Conference Agenda

A motor model order reduction (MOR) based on the decomposition into stator and rotor domains requires a Fourier expansion of the gap field with a large of number harmonic components, which are handled by the multiport Cauer ladder network (CLN) method. This article proposes a block Arnoldi method to obtain a reduced representation of spatial harmonics. Efficient bases for reduced harmonic representation are generated based on the inductance matrices of CLNs of stator and rotor domains. Simulation results show that the proposed method gives an efficient and accurate MOR of the induction motor.

There are several ways of coupling field and circuit models but, in our opinion, the most natural one uses Electric Circuit Element (ECE) boundary conditions (BC) for the field problem formulation. In our previous work we have successfully implemented dual full-wave (FW) frequency-domain E- and H-based formulations with ECE BC in the finite element method. Our interest was only in high frequency (HF) applications, where FW regime is needed. The study of a simple coaxial cable test led us to conclude that while the FW-E formulation exhibits a robust behaviour in the whole freuquency range, the FW-H lacks accuracy at HF and presents stability issues at LF. In this contribution we study the accuracy and stability of the frequency-domain FW-E and H formulations with ECE BC, when used for a wide frequency range, from LF to HF. Remedies for the issues noticed for the H formulation are proposed.

In the extended paper, definitions for p-simplices of polynomial degree k are reviewed using Bernstein polynomial bases. Some topological and combinatorial properties, such as boundary operators and equivalence relations for quotients are revised. Some CAD-like functionalities, such as formulas for degree elevation, are reviewed. Taking the boundary or elevating the degree of an arbitrary simplex yields simplices of other types. If it is unknown beforehand which types of simplices are actually needed while running a software, there is a need for metaprogramming all the types and methods of arbitrary polynomial simplices. In the extended paper, we show how this can be done using Julia metaprogramming functionalities.

Decreasing Spherical Harmonic Functions (DSHF) provide a natural base for the magnetic scalar potential far enough from the sources. This multipolar expansion orders the magnetic field according to its decreasing rate and spatial periodicity. Unfortunately, this representation is not valid close to the sources. In this paper we will construct a basis for double-layer potential distributions on a surface, as close to the sources as needed, which is valid next to the sources while exhibiting a multipolar expansion property.

The Cauer ladder network (CLN) method is a model order reduction technique applicable to the analyses of quasi-static electromagnetic fields. In this study, we propose a novel error estimation method for the reduced-order models given by the CLN method, using the Henrici–Pflüger truncation error bounds for continued fractions. Numerical results for an analytical model of magnetic sheets show that the proposed method provides a good error estimation for the reduced-order model.

The Cauer ladder network (CLN) method enables to construct a reduced model of a Finite Element magneto-quasistatic problem based on an equivalent electrical circuit. A construction based on the static vector potential formulations A and T has been proposed in the literature in the case of Single Input Single Output. In the communication, we propose to extend this approach in the case of Multiple Inputs Multiple Outputs.

Accurate estimation of the unknown conductor's shape and location is crucial for fault detection or construction, such as locating the invisible power conductors in renovating old facilities to avoid causing damage to the power system. Inspired by local linearization, we proposed a method to realize the reconstruction of conductors based on space discretization and magnetic field observation. conductors are approximated by different combinations of line elements in series. An objective function is constructed to select reasonable elements by minimizing the deviation between the measured and predicted magnetic field values. Since the function is ill-conditioned and underdetermined, the Tikhonov regularization method is applied to get a unique solution. All the reconstruction results, including the conductor's location, length, and shape information, are visualized. Both simulations and experiments have assessed the genuineness of the suggested technique.

In this paper, the Finite Element (FE) model of the converter transformer under a polarity reversal transient electric field is reduced using the Proper Orthogonal Decomposition (POD) method, and the computational results of the POD Reduced Order Model (ROM) match with those of the original FE model. While polarity reversals occur, the nodal potential values obtained from the POD model have a significantly higher error than the FE model. The segmented definition time step method reduces the error peak and the model computation time, and the Arnoldi-Based Krylov method reduces the overall error value of the ROM, resulting higher accuracy and lower computation time.

Accelerator magnets made from blocks of permanent magnets in a zero-clearance configuration, are known as Halbach arrays.

The field quality in these magnets strongly depends on the magnetization direction of the permanent magnet blocks. The objective

of this work is to retrieve magnetization parameters from magnetic field measurements by means of a Bayesian approach. From

Helmholtz-coil measurements of the magnetized blocks, a prior distribution of the magnetization orientation is estimated. The posterior

distribution is derived using Bayes’ rule and samples are drawn with the Metropolis-Hastings algorithm. It is shown that the resulting

sample mean approximates the prescribed magnetization orientations (ground truth), and therefore magnetic measurement data can

be used to update the numerical model of the magnet as built.

The multiport Cauer ladder network (CLN) method is an efficient and accurate model order reduction (MOR) method for multi-input/multi-output systems. This manuscript discusses a theoretical aspect of port reduction of multiport CLN, where an intuitively derived method gives an inaccurate reduced representation. A recurrence formula is derived to generate an accurate reduced system.

The main aim of this work is to propose an accurate model for the simulation of losses and hysteresis characteristics under non-sinusoidal excitation over a wide range of frequencies and magnetic flux in Nanocrystal materials. A mathematical model based on the classical Bertotti loss separation model is proposed. Firstly, based on Amar arithmetic, the loss of sinusoidal excitation is calculated at a fixed frequency and voltage form coefficient is introduced to calculate the core losses under non-sinusoidal excitation. Secondly, the field separation expression of dynamic hysteresis model is derived subsequently according to the principle of field separation and loss separation. As the experimental results shows, the proposed model can accurately simulate the dynamic hysteresis and loss characteristics of nanocrystal under high-frequency non-sinusoidal excitation.