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The electromagnetic modeling of inductively coupled, resonant wireless power transfer (WPT) is dealt with. This paper aims to present a numerically efficient simulation method.

Recently, integral equation formulations have been proposed, using piecewise constant basis functions for the series expansion of the current along the coil wire. In the present work, this scheme is improved by introducing global basis functions.

The use of global basis functions provides a stronger numerical stability and a better control over the convergence of the simulation; moreover, the associated computational cost is lower than for the previous schemes. These advantages are demonstrated in numerical examples, with special attention to the achievable efficiency of the power transfer.

The method can be efficiently used, e.g., in the optimal design of resonant WPT systems.

The presented computation scheme is original in the sense that global series expansion has not been previously applied to the numerical simulation of resonant WPT.

This study aims to model and investigate low-loss wave-propagation modes across random media. The objective is to achieve better channel properties for applying radio links through random vegetation (e.g. forest) using a beamforming approach. Thus, obtaining the link between the statistical parameters of the media and the channel properties.

A beamforming approach is used to obtain low-loss propagation across random media constructed of long cylinders, i.e. a simplified two dimensional (2D) model of agroforests. The statistical properties of the eigenmode radio wave propagation are studied following a Monte Carlo method. An error quantity is defined to represent the robustness of an eigenmode, and it is shown that it follows a known Lognormal statistical distribution, thereby providing a base for further statistical investigations.

In this study, it is shown that radio wave propagation eigenmodes exist based on a mathematical model. The algorithm presented can find such modes of propagation that are less affected by the statistical variation of the media than the regular beams used in radio wave communication techniques. It is illustrated that a sufficiently chosen eigenmode waveform is not significantly perturbed by the natural variation of the tree trunk diameters.

As a new approach to obtain low-loss propagation in random media at microwave frequencies, the presented mathematical model can calculate scattering-free wave-propagation eigenmodes. A robustness quantity is defined for a specific eigenmode, considering a 2D simplified statistical forest example. This new robustness quantity is useful for performing computationally low-cost optimization problems to find eigenmodes for more complex vegetation models.

The purpose of this paper is the development of an analytic computational model for electromagnetic (EM) wave scattering from spherical objects. The main application field is the modeling of electrically large objects, where the standard numerical techniques require huge computational resources. An example is full-wave modeling of the human head in the millimeter-wave regime. Hence, an approximate model or analytical approach is used.

The Mie–Debye theorem is used for calculating the EM scattering from a layered dielectric sphere. The evaluation of the analytical expressions involved in the infinite sum has several numerical instabilities, which makes the precise calculation a challenge. The model is validated through an application example with comparing results to numerical calculations (finite element method). The human head model is used with the approximation of a two-layer sphere, where the brain tissues and the cranial bones are represented by homogeneous materials.

A significant improvement is introduced for the stable calculation of the Mie coefficients of a core–shell stratified sphere illuminated by a linearly polarized EM plane wave. Using this technique, a semi-analytical expression is derived for the power loss in the sphere resulting in quick and accurate calculations.

Two methods are introduced in this work with the main objective of estimating the final precision of the results. This is an important aspect for potentially unstable calculations, and the existing implementations have not included this feature so far.

To develop new and existing coupled thermal and mechanical models of electromagnetic solids for the simulation of coupled field problems based on a consistent theoretical and computational framework.

The finite element computational models we describe involve the combination of classical electrodynamics, continuum mechanics, and thermodynamics. In order to create consistent coupled models, we employ the fundamental principles of thermodynamics as a common framework.

Our procedure requires the necessary thermodynamical considerations for building consistent multiphysics models and develops some novel implementation issues that are important from the designers' point of view. Additionally, efficient numerical algorithms for solving the arising static and dynamic nonlinearities are discussed.

The paper targets the simulation of coupled problems in macroscopic electromagnetic continua.

The application areas of the coupled field models are identified and illustrated by the solution of complex industrial problems.

We introduce new computational models and techniques for the solution of some coupled field problems in electromagnetic solids. While some elements of these computational models and techniques have been used for decades, the complete theoretical and computational framework is presented for the first time here.

The purpose of this paper is to describe a numerical inversion technology developed to reconstruct endocardial electric potential maps on the internal surface of heart chambers utilizing intracavitary multi‐electrode catheter measurements. The objective is to perform the reconstruction real time with high accuracy, thereby allowing the incorporation of the technology into medical imaging systems.

Electrode potential points from several beats are merged in order to maximize the information extracted from the catheter measurements. To solve the ill‐posed inverse problem fast, numerically stable solution algorithms based on generalized Tikhonov regularization and bidiagonalization are developed. The latter algorithm also provides an efficient framework for choosing the regularization parameter optimally.

Results of three examples are presented to thoroughly illustrate the performance of the algorithm: one with synthetic data generated in a computational electromagnetics (virtual lab) environment, thereby allowing exact error analysis; another with measured data from a phantom‐bench human heart model where the effect of measurement errors can be investigated in a controlled environment; and a third example that illustrates how the algorithm performs when the catheter data are collected in vivo in a swine heart.

The speed and accuracy in the three examples successfully prove that the inversion technology can be a key component of medical imaging systems.

While some elements of these computational models and techniques presented have been used for decades, the authors achieve speed and accuracy that have not been reported before by combining multi‐beat catheter measurements, the generalized Tikhonov regularization technique, a bidiagonalization algorithm and other top‐notch linear algebra techniques.