Machine learning techniques in magnetic levitation problems

Manuel Arrayás, José L. Trueba and Carlos Uriarte

Chaos, Solitons & Fractals, 2023, vol. 167, issue C

Abstract: 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.

Keywords: Magnetic levitation; Machine learning; Stability regions (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S096007792201222X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:167:y:2023:i:c:s096007792201222x

DOI: 10.1016/j.chaos.2022.113043

Access Statistics for this article

Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros

More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().