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The purpose of this paper is to provide a model for simulating contamination by ferromagnetic particles in sensors that use permanent magnets. This topic is especially important for automotive applications, where magnetic sensors are extensively used and where metallic particles are present, particularly because of friction between mechanical parts. The aim of the model is to predict the particle accumulation and its effect on the sensor performance.

Magnetostatic moment method is used to calculate particles' magnetization and magnetic field. Magnetic saturation is included and Newton–Raphson method is used to solve the non-linear system. Magnetic force on particles is calculated as a gradient of energy. Dynamic simulation provides the positions of agglomerated particles.

A simulation of magnetic park lock sensor shows a significant impact of ferromagnetic particles on sensor's accuracy. Moreover, gains on computational time because of model optimizations are reported.

Only magnetic force and gravity are taken into account for particle dynamics. Mechanical forces such as friction and particle interactions might be considered in future works.

This paper provides the possibility to evaluate and improve magnetic sensor design with respect to particles contamination.

The paper presents a novel simulation tool developed to answer the growing need for reliable and fast prediction of magnetic position sensors’ degradation in the presence of metallic particles.

The aim of this paper is to model time‐harmonic problems in unbounded domains with coils of complex geometry and ferromagnetic materials.

The approach takes the form of a coupling between two integrals methods: the magnetic moment method (MMM) and the partial element equivalent circuit (PEEC) method. The modeling of conductor system is achieved thanks to PEEC method while the MMM method is considered for the magnetic material.

The paper shows how to use the MMM/PEEC coupled method to model a problem comprising conductors and ferromagnetic materials and compare its results with the FEM and the FEM/PEEC coupling.

The two methods PEEC and MMM are well‐known. The innovation here is coupling these methods in order to take advantages from both methods. Moreover, the performances of this coupling are studied in comparison with others (FEM, FEM/PEEC coupling).

This paper aims to present a modeling approach of diamagnetic microsystems for design and optimization requirements. It is demonstrated on the stabilisation optimization of a diamagnetic levitation system for biomedical applications.

Surface approach was used to compute analytically the magnetic field induction. This modeling is depending on system to design (approximation, equation simplifications due to specific geometries) coupled with a design framework which is based on symbolic equation derivation and SQP constrained optimization algorithm.

Optimally stabilized magnetic levitating systems, for a pyrolitic graphite micro plate and for a latex bead.

The analytical or semi‐analytical modeling of magnetic field induction and forces produced by complex geometries is sometimes either hard to establish or not adequate to perform a fast optimization, due to heavy numerical parts implemented into the device modeling.

Implications are of two kinds. First are results of the magnetic levitating system which can improve lab on a chip for biomedical applications. Second is design framework improvement with diamagnetic modeling capabilities.

Stability optimization of diamagnetic levitation system, based on an original approach of modeling and sizing with dedicated tools.

This paper aims to present an adaptive method based on finite element analysis to calculate iron losses in switched reluctance motors (SRMs). Calculation of iron losses by analytical formulas has limited accuracy. On the other hand, its estimation in rotating electrical machines through fully dynamic simulations with a fine time-step is time-consuming. However, in the initial design process, a quick and sufficiently accurate method, i.e. a value close to that of iron losses, is always welcome. The method presented in this paper is a semi-analytical approach. The main problem is that iron losses depend on d B/d t. Therefore, the accuracy of the calculation of iron losses depends on the accuracy of the calculation of the first derivative of the flux density waveform. When adopting a magnetostatic model to estimate the iron losses, an important question arises: by how many magnetostatic simulations can the iron losses be estimated within the desired accuracy? In the proposed algorithm, the aim is not to accurately calculate the value of iron losses in SRMs. The objective is to find a numerical error criterion to calculate iron losses in SRMs with a minimum number of magnetostatic simulations.

A finite element solver is developed by authors in MATLAB to solve the 2 D nonlinear magnetostatic problem using the Newton–Raphson method. A parametric program is developed to create geometry and mesh. The proposed method is implemented in MATLAB using the developed solver. Counterpart simulations are done in the ANSYS Maxwell software to validate the accuracy of the results generated by the developed solver.

The performance of the proposed method is studied on a 12/8 (500 W) SRM. Three scenarios are studied. The first one is the calculation of iron losses by uniform refinement, and the second one is by adaptive refinement, and the last one is by adaptive refinement started by particular initial points (switching points). According to the results, the proposed method substantially reduces the number of magnetostatic simulations without sacrificing accuracy.

The main novelty of this paper is introducing an error criterion to find the minimum number of magnetostatic simulations that are needed to calculate iron losses with the desired accuracy.

Gives introductory remarks about chapter 1 of this group of 31 papers, from ISEF 1999 Proceedings, in the methodologies for field analysis, in the electromagnetic community. Observes that computer package implementation theory contributes to clarification. Discusses the areas covered by some of the papers ‐ such as artificial intelligence using fuzzy logic. Includes applications such as permanent magnets and looks at eddy current problems. States the finite element method is currently the most popular method used for field computation. Closes by pointing out the amalgam of topics.

Confronting the unveiled sophisticated structural and physical characteristics of permanent magnets, notably the samarium–cobalt (Sm-Co) alloy, This work aims to introduce a simulation scheme that can link physics-based micromagnetics on the nanostructures and magnetostatic homogenization on the mesoscale polycrystalline structures.

The simulation scheme is arranged in a multiscale fashion. The magnetization behaviors on the nanostructures examined with various orientations are surrogated as the micromagnetic-informed hysterons. The hysteresis behavior of the mesoscale polycrystalline structures with micromagnetic-informed hysterons is then evaluated by computational magnetostatic homogenization.

The micromagnetic-informed hysterons can emulate the magnetization reversal of the parameterized Sm-Co nanostructures as the local hysteresis behavior on the mesostructures. The simulation results of the mesoscale polycrystal demonstrate that the demagnetization process starts from the grain with the largest orientation angle (a) and then propagates to the surrounding grains.

The presented scheme depicts the demand for integrating data-driven methods, as the parameters of the surrogate hysteron intrinsically depend on the nanostructure and its orientation. Further hysteron parameters that help the surrogate hysteron emulate the micromagnetic-simulated magnetization reversal should be examined.

This work provides a novel multiscale scheme for simulating the polycrystalline permanent magnets’ hysteresis while recapitulating the nanoscale mechanisms, such as the nucleation of domains, and domain wall migration and pinning. This scheme can be further extended to simulate the part-level hysteresis considering the mesoscale features.

Discusses the 27 papers in ISEF 1999 Proceedings on the subject of electromagnetisms. States the groups of papers cover such subjects within the discipline as: induction machines; reluctance motors; PM motors; transformers and reactors; and special problems and applications. Debates all of these in great detail and itemizes each with greater in‐depth discussion of the various technical applications and areas. Concludes that the recommendations made should be adhered to.

The purpose of this paper is to solve generic magnetostatic problems by BEM, by studying how to use a boundary integral equation (BIE) with the double layer charge as unknown derived from the scalar potential.

Since the double layer charge produces only the potential gap without disturbing the normal magnetic flux density, the field is accurately formulated even by one BIE with one unknown. Once the double layer charge is determined, Biot‐Savart's law gives easily the magnetic flux density.

The BIE using double layer charge is capable of treating robustly geometrical singularities at edges and corners. It is also capable of solving the problems with extremely high magnetic permeability.

The proposed BIE contains only the double layer charge while the conventional equations derived from the scalar potential contain the single and double layer charges as unknowns. In the multiply connected problems, the excitation potential in the material is derived from the magnetomotive force to represent the circulating fields due to multiply connected exciting currents.

The use of gradient-based methods in finite element schemes can be prevented by undefined derivatives, which are encountered when modeling hysteresis in constitutive material laws. This paper aims to present a method to deal with this problem.

Non-smooth Newton methods provide a generalized framework for the treatment of minimization problems with undefined derivatives. Within this paper, a magnetostatic finite element formulation that includes hysteresis is presented. The non-linear equations are solved using a non-smooth Newton method.

The non-smooth Newton method shows promising convergence behavior when applied to a model problem. The numbers of iterations for magnetization curves with and without hysteresis are within the same range.

Mathematical tools like Clarke's generalized Jacobian are applied to magnetostatic field problems with hysteresis. The relation between the non-smooth Newton method and other methods for solving non-linear systems with hysteresis like the M(B)-iteration is established.

The purpose of this paper is to develop an original approach to simulate the reading process for multitrack shielded magneto‐resistive reading (MR) heads.

The shields and the media are of micron size while the sensor has sizes comparable with the characteristic length scales of the magnetic materials which are of the order of nanometer. Because of this large difference of scales between the different parts of the head, the macroscopic shields and the media are described by a boundary element method (BEM) approach, while the sensor is treated by micromagnetism in order to reconstruct the response of shielded multitrack MR head. To select the most favorable approach, several releases were implemented and compared. A technique based on a full‐coupling procedure was found to be the most general but too expensive in time. Appling the perfect‐imaging method directly into the micromagnetic simulator, the authors succeed in accelerating the computation without loosing accuracy.

Solving by BEM the Poisson equation for the scalar magnetic potential only the surfaces interfaces are discretised, saving thus computation time and memory resources. In addition, for multi‐tracks data pattern, the magnetic scalar potential may be estimated with a good approximation by considering a periodic system along the crosstrack direction. By applying the Fourier series expansion for the magnetic charges distribution along the crosstrack direction, the initial BEM 3D problem can be treated as a bi‐dimensional one.

This macroscopic‐microscopic coupling technique allows a full description of the behaviour of the magnetic sensor in its environment, being a useful tool for the design and the optimisation of the multitrack MR reading heads.