Search results

In electrochemotherapy, flexible electrodes, composed by an array of needles, are applied to human tissues to treat large surface tumors. The positioning of the needles in the tissue depends on the surface curvature. The parallel needle case is preferred, as their relative inclinations strongly affect the actual distribution of electric field. Nevertheless, in some case, small inclinations are unavoidable. The purpose of this paper is to study the electric field distribution for non-parallel needles.

The effect of electrode position is evaluated systematically by means of numerical models and experiments on phantoms for two different angles (5° and 30°) and compared with the case of parallel needles. Potato model was used as phantom, as this tissue becomes dark after few hours from electroporation. The electroporation degree was gauged from the color changings on the potatoes.

The distribution of electric field in different needle configuration is found by means of finite element analysis (FEA) and experiments on potatoes. The electric field level of inclined needles was compared with parallel needle case. In particular, the electric field distribution in the case of inclined needles could be very different with respect to the one in the case of parallel needles. The degree of enhancement for different inclinations is visualized by potato color intensity. The FEA suggested that the needle parallelism has to be maintained as possible as if the tips are closer to each other, the electric field intensity could be different with respect to the one in the case of parallel needles.

This paper analyzes the effect of inclined electrodes considering also the non-linearity of tissues.

Inverse problems in electromagnetism, namely, the recovery of sources (currents or charges) or system data from measured effects, are usually ill-posed or, in the numerical formulation, ill-conditioned and require suitable regularization to provide meaningful results. To test new regularization methods, there is the need of benchmark problems, which numerical properties and solutions should be well known. Hence, this study aims to define a benchmark problem, suitable to test new regularization approaches and solves with different methods.

To assess reliability and performance of different solving strategies for inverse source problems, a benchmark problem of current synthesis is defined and solved by means of several regularization methods in a comparative way; subsequently, an approach in terms of an artificial neural network (ANN) is considered as a viable alternative to classical regularization schemes. The solution of the underlying forward problem is based on a finite element analysis.

The paper provides a very detailed analysis of the proposed inverse problem in terms of numerical properties of the lead field matrix. The solutions found by different regularization approaches and an ANN method are provided, showing the performance of the applied methods and the numerical issues of the benchmark problem.

The value of the paper is to provide the numerical characteristics and issues of the proposed benchmark problem in a comprehensive way, by means of a wide variety of regularization methods and an ANN approach.

An inductor for the uniform heating of the extremity of a ferromagnetic steel tube for stress relieving is considered. The main goal of the study is to investigate the possibility to achieve a reasonable design of the inductor when dealing with many design variables.

Genetic optimization algorithms are used for this purpose, demonstrating the applicability of these techniques to the design of induction heating inductors. Genetic algorithms provide to the designer several optimal solutions belonging to Pareto Front, and this way they allow choosing the solution that better fits the technological requirements. In any case, the designer has to adapt the chosen solution to fit in with the real possibilities in industrial application.

The study demonstrates that automatic optimization methods may help the designer of the induction heating system to solve complex problems with very conflicting technological requirements.

In the paper, a problem with a high number of design variables is solved. Moreover, the goals of the optimization process are strongly conflicting, and the proposed problem is a challenging one.

This paper aims to deal with the optimal shape design of a class of permanent magnet motors by minimizing multiple objectives according to an original interpretation of Pareto optimality. The proposed method solves a many-objective problems characterized by five objective functions and five design variables with evolution strategy algorithms, classically used for single- and multi-objective (two objective functions) optimization problems.

Two approaches are proposed in the paper: the All-Objectives (AO) and the Many-Objectives (MO) optimization approach. The former is based on a single-objective optimization of a preference function, i.e. a normalized weighted sum. In contrast, in the MO a multi-objective optimization algorithm is applied to the minimization of a weight-free preference function and simultaneously to a maximization of the distance of the current solution from the prototype. The optimizations are based on an equivalent circuit model of the Permanent Magnet (PM) motor, but the results are assessed by means of finite element analyses (FEAs).

An extensive study of the solutions obtained by means of the different optimization approaches is provided by means of post-processing analyses. Both the approaches find non-dominated solutions with respect to the prototype that are substantially improving the initial solution. The points of strength along with the weakness points of each solution with respect to the prototype are analysed in depth.

The paper gives a good guide to the designers of electric motors, focussed on a shape design optimization.

Considering simultaneously five objective functions in an automated optimal design procedure is challenging. The proposed approach, based on a well-known and established optimization algorithm, but exploiting a new concept of degree of conflict, can lead to new results in the field of automated optimal design in a many-objective context.

The purpose of the study is to design the compensation network of a dynamic wireless power transfer system, considering the movement of the receiving coil along an electrified track with a large number of inductors buried on the road.

A finite element model has been developed to calculate the self-inductances of transmitting and receiving coils as well as the mutual inductances between the receiving coil and the transmitting ones in the nearby and for various relative positions. The calculated lumped parameters, self-inductances and mutual inductances depending on the relative positions between the coils, have been considered to design the compensation network of the active coils, which is composed of three capacitive or inductive reactances connected in the T form. The optimal values of the six reactances, three for the transmitting coils and three for the receiving one, have been calculated by resorting to the Genetic Algorithm NSGA-II.

In this paper, the results obtained by means of the optimizations have broadly discussed. The optimal values of the reactances of the compensation networks show a clear trend in the receiving part of the circuit. On the other hand, the problem seems very sensitive to the values of the reactances in the transmitting circuit.

Dynamic wireless power transfer system is one of the newest ways of recharging electric vehicles. Hence, the design of compensation networks for this kind of systems is a new topic, and there is the need to investigate possible solutions to obtain a good performance of the recharging system.

The purpose of this paper is to show how the EStra-Many method works on optimization problems characterized by high-dimensionality of the objective space. Moreover, a comparison with a more classical approach (a constrained bi-objective problem solved by means of NSGA-II) is done.

The six reactances of a compensation network (CN) for a wireless power transfer system (WPTS) are synthesized by means of an automated optimal design. In particular, an evolutionary algorithm EStra-Many coupled with a sorting strategy has been applied to an optimization problem with four objective functions (OFs). To assess the obtained results, a classical genetic algorithm NSGA-II has been run on a bi-objective problem, constrained by two functions, and the solutions have been analyzed and compared with the ones obtained by EStra-Many.

The proposed EStra-Many method identified a solution (CN synthesis) that enhances the WPTS, considering all the four OFs. In particular, to assess the synthesized CN, the Bode diagram of the frequency response and a circuital simulation were evaluated a posteriori; they showed good performance of the CN, with smooth response and without unwanted oscillations when fed by a square wave signal with offset. The EStra-Many method has been able to find a good solution among all the feasible solutions, showing potentiality also for other fields of research, in fact, a solution nondominated with respect to the starting point has been identified. From the methodological viewpoint, the main finding is a new formulation of the many-objective optimization problem based on the concept of degree of conflict, which gives rise to an implementation free from hierarchical weights.

The new approach EStra-Many used in this paper showed to properly find an optimal solution, trading-off multiple objectives. The compensation network so synthesized by the proposed method showed good properties in terms of frequency response and robustness. The proposed method, able to deal effectively with four OFs, could be applied to solve problems with a higher number of OFs in a variety of applications because of its generality.

The paper presents the Finite Element (FE) evaluation of the magnetic field emitted by a Wireless Power Transfer Systems used to charge the battery of electrical vehicles. An original approach for reducing the mesh size of the 3D FE model is used.

A minicar equipped with a circular coil is considered, while the transmitting coil is coherent with the Society of Automotive Engineers (SAE) standard. The different shape of the coils and a possible misalignment are considered as possible sources of emitted magnetic field, which a person could be exposed to. To this end, a FE model is implemented. Because of the complexity of the mesh, a suitable 3D model is used. This model is previously validated and then used for evaluating the magnetic field around the Wireless Power Transfer Systems (WPTS).

The magnetic flux density around the WPTS is calculated and compared with the International Commission on Non-Ionizing Radiation Protection (ICNIRP) limits.

The proposed 3D model, whose validation is shown in the paper, is able to compute the magnetic field with high accuracy despite the presence of a conductive and ferromagnetic thin structure, the steel layer related to the car frame, which would need a very fine mesh with a large number of elements to solve Maxwell equations.