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May 9, 2026Applied Sciences0 citationsOpen Access

Determination of Material Permeability and Conductivity Based on Electrical Measurements Using FEM and Optimization Methods

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JFJernej FrangežMJMarko Jesenik

Key Points

  • This research aims to determine the permeability and conductivity of magnetic steel materials through electrical measurements using FEM and optimization methods.
  • Used a finite element method (FEM) for analysis.
  • Compared three models: a whole 3D model, a 1/8 symmetrical 3D model, and a 2D axisymmetric model.
  • Employed a skin-depth mesh to enhance accuracy of results.
  • The Finite Element Model demonstrated strong model conditioning validated against reference data.
  • The results from the measurements showed significant accuracy in determining both permeability and conductivity.

Abstract

Every day, more and more electrical devices are produced, such as electric motors and actuators, which tend to operate according to their intended purpose with minimal maintenance. This is possible if they are assembled with the right input material, which needs to be tested at various stages of production. The presented approach proposes using the existing measuring equipment, combined with the finite element method and an optimization method, to determine the relative permeability and conductivity—in a contactless manner—from electrical measurements for magnetic steel materials. A comparison was made among three models: a whole 3D model, a 1/8 symmetrical 3D model, and a 2D axisymmetric model. During the research, the importance of using a skin-depth mesh was emphasized to obtain the correct results. A novel approach is used to analyze and optimize both the permeability and conductivity using a single model, optimization, and measurements. The optimized Finite Element Model shows very strong model conditioning, as tested with reference data, yielding great results with the measured data.

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Cite This Study

Frangež et al. (2026) studied this question.

synapsesocial.com/papers/69fecfafb9154b0b82876b19https://doi.org/10.3390/app16104580
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