Paper Info
Title
A neural-FEM approach for the effective permeability estimation of a composite magnetic shielding mortar
Abstract
A mixed Neural-Finite Element Method (FEM) strategy is proposed for the evaluation of magnetic permeability for the equivalent homogenized material of a magnetic shielding mortar containing ferromagnetic particles. The approach is based on a two phases procedure: in the first phase thousands of FEM meshes representing the same sample geometry, with different inclusions distribution, are used to compute the magnetic field; the data so achieved are then used to fed a feedforward neural network, which is able to extract the relationship, among the quantity of magnetic material used (input), its magnetic permeability (input) and the equivalent material characteristic (output). These two phases are unsupervised as in a machine learning approach in such a way that the estimation can be refined automatically. The obtained results are validated by comparison with experimental data available from literature.
Year
DOI
Venue
2019
10.1109/RTSI.2019.8895586
2019 IEEE 5th International forum on Research and Technology for Society and Industry (RTSI)
Keywords
Field
DocType
magnetic shielding,Finite element method,neural networks,multiscale problem
Magnetic field,Feedforward neural network,Biological system,Relative permeability,Electromagnetic shielding,Magnet,Finite element method,Permeability (electromagnetism),Artificial neural network,Materials science
Conference
ISSN
ISBN
Citations 
2687-6809
978-1-7281-3816-9
0
PageRank 
References 
Authors
0.34
4
2
Name
Order
Citations
PageRank
Salvatore Coco112.39
Antonino Laudani2449.11