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The purpose of this paper is the numerical verification of the linearization coefficient a_p proposed by Turowski for the calculation of the electromagnetic field distribution and therefore the stray losses inside magnetically saturated solid steel conductors.

The numerical verification is performed on a case study consisting of a simple current conductor sheet parallel to a solid steel plate. Numerical computations are compared with analytical calculations with and without inclusion of the semi-empirical Turowski’s coefficient.

Results confirm a good agreement between numerical values for steel with non-linear permeability and analytical ones applying Turowski’s coefficient. This is particularly powerful in the case of analytical calculation of the magnetic surface impedance (SI) to increase precision when hybrid methods are used. The concept of SI enables the establishment of hybrid approaches for the calculation of stray losses, combining the numerical methods (finite difference method, finite element method (FEM), etc.) together with the analytical formulation, gaining from the advantages of both methods.

Previous numerical analysis was focused on the field dependence on time for several depths inside solid steel. The aim of this paper is to investigate the electromagnetic field distribution inside solid steel on a representative FEM model and verify how the linearization coefficient a_p proposed by Turowski works.

At the ISEF'89 Symposium in Lodz an application of the fast reluctance network method and the computer program RNM‐3D for analysis of leakage fields and combined 3‐D screens of tank was presented. Now, similar effective and fast computation of stray losses in such a structure has been performed.

3‐D Reluctance Network Method has proved as an effective, experimentally verified method of an evaluation of leakage fields and interactive design of screens. Though relative loss distribution is also easy to obtain the evaluation of absolute value — due to higher order of nonlinearity is much more difficult. In the paper analysis of this problem and simplified method of total loss calculation in tank wall, with semiempirical correction is given.

Among the many calculation methods that allow the evaluation of magnetic field in different electromagnetic devices is the Reluctance Network Method (RNM). It is based on network theory according to which the analysed space is replaced by the network of magnetic reluctances, with magnetomotive forces as supply sources. This method makes it possible to analyse magnetic fields in two‐dimensional (2‐D) and three‐dimensional (3‐D) domains, and in comparison to other numerical methods (e.g. Finite‐Element Method) the calculation time is much shorter, with relatively good accuracy.

Recent progress in the development of electromagnetic field theory and sophisticated software for solution of complicated, non‐linear, 3‐D structures is not always accompanied with relatively cheap and simply presented engineering instructions, easy to use for regular industrial design. In the paper some theoretical and practical examples are given as to how one can get over a excessive calculating difficulties to obtain quickly simple design directions and reduce complicated theory to simple practical conclusions. The fast and cheap package RNM‐3D is validated by comparison with industrial test data and with the interactive graphics system is the final illustration of the effectiveness of such an approach. RNM‐3D is used successfully in many transformer works the world over.

The purpose of this paper is to show the evolution of microsystems together with modeling methods in the space of dozen years as a result of finished research in the frame of several projects.

In this paper several approaches are presented. First, microsystems were built in multi project wafer technology. They were demonstrators like micromotor, micromirrors or micropumps modeled using dedicated design tool. A multi purpose chip was also designed using HDL description and FEM simulations. The next project concerned chemical sensors, where specialized models were developed and implemented in VHDL‐AMS in order to perform multidomain behavioral simulations. Dedicated tools were also developed for medical applications.

The evolution of MEMS technology is strictly connected with simulation and modeling methods. The success and short time to market need fast and accurate simulation methods. This paper shows that the approach depends on application. Moreover, it is connected with the access to the technology.

This paper presents a brief overview on projects performed in DMCS‐TUL department. It shows the evolution of modeling methods and technology used in developing and fabrication of microsystems for various applications.

Magnetostaic field analysis of 3‐D nonlinear model problem (No.10 ‐ TEAM Workshop) is carried out by the authors using the Reluctance Network Method. The components and resultant flux density are computed and compared with measurements and results obtained by other authors and shaw reasonable convergence and much less CPU time.

Introduction Academic institutions involved in electrical engineering education now realise the importance of students' understanding of the concepts of magnetic fields and their application in various electromechanical devices and systems. Students find it extremely difficult to comprehend magnetic fields and to grasp the physical phenomena which occur in those devices and systems. Often to be able to consider, and skillfully investigate, the behaviour of such devices and systems, students have not only to demonstrate the knowledge and understanding of difficult physical phenomena, but also show the ability to perform sometimes extremely complex mathematical calculations. Of the many aims and objectives to consider when teaching, two important factors are:

This paper presents the numerical solution of the TEAM Workshop Problem 7 obtained by Reluctance Network Method (RNM). The problem represents a three‐dimensional multiply connected eddy current problem with a time — harmonic excitation. The numerical results obtained by RNM in reasonable computing time, agree extremely well with experimental data and other methods results.

The purpose of this paper is to describe a parameter identification method based on multiobjective (MO) deterministic and non-deterministic optimization algorithms to compute the temperature distribution on transformer tank covers.

The strategy for implementing the parameter identification process consists of three main steps. The first step is to define the most appropriate objective function and the identification problem is solved for the chosen parameters using single-objective (SO) optimization algorithms. Then sensitivity to measurement error of the computational model is assessed and finally it is included as an additional objective function, making the identification problem a MO one.

Computations with identified/optimal parameters yield accurate results for a wide range of current values and different conductor arrangements. From the numerical solution of the temperature field, decisions on dimensions and materials can be taken to avoid overheating on transformer covers.

The accuracy of the model depends on its parameters, such as heat exchange coefficients and material properties, which are difficult to determine from formulae or from the literature. Thus the goal of the presented technique is to achieve the best possible agreement between measured and numerically calculated temperature values.

Differing from previous works found in the literature, sensitivity to measurement error is considered in the parameter identification technique as an additional objective function. Thus, solutions less sensitive to measurement errors at the expenses of a degradation in accuracy are identified by means of MO optimization algorithms.