Location : Saclay, France
Yearly income :
About the topic
The use of Barkhausen noise (BN) measurements for assessing the structural health of magnetic materials has become an increasingly important industrial technique the last years. The primary interest in the application of this technique is owing to the direct dependence of the Barkhausen noise signals to the microstructure of the material under consideration as well as its stress level and chemical its chemical composition.
Although rich in information, BN signals are hard to interpret due to the complexity of the underlying physics. The development of efficient and accurate modelling tools is thus necessary to enhance the understanding of the basic features of the measured signals and access to more quantitative estimations of characteristic quantities, such as the level of stress or a rate of chemical components.
Existing approaches can be grossly divided into two families: Monte Carlo- based methods at spin level, and those labelled as mesoscopic ones, based on the solution of a magnetostatic problem at the of the magnetic domains. In these latter approaches, Maxwell equations are solved for a simplified domain configuration, and the displacements of domain walls under the action of an external field are calculated.
About the project
This proposed PhD subject is concerned with the development of a dedicated simulation tool for the calculation of BN signals based on the mesoscopic approach described above. The developed algorithm will exploit empirical considerations on the distribution and dynamic behaviour of domain walls for the selection of representative domain ensembles that will be used as basis of the study. Magnetostatic simulations will be carried out using a 3D numerical solver based on finite integration technique (FIT) developed at CEA LIST. Theoretical results will be compared to experimental data obtained in laboratory controlled conditions partly in the host lab, partly in the laboratoire Roberval (Université de Technologie de Compiègne, UTC), involved in the direction of this PhD topic.