Abstracts - Dipartimento di Elettronica Applicata

Meta 2010 & FEM 2010 – Rome, 13-15 December 2010
Neural-FEM approach for the analysis of Hysteretic
Materials in unbounded domain
S. Coco (1) , A. Laudani (1) , A. Salvini (2) and F. Riganti Fulginei (2)
(1) University of Catania, DIEES Catania, Italy – e-mail: alaudani@diees.unict.it,
coco@diees.unict.it
(2) Roma Tre University of, DEA
Roma, Italy – e-mail: asalvini@uniroma3.it, riganti@uniroma3.it
The Finite Element method has proved to be a powerful tool for the modeling of
electromagnetic devices, thanks to the possibility of accurate representation of
realistic geometry of the device. On the other hand, the modeling of magnetic material
has also been the subject of many studied, above all to take into account the hysteresis
phenomenon and to model it in an efficient and accurate way. The possibility of using
Neural Networks to model magnetic hysteresis has been verified in literature [1], and
represents a good solution if a dedicated model for the training of the network is
implemented.
In this paper the authors present a Finite Element code for the analysis of magnetic
problems in unbounded domains combined with a Neural Network (NN) approach for
the characterization of magnetic hysteresis. In particular, the proposed NN is capable
to perform the modelling of saturated and non-saturated, symmetric or asymmetric
hysteresis loops. The use of this NN approach is advantageous for avoiding
identification of hysteresis models and their inversion (if requested). Even if a number
of measurements are requested, they are very simple and fast to perform (asymmetric
saturated static loops). Thus, the present approach can be easily embedded into a set
of field equations since it does not require a preliminary knowledge of the H (or B)
waveform. In addition, in order to treat boundlessness in the system of coupled
equations used for solving the magnetic problem, we adopt an iterative scheme based
on a fictitious boundary that encloses all the field sources and the hysteretic material
regions with the aim to define a bounded domain. In this way the unbounded coupled
problem solution is converted into the iterative solution of a sequence of bounded
Dirichlet magnetic hysteresis problems. The boundary conditions on the fictitious
boundary are initially guessed and successively updated according to the solution
obtained in the previous iteration step [3]. The main important advantage of this
approach is its easy implementation starting from FEM codes for bounded domains.
References
[1] H.H. Saliah, D.A. Lowther, and B. Forghani, “A neural network model of magnetic hysteresis for
computational magnetics,” IEEE Trans. on Magnetics, 33, 4146-4148, 1997
[2] F.R. Fulginei and A. Salvini, “Softcomputing for the Identification of the Jiles–Atherton Model
Parameters”, IEEE Trans. On Magnetics, 41, 1100-1108, 2005.
[3] S. Coco and A. Laudani, “Iterative FE Solution of Unbounded Magneto-Thermal Problems”, Proc.
of 10th IGTE Symposium on Numerical Field Calculation in Electrical Engineering, Graz, Austria,
16-18 Sept, 2002.
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