Dynamic Ferromagnetic Hysteresis Modelling Using a Preisach-Recurrent Neural Network Model

Dynamic Ferromagnetic Hysteresis Modelling Using a Preisach-Recurrent Neural Network Model

In this work, a Preisach-recurrent neural network model is proposed to predict the dynamic hysteresis in ARMCO pure iron, an important soft magnetic material in particle accelerator magnets. A recurrent neural network coupled with Preisach play operators is proposed, along with a novel validation me...

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Bibliographic Details
Main Authors: Christian Grech, Marco Buzio, Mariano Pentella, Nicholas Sammut
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:Materials
Subjects:
ARMCO pure iron
dynamic hysteresis loop
machine learning
magnetic properties
particle accelerators
Preisach
Online Access:https://www.mdpi.com/1996-1944/13/11/2561

Internet

https://www.mdpi.com/1996-1944/13/11/2561

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