Search results

A mixed variational formulation of the free boundary problem involved in the analysis of reverse‐biased semiconductor devices is put forward. This can be profitably used in the investigation of the field distribution near the junction and at the surface of devices. A peculiar feature of the new formulation is that the electric field is assumed as a variable in the solution, together with the potential, thus enabling the electric field to be determined directly and accurately. The numerical algorithm associated with the method turns out to be quite simple and can be easily and readily implemented even on a desktop computer.

Historically, the idea of using electrostatic phenomena to produce motion has long stimulated the activity of scientists. Although the power generated by electrostatic motors is modest, the absence of windings and ferromagnetic material makes this kind of device competitive for applications characterized by low levels of torque and reduced volumes. During last years a renewed attention appeared towards electrostatic devices in the microscopic scale; their fabrication has been possible thanks to the technology for Si‐integrated‐circuits. In particular, electrostatic micromotors have an increasing role as position actuators when submillimetric movements are required. Methodologies of numerical simulation applied to microdevices are a helpful tool for the designer, who should fulfil criteria often in mutual clash like electromechanical response and fabrication cost. More generally, procedures of automated optimal design are now available, tackling the design problem as the constrained minimization of an objective function suitably set up.

The work aims at investigating the law of miniaturization of a linear reluctance motor by expressing the ratio of force to mass as a function of bar position in per unit, for different scale factors. Corresponding to the same factors, inductance is also computed. Finally the ratio of the bar length to external diameter is changed and the analysis is accordingly repeated.

Introduces papers from this area of expertise from the ISEF 1999 Proceedings. States the goal herein is one of identifying devices or systems able to provide prescribed performance. Notes that 18 papers from the Symposium are grouped in the area of automated optimal design. Describes the main challenges that condition computational electromagnetism’s future development. Concludes by itemizing the range of applications from small activators to optimization of induction heating systems in this third chapter.

Gives introductory remarks about chapter 1 of this group of 31 papers, from ISEF 1999 Proceedings, in the methodologies for field analysis, in the electromagnetic community. Observes that computer package implementation theory contributes to clarification. Discusses the areas covered by some of the papers ‐ such as artificial intelligence using fuzzy logic. Includes applications such as permanent magnets and looks at eddy current problems. States the finite element method is currently the most popular method used for field computation. Closes by pointing out the amalgam of topics.

In the paper, attention is focused on a class of single‐phase transformers that are employed when a high‐voltage withstand test is required for verifying the quality of the dielectric insulation of a given component. The HV winding of this kind of transformer is made up of several layers, characterized by height that decreases along with the increase of the voltage profile in order to keep the distance between winding and ground within acceptable limits. Therefore, the designer of such devices is mainly concerned with the shaping of the HV winding; starting from a tentative configuration, he has to find the winding shape such that the electric breakdown cannot occur, at the same time keeping the volume of oil and active materials as small as possible. Traditionally, the design is developed by means of a trial‐and‐error approach based on a sequence of field analyses, varying a design variable at a time; the paper shows how the design problem can be solved more efficiently by optimizing the profile of the winding in an automatic way.

Discusses the automated shape design of the electrodes supplying an arrangement for high‐voltage test. Obtains results that are feasible for industrial applications by means of an optimisation algorithm able to process discrete‐valued design variables.

The main goal of this paper is to show the constant growth of recent research work on automated optimal design of low‐frequency electromagnetic systems by reviewing the current literature on the topic.

The paper reports recent experiences of the authors in the automated optimal design of devices and systems for induction heating. The results presented have been obtained in the frame of a long‐lasting cooperation between Laboratory of Electroheat, University of Padova and Electromagnetic Devices CAD Laboratory, University of Pavia. In particular, two case studies are discussed; in both cases, the shape design of the inductor is carried out in a systematic way, by minimizing user‐defined objective functions depending on design variables and subject to bounds and constraints. When the design problem is characterized by many objectives which are in mutual conflict, the non‐dominated set of solutions is identified.

Transverse flux induction heating (TFH) is a process advantageously applied for the heat treatment of thin non‐ferrous metal strips. In comparison with the better known longitudinal flux heating the design of TFH inductors is more complex. In fact both the prediction of power density distribution in the strip and the calculation of the thermal transient during the heating process require a solution of 3D electromagnetic and thermal problems. Moreover the requirements for a good inductor design are in conflict with each other. In the paper a code for the solution of 3D electromagnetic and thermal problems suitable for the design of TFH systems is presented. The analytical‐numerical approach (analytical for the electromagnetic problem, numerical for the thermal one) is suitable for coupling with optimisation algorithms. Both evolutionary strategy and simplex methods and their combination have been used in order to obtain an optimal design for a particular application of TFH.