One-dimensional model of cable-in-conduit superconductors under cyclic loading using artificial neural networks

M. Lefik, B. A. Schrefler

Research output: Contribution to journalArticle

12 Scopus citations

Abstract

An artificial neural network with two hidden layers is trained to define a mechanical constitutive relation for superconducting cable under transverse cyclic loading. The training is performed using a set of experimental data. The behaviour of the cable is strongly non-linear. Irreversible phenomena result with complicated loops of hysteresis. The performance of the ANN, which is applied as a tool for storage, interpolation and interpretation of experimental data is investigated, both from numerical, as well as from physical viewpoints.

Original languageEnglish (US)
Pages (from-to)105-117
Number of pages13
JournalFusion Engineering and Design
Volume60
Issue number2
DOIs
StatePublished - May 2002

Keywords

  • Artificial neural network
  • Elasto-plastic hysteresis
  • Frictional heating
  • Numerical model

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Nuclear Energy and Engineering
  • Civil and Structural Engineering
  • Mechanical Engineering

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