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涂层可对纤维起到表面改性以及调节界面残余应力的作用,对宏观性能起着重要的影响。为准确预测多场环境下涂层-纤维增强磁电弹性(MEE)材料的有效属性和局部场分布,基于变分渐近理论建立均匀化细观力学模型。从非均匀连续介质的总电磁焓入手,利用材料细观尺度远小于宏观尺度的特征,将多物理场下细观力学建模转换为约束条件下总电磁焓的最小化问题。为分析工程应用中智能材料的涂层-纤维细观结构,采用有限元技术实现该模型的数值模拟。通过与有限元结果的对比分析表明:构建的模型可准确预测涂层-纤维增强磁电弹性材料的多物理场行为,不同厚度和刚度的涂层对应力集中和有效属性有较大的影响,同时揭示了许多独特的电-磁交互现象,为预测和优化涂层-纤维增强磁电弹性材料的性能提供有益的参考。
The coatings can act as a surface modification of the fibers and as a regulator of the residual stresses in the interface, with important implications for macro performance. In order to accurately predict the effective properties and local field distribution of the coating-fiber-reinforced magnetoelastic (MEE) material under multi-field conditions, a uniform meso-mechanics model was established based on the variational asymptotic theory. Starting from the total electromagnetic enthalpy of nonuniform continuous medium, the mesomechanical modeling under multiphysics is changed to the problem of minimizing the total enthalpy of electromagnetism under constrained conditions by using the characteristics that the mesoscopic scale is much smaller than the macroscale. In order to analyze the coating-fiber mesostructure of intelligent material in engineering application, the numerical simulation of the model was carried out by finite element method. The comparison with the finite element results shows that the model can accurately predict the multi-physics behavior of the coating-fiber reinforced magnetoelastic materials. The coatings with different thicknesses and stiffness have a great influence on the stress concentration and the effective properties. At the same time, many unique electro-magnetic interaction phenomena are revealed, which provide useful references for predicting and optimizing the properties of coating-fiber reinforced magnetoelastic materials.