Machine learning techniques in magnetic levitation problems
Fecha
2022
Título de la revista
ISSN de la revista
Título del volumen
Editor
Elsevier
Resumen
We present a method for calculating the stability region of a perfect diamagnet levitated in a magnetic
field created by a circular current loop making use of the machine learning techniques. As an application
we compute stability regions, points of stable equilibrium and stable oscillatory motions in two chip-based
superconducting trap architectures used to levitate superconducting particles. Our procedure is an alternative
to a full numerical scheme based on finite element methods which are expensive to implement for optimizing
experimental parameters.
Descripción
This work was funded by Universidad Rey Juan Carlos, Spain , Programa Propio: Analysis, modelling and simulations of singular structures in continuum models, M2604.
Palabras clave
Citación
Manuel Arrayás, José L. Trueba, Carlos Uriarte, Machine learning techniques in magnetic levitation problems, Chaos, Solitons & Fractals, Volume 167, 2023, 113043, ISSN 0960-0779, https://doi.org/10.1016/j.chaos.2022.113043
Colecciones
Excepto si se señala otra cosa, la licencia del ítem se describe como Atribución 4.0 Internacional