Jingyu Zheng , Xin Hu , Guangze Tang , Zhenhui Liu , She Li , Hanghang Yan , Xiangyang Cui
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Enabling accurate simulations of the nonlinear magnetic hysteresis behavior in ferromagnetic materials
In this work, a stable node - based smoothed finite - element method algorithm is developed to address the lower accurate issues in the simulation of the magnetic hysteresis behavior in ferromagnetic materials, in which the inverse vector Jiles - Atherton model is intimately coupled. The improvement of the accuracy for hysteresis issues is achieved by linking the stable node - based smoothed finite - element method in the framework of the Newton - Raphson iteration and the Jiles - Atherton model. The optimal relaxation coefficient method is introduced to address the natural strong nonlinearity of the Jiles - Atherton model and to ensure the convergence of the model. The algorithm is validated against the experimental results, and several examples are presented for simulations of the ferromagnetic hysteresis issues to illustrate both the accuracy and expandability in the practical scenarios of ferromagnetic materials.
期刊介绍:
Applied Mathematical Modelling focuses on research related to the mathematical modelling of engineering and environmental processes, manufacturing, and industrial systems. A significant emerging area of research activity involves multiphysics processes, and contributions in this area are particularly encouraged.
This influential publication covers a wide spectrum of subjects including heat transfer, fluid mechanics, CFD, and transport phenomena; solid mechanics and mechanics of metals; electromagnets and MHD; reliability modelling and system optimization; finite volume, finite element, and boundary element procedures; modelling of inventory, industrial, manufacturing and logistics systems for viable decision making; civil engineering systems and structures; mineral and energy resources; relevant software engineering issues associated with CAD and CAE; and materials and metallurgical engineering.
Applied Mathematical Modelling is primarily interested in papers developing increased insights into real-world problems through novel mathematical modelling, novel applications or a combination of these. Papers employing existing numerical techniques must demonstrate sufficient novelty in the solution of practical problems. Papers on fuzzy logic in decision-making or purely financial mathematics are normally not considered. Research on fractional differential equations, bifurcation, and numerical methods needs to include practical examples. Population dynamics must solve realistic scenarios. Papers in the area of logistics and business modelling should demonstrate meaningful managerial insight. Submissions with no real-world application will not be considered.