Conference Agenda

The aim of this study is to develop an Integro-Differential approach, specifically the coupling of the Finite Method (FEM) with the Partial Element Equivalent Circuit (PEEC), capable of efficiently modeling a contactless electromagnetic induction heating system (CEIH) for performing localized heat treatment in structures with heterogeneous dimensions. Thermal calculations using conventional methods, such as the finite element method, require significant computation time due to the relative movement of the excitation coil along three spatial axes, its inclination, the heterogeneous dimensions of the treated workpiece, and the high precision required for the heat treatment. This paper investigates the computational process of induction heating and identifies the root cause of inefficiency in conventional electromagnetic-thermal methods. To address this, a direct FEM-PEEC coupling method is proposed to calculate the three-dimensional eddy current distribution by meshing only the active parts of the domain, excluding the air region. This approach enables the heat flux to directly serve as input for temperature field calculations. Furthermore, the paper introduces a framework for handling large-scale or multi-coil configurations. The results show that the proposed methodology significantly reduces execution time while maintaining high precision. Its effectiveness was validated by comparing the outcomes with those obtained using the numerical method (Flux 3D Software).

This paper presents the design and optimization of an iron-less spherical actuator capable of operating in an MRI (magnetic resonance imaging) environment. A coupled electromagnetic-thermal approach is adopted for the actuator design. To reduce optimization time, a 2D axisymmetric electromagnetic model is developed to predict the magnetic field generated by the actuator, while a 1D lumped parameter thermal model (LPTM) is employed to estimate the actuator’s heating. These models are validated using finite element analyses. MRI compatibility is ensured through the definition of both electromagnetic and thermal criteria

Determining the likelihood of the occurrence, growth and extinction of partial discharges between two conductors is a key point when designing an electrical devices such as transformers, electrical machines or busbars.

The continuity equations governing both time- and position-dependence of charged particle densities allows to build the most comprehensive model of partial discharge development in gas.

Known in the literature as fluid model, plasma model or even electrohydrodynamic model, it consists of set of drift-diffusion-reaction type equations strongly coupled to Poisson's equation that still remains challenging to solve by means of FEM due to numerical instability.

This paper deals with the modeling of spatio-temporal growth of partial discharge inside gas solved by means of FEM and stabilized by mean of a semi-lagrangian method.

This paper addresses the lumped parameter thermal network(LPTN) analysis method for temperature prediction of an interior permanent magnet synchronous motor (IPMSM). As the systems incorporating motors demand higher output power and torque, the need for motor downsizing continues to grow. However, the reduction in surface area for dissipating the losses generated within the motor has led to persistent thermal issues. Consequently, the importance of accurate temperature analysis for motors has become increasingly significant. In the proposed LPTN analysis, the accurate prediction of motor temperature heavily depends on the estimation of the convective heat transfer coefficient and thermal contact resistance coefficient. To address this, the paper presents a method that employs particle swarm optimization, a global optimization algorithm, to minimize the error between experimental results and analytical predictions.

The investigation of the fundamental properties of materials such as niobium or Nb3Sn by high-precision surface resistance measurements is a crucial aspect for the further development of superconducting radio-frequency (RF) technology. A calorimetric method using the dedicated quadrupole resonator (QPR) instrument is now one of the most accurate and reliable measurement methods for determining the high-frequency properties of superconducting materials with a resolution in the n$\Omega$ range. As with other resonators, the QPR deviates from its nominal design during operation for various reasons. These shape deviations can be static, e.g., due to manufacturing variations reflected in the manufacturing tolerances, or dynamic, e.g., because of physical phenomena such as Lorentz force (LF) detuning or microphonics. This, in turn, can significantly limit the measurement accuracy and general operation of a QPR. In our work, therefore, we developed an algorithm for multi-objective and multi-physics optimization that contributes to estimating shape deviations. The optimized QPR design is insensitive to geometrical uncertainties and compensates for the effects of LF detuning and high-frequency losses at the adapter flange.

We consider a 2d permanent magnet synchronous machine operating in a sequence of static operating points coming from a drive cycle. We aim to find a rotor design which maximizes the efficiency defined as the quotient of input and output energy considering Joule losses in the stator and eddy current losses in the permanent magnets. We additionally perform a thermal analysis in the rotor considering eddy current losses as heat source since the air gap acts as a thermal insulator and add a temperature constraint to avoid damage of the permanent magnets. To solve the resulting free form topology optimization problem we use a level set description of the design and the topological derivative as sensitivity information. We show the effect of this constraint at very high speeds which is a trend in recent machine development.

The design of electrical motors is becoming more and more complex as it must deal with multi-physical analysis and multi-objective optimization. Using a surrogate model can enhance the exploration capabilities of optimization. Global Sensitivity Analysis is a technique that highlights the most critical input parameters influencing the performance of a device. The analysis of a V-shaped Interior Permanent Magnet (IPM) motor structure is attempted. Due to the computational intensity of performance evaluation, a data-driven model with 8 parameters generating 2 outputs (torque and temperature) is created using an artificial neural network. Polynomial Chaos Expansion is then applied on the surrogate model to assess the performance variation. Some results on a motor configuration are presented, and their potential in the design process is outlined.

A novel 3-D multiphysics Finite Element Method (FEM) electromagnetic simulation model for railguns was developed, effectively handling moving components through a deformed geometry approach. Results show a 2.5% deviation in armature speed compared to those obtained with a quasistatic model. The presented model facilitates potential detailed railgun studies, such as thermal analysis.

Semiconductor topologies are fundamental building blocks of many conventional devices used in daily life, and accurate modeling and simulation tools of those topologies are thus of great relevance. To account for the nonclassical effects in the charge transport, the hydrodynamic model (HDM) and the energy-balance model (EBM) have been employed. In this work, we develop a numerical solver that incorporates HDM, using the discontinuous Galerkin finite element method. Besides the HDM solver, we make use of a commercial EBM implementation. The analysis has been performed for a n+nn+ junction, under the excitation of a voltage source. The obtained results have been compared with the ones of the classical drift-diffusion model. It is shown that the studied models may result in quite different predictions of the response of the investigated structure. We are currently developing an EBM solver, that will be validated with the above commercial tool. A detailed comparison of the HDM and EBM solvers will be performed.

The aim of this work is to develop a tool allowing to model a symmetrical collapse of a fluid in the presence of magnetic fields.

We use a Python-based numerical solver. We have implemented the fluid dynamics part and electromagnetics. This contribution will

focus on the coupling between both parts and in particular on solving the quasi-stationary Maxwell equations in the given framework.

The complexity of the system required us to check different numerical schemes, which will be compared. Moreover, throughout the

project, we have used several methods to reduce numerical errors. Their efficiency will be discussed.

The present work present a dynamic simulation of movement up to contact of an electromechanical armature by coupling between an analytical solution (AN) and finite elements (FE) one. The transient behavior of the electromechanical system study with small air-gap is performed when the coupling between mechanical and electromagnetic equations. The completely closed position at the air-gap is investigated with the movement simulation realized using coupled model. In this case only one mesh is needed for all displacements steps. The efficiency obtained when the air-gap vanishes is with a great interest. Results of 2D electromechanical system study using coupled FE-AN model are compared to finite elements calculation. The results seems to be acceptable and promising.