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The aim of the International Journal of Applied Electromagnetics and Mechanics is to contribute to intersciences coupling applied electromagnetics, mechanics and materials. The journal also intends to stimulate the further development of current technology in industry. The main subjects covered by the journal are:
- Physics and mechanics of electromagnetic materials and devices
- Computational electromagnetic in materials and devices
- Applications of electromagnetic fields and forces
The three interrelated key subjects - materials, electromagnetics and mechanics - include the following aspects: control, micromachines, intelligent structure, inverse problem, eddy current analysis, electromagnetic NDE, magnetic materials, magnetoelastic effects in materials, bioelectromagnetics, magnetosolid mechanics, magnetic levitations, applied physics of superconductors, superconducting magnet technology, superconducting propulsion system, nuclear fusion reactor components and wave propagation in electromagnetic fields.
Authors: Barba, Paolo Di | Mognaschi, Maria Evelina | Wiak, Sławomir
Article Type: Editorial
DOI: 10.3233/JAE-229002
Citation: International Journal of Applied Electromagnetics and Mechanics, vol. 69, no. 2, pp. 125-126, 2022
Authors: Di Barba, Paolo | Mognaschi, Maria Evelina | Wiak, Slawomir
Article Type: Research Article
Abstract: In computational electromagnetism there are manyfold advantages when using machine learning methods, because no mathematical formulation is required to solve the direct problem for given input geometry. Moreover, thanks to the inherent bidirectionality of a convolutional neural network, it can be trained to identify the geometry giving rise to the prescribed output field. All this puts the ground for the neural meta-modeling of fields, in spite of different levels of cost and accuracy. In the paper it is shown how CNNs can be trained to solve problems of optimal shape synthesis, with training data sets based on finite-element analyses of …electric and magnetic fields. In particular, a concept of multi-fidelity model makes it possible to control both prediction accuracy and computational cost. The shape design of a MEMS design and the TEAM workshop problem 35 are considered as the case studies. Show more
Keywords: Surrogate models, convolutional neural network, field analysis and synthesis
DOI: 10.3233/JAE-210222
Citation: International Journal of Applied Electromagnetics and Mechanics, vol. 69, no. 2, pp. 127-137, 2022
Authors: Jansen, Kevin | Kern, Alexander | Mülder, Christoph | Hameyer, Kay
Article Type: Research Article
Abstract: The simulation of electrical machines at the first design stage requires efficient methods to characterize among other properties its vibrational behavior. Particularly when considering both designed and parasitic geometrical modifications, magnetic circuit calculations of large-dimensioned machines by finite-element methods (FEM) are cumbersome. Semi-analytical approaches by means of conformal mapping are therefore useful to estimate the impact of several effects, such as asymmetric stator laminations, rotor pole shapes and air gap imperfections. No-load operation is studied and the presented approach is validated by FEM simulations. The aim of this work is to study force excitations by the magnetic air gap field …in salient multi-pole synchronous generators deviating from ideal and symmetrical geometrical conditions by using conformal maps. Show more
Keywords: Parasitic magnetic forces, conformal mapping, electrical machines, large drives
DOI: 10.3233/JAE-210183
Citation: International Journal of Applied Electromagnetics and Mechanics, vol. 69, no. 2, pp. 139-147, 2022
Authors: Cvetkovski, Goga | Petkovska, Lidija
Article Type: Research Article
Abstract: This paper presents a novel approach to the efficiency improvement of permanent magnet synchronous motor using gravitational search algorithm as an optimization tool. The gravitational search algorithm (GSA) is a recently developed meta-heuristic optimization algorithm, which so far has proven to be quite suitable for solving power engineering optimization problems. The aim of this research work is to implement this novel optimization algorithm for the efficiency improvement of permanent magnet synchronous motor, where the objective function in the optimization process is the efficiency of the investigated motor. Comparative analysis of the initial and a number of optimized solutions of the …motor model is performed. Show more
Keywords: Permanent magnet synchronous motor, efficiency, optimization, optimal design, gravitational search algorithm
DOI: 10.3233/JAE-210178
Citation: International Journal of Applied Electromagnetics and Mechanics, vol. 69, no. 2, pp. 149-167, 2022
Authors: Kłosowski, Grzegorz | Rymarczyk, Tomasz
Article Type: Research Article
Abstract: This paper refers to a new resilient cyber-physical machine learning-based system that enables the generation of high-resolution tomographic images. The research object was a model of a tank filled with tap water. Using electrical impedance tomography (EIT) with 16 electrodes, the possibility of identifying inclusions inside the reservoir was investigated. A two-stage hybrid approach was proposed. In the first stage, three independent models were trained for the Elastic Net, Artificial Neural Networks (ANN) and Support Vector Machine (SVM) methods. In the second stage, a k-Nearest Neighbors (kNN) classification model was trained, that optimizes tomographic reconstructions by selecting the best method …for each pixel, taking into account the specificity of a given measurement vector. Research has shown that applying the new concept results in a higher reconstruction quality than other methods used singly. It should be emphasized that our research is not intended to develop a new homogenous machine learning method. Instead, the goal is to invent an innovative, original, and flexible way to simultaneously use multiple machine learning methods for image optimization in industrial electrical impedance tomography. Show more
Keywords: Machine learning, ensemble learning, electrical tomography, process tomography, hybrid tomography
DOI: 10.3233/JAE-210160
Citation: International Journal of Applied Electromagnetics and Mechanics, vol. 69, no. 2, pp. 169-178, 2022
Authors: Paplicki, Piotr | Prajzendanc, Pawel | Wardach, Marcin | Palka, Ryszard | Cierzniewski, Kamil | Pstrokonski, Rafal
Article Type: Research Article
Abstract: The paper presents 3D-FEA results of electromagnetic torque characteristics of a Field Control Axial Flux Permanent Magnet Machine (FCAFPMM) obtained for different pole shapes. The influence of the angular span of iron and permanent magnet poles on the cogging torque performance has been analysed at different excitations of an additional stator winding.
Keywords: Axial flux, hybrid machine, permanent magnet, cogging torque, torque ripple
DOI: 10.3233/JAE-210182
Citation: International Journal of Applied Electromagnetics and Mechanics, vol. 69, no. 2, pp. 179-188, 2022
Authors: Di Barba, Paolo | Mognaschi, Maria Evelina | Petkovska, Lidija | Cvetkovski, Goga
Article Type: Research Article
Abstract: In the paper an original approach to efficiency map optimal synthesis is presented. A permanent magnet motor, working as controlled AC motor of synchronous type (PMSM), is selected as a case study. The first target of this research is to derive a lumped-parameter model of the motor (low-fidelity model), validated by magnetic field analysis (high-fidelity model). In turn, the end target is these two models application in a cost-effective optimisation procedures, where the goal is to identify the motor geometry maximizing the map area which is encompassed by a prescribed value for the motor efficiency.
Keywords: Permanent magnet synchronous motor (PMSM), efficiency map, shape optimisation, lumped-parameter model, magnetic field analysis
DOI: 10.3233/JAE-210201
Citation: International Journal of Applied Electromagnetics and Mechanics, vol. 69, no. 2, pp. 189-199, 2022
Authors: Kurosawa, Yuji | Enomoto, Yuji | Soda, Naoya
Article Type: Research Article
Abstract: Vector magnetic properties of various electrical steel sheets have been investigated by using a vector magnetic property measurement apparatus to select a magnetic material suitable as a motor core material. However, a magnetic material with a higher saturation magnetization than an electrical steel sheet is useful for increasing torque of a motor. Therefore, a permendur with higher saturation magnetization than an electrical steel sheet is selected as a measurement sample. It is known that a permendur does not have magnetic anisotropy. In this paper, vector magnetic properties of two kinds of permendurs made by VACUUMSCHMELZE (VAC) and Hitachi Metals are …measured. Moreover, maximum magnetic field intensities and core losses of two kinds of permendurs to an inclination angle of magnetic flux density vector locus from rolling direction are evaluated for investigation of those magnetic anisotropies. As a result, differences of vector magnetic properties of two kinds of permendurs are revealed. Show more
Keywords: Magnetic anisotropy, permendur, vector magnetic properties
DOI: 10.3233/JAE-210181
Citation: International Journal of Applied Electromagnetics and Mechanics, vol. 69, no. 2, pp. 201-210, 2022
Authors: Kłosowski, Grzegorz | Rymarczyk, Tomasz
Article Type: Research Article
Abstract: The research aimed to develop an optimal way of using known machine learning techniques in electrical impedance tomography (EIT) of flood embankments. The innovative approach is based on the smart use of many machine learning techniques to allow the optimal selection of one of these techniques for each pixel of the tomographic image. An additional advantage of the presented concept is that selecting the optimal method for each pixel depends on the measurement set of a given case. This fact makes the method flexible and enables the automation of dyke monitoring using cyber-physical systems. Several machine learning methods were used …during the research, including Elastic Net, Support Vector Machine, and Artificial Neural Networks. The comparison of the new concept with popular methods showed that thanks to pixel-oriented ensemble learning, the reconstructions obtained with the new approach are much better than those obtained with typical machine learning methods. Show more
Keywords: Machine learning, ensemble learning, electrical tomography, levees monitoring, cyber-physical systems
DOI: 10.3233/JAE-210187
Citation: International Journal of Applied Electromagnetics and Mechanics, vol. 69, no. 2, pp. 211-220, 2022
Authors: Rebhaoui, Abderrahmane | Randi, Sid Ali | Demian, Cristian | Lecointe, Jean-Philippe
Article Type: Research Article
Abstract: Grain Oriented Electrical Steel (GOES) have better performance in terms of permeability and iron losses compared to conventional Fe-Si 3% Non-Oriented Grains Electrical Steel (NOES), particularly when it is magnetized in the rolling direction. This paper presents a concentrated winding radial flux permanent magnets synchronous machine (PMSM) equipped with teeth made of GOES sheet. The goal is to assess the suitability of the use of GOES sheets to improve the efficiency of electric motors. This work is based on the comparison of the performances (Joule losses, iron losses, losses in the permanent magnets and efficiency) of two iso-geometric motors: a …reference motor made of NOES sheets and a motor with GOES sheet teeth, at iso-torque and over the operating range (at constant torque and flux weakening). The comparison is made using a finite element software application considering the magnetic anisotropy of the GOES sheets. Show more
Keywords: PMSM, magnetic circuit, anisotropy, grain oriented electric steel, motor performances
DOI: 10.3233/JAE-210186
Citation: International Journal of Applied Electromagnetics and Mechanics, vol. 69, no. 2, pp. 221-232, 2022
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