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

M. Lefik; B. A. Schrefler

doi:10.1016/S0920-3796(01)00602-0

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

M. Lefik, B. A. Schrefler

Research output: Contribution to journal › Article › peer-review

15 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 language	English (US)
Pages (from-to)	105-117
Number of pages	13
Journal	Fusion Engineering and Design
Volume	60
Issue number	2
DOIs	https://doi.org/10.1016/S0920-3796(01)00602-0
State	Published - 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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10.1016/S0920-3796(01)00602-0

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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.",

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AU - Lefik, M.

AU - Schrefler, B. A.

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N2 - 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.

AB - 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.

KW - Artificial neural network

KW - Elasto-plastic hysteresis

KW - Frictional heating

KW - Numerical model

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

Abstract

Keywords

ASJC Scopus subject areas

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