of aging regions under a constant electric field, with thermal energy playing a dominant role in the aging process. To examine the impact of internal defects, a fully aged region is introduced at the center of the simulation domain to simulate the effects of cavity discharge. The results indicated that while aging regions within defects grew rapidly, the overall growth remained slow and stable and is primarily influenced by charge diffusion. Further analysis explored the effects of the internal cavity defects near the electrodes. The presence of defects attracted the aging regions, causing them to grow uniformly without significant morphological changes, highlighting the interplay between thermal and charge-induced aging. The phase-field model effectively captures the dynamics of the aging regions influenced by internal defects, gradient energy, and charge diffusion. This comprehensive understanding enhances our ability to predict material degradation and informs the design of more reliable insulating materials for electrical applications.
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