B. Butrylo, F. Musy, L. Nicolas, R. Perrussel, R. Scorretti and C. Vollaire
This paper presents new trends in parallel methods used to solve finite element matrix systems: standard iterative and direct solving methods first, and then domain decomposition…
Abstract
This paper presents new trends in parallel methods used to solve finite element matrix systems: standard iterative and direct solving methods first, and then domain decomposition methods. For example, the current status and properties of two prevailing programming environments (PVM and MPI) are finally given and compared when implemented together with a finite element time domain formulation.
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Maria Roberta Longhitano, Fabien Sixdenier, Riccardo Scorretti, Laurent Krähenbühl and Christophe Geuzaine
To understand the behavior of the magnetization processes in ferromagnetic materials in function of temperature, a temperature-dependent hysteresis model is necessary. This study…
Abstract
Purpose
To understand the behavior of the magnetization processes in ferromagnetic materials in function of temperature, a temperature-dependent hysteresis model is necessary. This study aims to investigate how temperature can be accounted for in the energy-based hysteresis model, via an appropriate parameter identification and interpolation procedure.
Design/methodology/approach
The hysteresis model used for simulating the material response is energy-consistent and relies on thermodynamic principles. The material parameters have been identified by unidirectional alternating measurements, and the model has been tested for both simple and complex excitation waveforms. Measurements and simulations have been performed on a soft ferrite toroidal sample characterized in a wide temperature range.
Findings
The analysis shows that the model is able to represent accurately arbitrary excitation waveforms in function of temperature. The identification method used to determine the model parameters has proven its robustness: starting from simple excitation waveforms, the complex ones can be simulated precisely.
Research limitations/implications
As parameters vary depending on temperature, a new parameter variation law in function of temperature has been proposed.
Practical implications
A complete static hysteresis model able to take the temperature into account is now available. The identification is quite simple and requires very few measurements at different temperatures.
Originality/value
The results suggest that it is possible to predict magnetization curves within the measured range, starting from a reduced set of measured data.
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R. Scorretti, R. Takahashi, L. Nicolas and N. Burais
The LF magnetic field (50 Hz‐100 kHz) generated in the air by electrical appliances is characterised using multipoles. The maximum likelihood estimation of an equivalent…
Abstract
The LF magnetic field (50 Hz‐100 kHz) generated in the air by electrical appliances is characterised using multipoles. The maximum likelihood estimation of an equivalent multipolar source is computed using a genetic algorithm. The choice of the position and the number of measurement points are discussed.
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Vesna Rubežić, Luka Lazović and Ana Jovanović
The purpose of this paper is to propose a chaotic optimization method for identifying the parameters of the Jiles–Atherton (J-A) hysteresis model.
Abstract
Purpose
The purpose of this paper is to propose a chaotic optimization method for identifying the parameters of the Jiles–Atherton (J-A) hysteresis model.
Design/methodology/approach
The J-A model has five parameters which are assigned with physical meaning and whose determination is demanding. To determine these parameters, the fitness function, which represents the difference between the measured and the modeled hysteresis loop, is formed. Optimal parameter values are the values that minimize the fitness function.
Findings
The parameters of J-A model for three magnetic materials are determined. The model with the optimal parameters is validated using measured data and comparison with particle swarm optimization algorithm, genetic algorithm, pattern search and simulated annealing algorithm. The results show that the proposed method provides better agreement between measured and modeled hysteresis loop than other methods used for comparison. The proposed method is also suitable for simultaneous optimization of multiple hysteresis loops.
Originality/value
Chaotic optimization method is implemented for the first time for J-A model parameter identification. Numerical comparisons with results obtained with other optimization algorithms demonstrate that this method is a suitable alternative in parameters identification of J-A hysteresis model. Furthermore, this method is easy to implement and set up.
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Yaqi Wang, Lin Li and Xiaojun Zhao
The purpose of this paper is to combine the Jiles-Atherton (J-A) hysteresis model with the field separation approach to realize the accurate simulation of dynamic magnetostrictive…
Abstract
Purpose
The purpose of this paper is to combine the Jiles-Atherton (J-A) hysteresis model with the field separation approach to realize the accurate simulation of dynamic magnetostrictive characteristics of silicon steel sheet.
Design/methodology/approach
First, the energy loss of silicon steel sheet is divided into hysteresis loss Why, classical eddy current loss Wed and anomalous loss Wan according to the statistical theory of losses. The Why is calculated by static J-A hysteresis model, Wed and Wan are calculated by the analytical formulae. Then, based on the field separation approach, the dynamic magnetic field is derived. Finally, a new dynamic magnetostrictive model is proposed by means of the quadratic domain rotation model.
Findings
Comparison of simulation and experimental results verifies that the proposed model has high accuracy and strong universality.
Originality/value
The proposed method improves the existing method’s problem of relying on too much experimental data, and the method ensures the calculation accuracy, parameter identification accuracy and engineering practicability. Consequently, the presented work greatly facilitates further explorations and studies on simulation of dynamic magnetostrictive characteristics of silicon steel sheet.
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Brijesh Upadhaya, Paavo Rasilo, Lauri Perkkiö, Paul Handgruber, Anouar Belahcen and Antero Arkkio
Improperly fitted parameters for the Jiles–Atherton (JA) hysteresis model can lead to non-physical hysteresis loops when ferromagnetic materials are simulated. This can be…
Abstract
Purpose
Improperly fitted parameters for the Jiles–Atherton (JA) hysteresis model can lead to non-physical hysteresis loops when ferromagnetic materials are simulated. This can be remedied by including a proper physical constraint in the parameter-fitting optimization algorithm. This paper aims to implement the constraint in the meta-heuristic simulated annealing (SA) optimization and Nelder–Mead simplex (NMS) algorithms to find JA model parameters that yield a physical hysteresis loop. The quasi-static B(H)-characteristics of a non-oriented (NO) silicon steel sheet are simulated, using existing measurements from a single sheet tester. Hysteresis loops received from the JA model under modified logistic function and piecewise cubic spline fitted to the average M(H) curve are compared against the measured minor and major hysteresis loops.
Design/methodology/approach
A physical constraint takes into account the anhysteretic susceptibility at the origin. This helps in the optimization decision-making, whether to accept or reject randomly generated parameters at a given iteration step. A combination of global and local heuristic optimization methods is used to determine the parameters of the JA hysteresis model. First, the SA method is applied and after that the NMS method is used in the process.
Findings
The implementation of a physical constraint improves the robustness of the parameter fitting and leads to more physical hysteresis loops. Modeling the anhysteretic magnetization by a spline fitted to the average of a measured major hysteresis loop provides a significantly better fit with the data than using analytical functions for the purpose. The results show that a modified logistic function can be considered a suitable anhysteretic (analytical) function for the NO silicon steel used in this paper. At high magnitude excitations, the average M(H) curve yields the proper fitting with the measured hysteresis loop. However, the parameters valid for the major hysteresis loop do not produce proper fitting for minor hysteresis loops.
Originality/value
The physical constraint is added in the SA and NMS optimization algorithms. The optimization algorithms are taken from the GNU Scientific Library, which is available from the GNU project. The methods described in this paper can be applied to estimate the physical parameters of the JA hysteresis model, particularly for the unidirectional alternating B(H) characteristics of NO silicon steel.
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Ramezan Ali Naghizadeh, Behrooz Vahidi and Seyed Hossein Hosseinian
The purpose of this paper is to propose an accurate model for simulation of inrush current in power transformers with taking into account the magnetic core structure and…
Abstract
Purpose
The purpose of this paper is to propose an accurate model for simulation of inrush current in power transformers with taking into account the magnetic core structure and hysteresis phenomenon. Determination of the required model parameters and generalization of the obtained parameters to be used in different conditions with acceptable accuracy is the secondary purpose of this work.
Design/methodology/approach
The duality transformation is used to construct the transformer model based on its topology. The inverse Jiles-Atherton hysteresis model is used to represent the magnetic core behavior. Measured inrush waveforms of a laboratory test power transformer are used to calculate a fitness function which is defined by comparing the measured and simulated currents. This fitness function is minimized by particle swarm optimization algorithm which calculates the optimal model parameters.
Findings
An analytical and simple approach is proposed to generalize the obtained parameters from one inrush current measurement for simulation of this phenomenon in different situations. The measurement results verify the accuracy of the proposed method. The developed model with the determined parameters can be used for accurate simulation of inrush current transient in power transformers.
Originality/value
A general and flexible topology-based model is developed in PSCAD/EMTDC software to represent the transformer behavior in inrush situation. The hysteresis model parameters which are obtained from one inrush current waveform are generalized using the structure parameters, switching angle, and residual flux for accurate simulation of this phenomenon in different conditions.
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Riccardo Scorretti, Ronan Perrussel, Laurent Morel, Noël Burais and Laurent Nicolas
The classical ϕ‐a formulations for numerical dosimetry of currents induced by extremely low frequency magnetic fields requires that the source field is provided through a vector…
Abstract
Purpose
The classical ϕ‐a formulations for numerical dosimetry of currents induced by extremely low frequency magnetic fields requires that the source field is provided through a vector potential. The purpose of this paper is to present a new formulation t‐b which directly takes the flux density as source term.
Design/methodology/approach
This formulation is implemented through finite element and validated by comparison with analytical solutions. The results obtained by both formulations are compared in the case of an anatomical computational phantom exposed to a vertical uniform field.
Findings
A good agreement between the t‐b formulation and both numerical and analytical computations was found.
Originality/value
This new formulation seems to be more accurate than the ϕ‐a formulation, and is more suited for situations where the magnetic field is known from experimental measurements, as there is no need for a magnetic vector potential.
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N. Siauve, R. Scorretti, N. Burais, L. Nicolas and A. Nicolas
The electromagnetic fields have a great influence on the behaviour of all the living systems. The as low as reasonably achievable (ALARA) principle imposes, in case of long…
Abstract
The electromagnetic fields have a great influence on the behaviour of all the living systems. The as low as reasonably achievable (ALARA) principle imposes, in case of long exposures to low (i.e. power systems) or high frequency (i.e. microwave systems or cell phones) fields, some limitations to the radiated fields by the industrial equipment. On the other hand, some benefits can be taken from the effects of the electromagnetic fields on the living being: the hyperthermal technique is well known for the treatment of the cancer. Either we want to be protected from the fields, or we want to take benefit of the positive effects of these fields, all the effects thermal as well as genetic have to be well known. Like in any industrial application, the electromagnetic field computation allows a better knowledge of the phenomena, and an optimised design. Hence, there is a very important challenge for the techniques of computation of electromagnetic fields. The major difficulties that appear are: (1) related to the material properties – the “material” (the human body) has very unusual properties (magnetic permeability, electric permittivity, electric conductivity), these properties are not well known and depend on the activity of the person, and this material is an active material at the cell scale; (2) related to the coupling phenomena – the problem is actually a coupled problem: the thermal effect is one of the major effects and it is affected by the blood circulation; (3) related to the geometry – the geometry is complex and one has to take into account the environment. The problems that we have to face with are – the identification of the properties of the “material”, the coupled problem solution and the representation of the simulated phenomena.
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Luca Di Rienzo and Jens Haueisen
To define a methodology for comparing sensor arrays for solving magnetostatic linear inverse problems.
Abstract
Purpose
To define a methodology for comparing sensor arrays for solving magnetostatic linear inverse problems.
Design/methodology/approach
A singular value decomposition related projection method is used for comparing sensor arrays and we applied it to a biomagnetic inverse problem, as an example. Furthermore, a theoretical reference sensor system is introduced and used as a benchmark for the analysed sensor arrays.
Findings
The method has turned out to be effective in comparing three different theoretical sensor arrays, showing the superiority of the two arrays constituted by three‐axial sensors.
Research limitations/implications
The method has been applied only to the case of over‐determined problems. The underdetermined case will be considered in future work.
Practical implications
From the applicative point of view, the illustrated methodology is useful when one has to choose between existing sensor arrays or in the design phase of a new sensor array.
Originality/value
A new methodology is proposed for comparing sensor arrays. The advantage of the methodology are to take into account the regularization in the solution of the inverse problem and to be general, not depending on a particular source configuration.