Systematic Raman scattering investigations were carried out on TPP during the isothermal transformations of the supercooled liquid into the glacial state, in the 210−230 K temperature range. From these experiments the glaciation process can be interpreted in terms of aborted crystallization. This study reveals that the crystallization aborts in a distinctive stage, i.e., in a glacial state composed of crystallites of the stable crystalline state, characterized by a size strongly dependent on the aging temperature. The size of crystallites can be considered in the nanometric or micrometric scale if the glacial state is prepared, respectively at the low or at high temperature in the 210−230 K range. The time of transformation into the glacial state is also observed as drastically dependent on the aging temperature.

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In this communication, the Preisach and Jiles‐Atherton models are studied to take hysteresis phenomenon into account in finite element analysis. First, the models and their identification procedure are briefly developed. Then, their implementation in the finite element code is presented. Finally, their performances are compared with an electromagnetic system made of soft magnetic composite. Current and iron losses are calculated and compared with the experimental results.

This work proposes a modification in the Jiles-Atherton hysteresis model in order to improve the minor loops representation. The irreversible magnetization component is slightly modified keeping unchanged the other model equations and the model simplicity. Differently to other proposed methodologies found in the literature, the previously knowledge of the magnetic field waveform is not need to assure closed minor loops. Measured and calculated hysteresis curves are used in order to validate the methodology.

To take account of the uncertainties introduced on the soft magnetic materials properties (magnetic behavior law, iron losses) during the manufacturing process, the present work deals with the stochastic modeling of the magnetic behavior law B-H and iron losses of claw pole stator generator. Twenty eight (28) samples of slinky stator (SS) coming from the same production chain have been investigated. The used approaches are similar to those used in mechanics. The accuracy of existing anhysteretic models has been tested first using cross validation techniques. The well known iron loss separation model has been implemented to take into account the variability of the losses. Then, the Multivariate Gaussian distribution is chosen to model the variability and dependencies between identified parameters, for both behavior law and iron loss models. The developed stochastic models allow predicting a 98% confidence interval for the considered samples.

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