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To apply two different integral formulations of full‐Maxwell's equations to the numerical study of interconnects in a low‐frequency range and compare the results.

The first approach consists of a surface formulation of the full‐Maxwell's equations in terms of potentials, giving rise to a surface electric field integral equation. The equation, given in a weak form, is solved by using a finite element technique. The solenoidal and non‐solenoidal components of the electric current density are separated using the null‐pinv decomposition to avoid the low‐frequency breakdown. The second model is an extension of partial element equivalent circuit technique to unstructured meshes allowing the use of triangular meshes. Two systems of meshes tied by duality relations are defined on multiconductor systems. The key point in the definition of the equivalent network is to associate the pair primal edge/dual face to a circuit branch. Solution of the resulting electrical network is performed by a modified nodal analysis method and regularization of the outcoming matrix is accomplished by standard techniques based on the addition of suitable resistors.

Both the formulation have a regular behaviour at very low frequency. This is automatically achieved in the first approach by using the null‐pinv decomposition.

Surface sources of fields.

Two different integral formulations of full‐Maxwell's equations for the numerical study of interconnects are compared in terms of low‐frequency behaviour.

The purpose of this paper is to present an electro‐thermo‐structural analysis based on the cell method (CM).

CM is useful for solving coupled problems when the same geometrical discretization can be adopted for different phenomena. In this case, the same geometrical structures and operators can be used, leading to a simplification of the numerical model.

In order to asses the performance of the proposed coupling scheme, results have been compared with values measured on a carbon‐fiber specimen heated by an electric current and with an applied the mechanical load.

A new dynamic coupling scheme based on the CM has been proposed and assessed with respect to measurements. A good agreement between model results and measurements has been shown, at least until second order effects appears, like the breaking of some fibers of the specimen or high‐temperature effects on epoxy resin.

The paper aims to describe the coupling of magnetostatic finite formulation of electromagnetic field with two integral methods.

The first hybrid scheme is based on Green's function applied to magnetization source while the other one is based on a magnetic scalar potential boundary element method. A comparison of the two techniques is performed on a benchmark case with analytical solution, on a 2D multiply‐connected problem and on an industrial case where measurements are available.

The proposed hybrid approaches have proved to be effective techniques to solve open boundary non‐linear magnetostatic problems. Similar convergence speed with respect to the number of unknowns is found for both schemes

The paper shows the effectiveness of hybrid schemes applied to the finite formulation, assessing their performances on various test cases.

The aim of this paper is to highlight the educational value of algebraic numerical methods with respect to traditional numerical techniques based on differential formulation.

Algebraic formulations of electromagnetic fields are gaining a new interest in the research community. One common characteristic of these methods is that they impose field equations, for instance charge or mass conservation, directly in algebraic form as a sum of partial contributes, without using differential operators like the divergence one. This feature leads directly to a system of linear equations without requiring any intermediate differential formulation as in finite element method. In addition, these systems of linear equations can be efficiently expressed as a product of matrices related to problem topology and material characteristics.

Owing to these features, a MATLAB implementation of these theoretical frameworks is particularly efficient and simple and can be used by electrical engineering students which, even if with a basic mathematical background, have a good practice with network theory and its computer implementation. Following this way of thinking, a MATLAB based environment has been created and here it is presented and discussed.

The implementation of the algebraic formulation can be done by using very basic mathematical tools, therefore the algebraic method becomes also a good way to introduce the numerical field analysis to undergraduate students.

The purpose of this paper is to present an approach to design passive loop systems in order to reach good performances.

The optimization has been performed by means of the MATLAB optimization toolbox “Gatool” which solves the optimization problems with a genetic algorithm.

Several configurations have been analyzed by varying the number of loops from 2 to 15, whose geometry has been chosen by the genetic algorithm. Considering a five loops configuration, along the reference path it is possible to obtain a shielding factor almost constant and equal to 3.5.

The optimized configurations have been compared with a practical employed layout composed of 17 closed loops placed above and around the junction zone. The shielding factors obtained by the six loops configuration are comparable with the ones of the practical layout.

Supplying remote wireless sensors is not an easy task if the site where the device is located is not easily accessible. In order to obtain direct measurements of the road-vehicle interactions, sensors must be placed inside the tyre environment thus a power supply must be available for their working there without any wire connection with the car main power. The paper aims to discuss these issues.

An electro-mechanical energy harvester has thus been developed for supplying an automotive wireless sensor of pressure, temperature and acceleration to be placed on the inner line of a tyre. The primary energy source is the vibrations or variable accelerations imposed to the device and induced in the tyre by the wheeling.

The harvester has been designed by means of a multi-physics optimisation based on an integrated electromagnetic-mechanical circuit simulator. Thus an automated optimisation of the device with respect to volume constraints, magnets dimensions, induction coils placement and size have been performed to increase the average power extracted from the device at different wheeling speeds.

The use of the multi-physics environment together with automated optimisation technique has been tested for the first time on the electromagnetic harvester structure.

The purpose of this study is to investigate and compare the ability of a new optimization technique based on the emulation of the immune system to detect the global maximum with multimodal functions and to test the capability of exploring the parameter space with respect to clustering enhanced Genetic Algorithms (GA).

Both algorithms have been tested on analytical test functions and on numerical functions of applicative interest. A set of performance criteria has been defined in order to numerically compare the performances of both optimization strategies.

Results show the great ability of Artificial Immune Systems (AIS) in thoroughly exploring the space of variables. On the other side, GA are faster to converge to the global optimum, but selection pressure can reduce the number of detected local optima.

This work is an attempt to assess the performances of a relatively new optimization algorithm based on AIS and to find its behavior on multimodal test functions, using GAs as reference optimization technique.