High temperature superconductors for commercial magnets

Godeke, Arno

doi:10.1088/1361-6668/acf901

Cited by 18 publications

(3 citation statements)

References 129 publications

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“…Superconducting magnets play a vital role in applications such as magnetic resonance imaging [1], motor winding [2], and nuclear fusion [3][4][5]. Superconducting magnets can be driven by an external power source continuously or operated in the persistent current mode [6,7].…”

Section: Introductionmentioning

confidence: 99%

A superconducting switch using induced current in the closed loop circuit

Li,

Xin

et al. 2024

Supercond. Sci. Technol.

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Superconducting magnets have been applied in many fields because of the high magnetic field and the low loss. In order to energize superconducting magnets and operate them in the persistent current mode, the superconducting switch is essential. Recently, a superconducting switch using the interaction between the DC transport current and induced current in a closed loop circuit has been proposed, which cannot only respond fast, but also operate efficiently. In this work, an analytical model based on equivalent circuit is proposed to explain the working principle of this type of superconducting switch. An experimental protype is built to investigate its electromagnetic behaviours and working performance. Impacting factors of the voltage across the superconducting switch have been clarified based on experimental results. The method based on asymmetric AC magnetic field is proposed to enhance the average voltage across the superconducting switch and its performance has been verified through experimental tests. Besides, the advantages and application prospects of the superconducting switch are discussed.

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Section: Introductionmentioning

confidence: 99%

A superconducting switch using induced current in the closed loop circuit

Li,

Xin

et al. 2024

Supercond. Sci. Technol.

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“…For instance, high-temperature superconducting (HTS) materials typically have n-values around 20, whereas their low-temperature superconducting (LTS) counterparts boast values closer to 100. While HTS offers enhanced magnet protection, operating it near the critical current threshold-around 90%-can lead to resistive voltages, resulting in energy losses and potentially harmful heating effects [10,11].…”

Section: Introductionmentioning

confidence: 99%

A comprehensive machine learning-based investigation for the index-value prediction of 2G HTS coated conductor tapes

Bonab,

Russo,

Morandi

et al. 2024

Mach. Learn.: Sci. Technol.

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Index-value, or so-called n-value prediction is of paramount importance for understanding the superconductors’ behaviour specially when modelling of superconductors is needed. This parameter is dependent on several physical quantities including temperature, the magnetic field’s density and orientation, and affects the behaviour of HTS devices made out of coated conductors in terms of losses and quench propagation. In this paper, a comprehensive analysis of many machine learning methods for estimating the n-value has been carried out. The results demonstrated that Cascade Forward Neural Network (CFNN) excels in this scope. Despite needing considerably higher training time when compared to the other attempted models, it performs at the highest accuracy, with 0.48 Root Mean Squared Error (RMSE) and 99.72% Pearson coefficient for goodness of fit (R-squared). On the other hand, the Rigid Regression method had the worst predictions with 4.92 RMSE and 37.29% R-squared. Also, Random Forest, boosting methods, and simple Feed Forward Neural Network can be considered as a middle accuracy model with faster training time than CFNN. The findings of this study not only advance modelling of superconductors but also pave the way for applications and further research on machine learning plug-and-play codes for superconducting studies including modelling of superconducting devices.

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“…However, most mechanical homogenization models ignored the fine structure of the HTS tape and cannot accurately calculate the stress-strain inside it, especially in the superconducting layer. In practical operation, the mechanical loads in HTS magnets cause complicated stress state inside the HTS tape such as tensile, bending, torsional stress, etc [28]. Therefore, it is necessary to develop a new modeling scheme to accurately calculate the stress-strain distribution inside the HTS tape during the operation of HTS magnets.…”

Section: Introductionmentioning

confidence: 99%

Multiscale modeling on the multi-physical behaviors of high temperature superconducting magnets based on a combined global homogenization and local refinement scheme

Wang,

Jing

2024

Supercond. Sci. Technol.

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The safe and stable operation is a crucial issue in the development of high-field high temperature superconducting (HTS) magnets. In this paper, we construct a multiscale model which couples the homogenized global (macroscopic) behavior and the refined local (mesoscopic) characteristics to simulate the coupled electromagnetic-mechanical-thermal behaviors of the HTS magnets. In the model, the numerical homogenization method is adopted to simulate the macroscopic behavior of the magnets and identify the “dangerous region” of the magnet which are prone to damage or quench. Then, a refined local sub-model which coupling with the macroscopic homogenization model is established by considering the microstructure and physical parameters of each components of the HTS tapes in the “dangerous region”. Thus, a combined global homogenization and local refinement scheme which balances the computational efficiency and numerical accuracy is developed to simulate the coupled multi-physical behaviors of the HTS magnets including the quench and its propagation. Our results show that the refined local sub-model can simulate the electromagnetic field and the stress-strain at the scale of the tape more accurately. Characteristics, such as the discontinuous stress distribution across the interfaces between different layers and the current shunt from the HTS layer to metallic layers during the quench process of HTS tapes, which are beyond the capability of the homogenization model, have also been well depicted by the refined sub-model.

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High temperature superconductors for commercial magnets

Cited by 18 publications

References 129 publications

A superconducting switch using induced current in the closed loop circuit

A superconducting switch using induced current in the closed loop circuit

A comprehensive machine learning-based investigation for the index-value prediction of 2G HTS coated conductor tapes

Multiscale modeling on the multi-physical behaviors of high temperature superconducting magnets based on a combined global homogenization and local refinement scheme

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