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机器学习应用于X射线断层扫描，作为分析RRP NbSn导线中孔隙的一种新工具。

Machine learning applied to X-ray tomography as a new tool to analyze the voids in RRP NbSn wires.

作者信息

Bagni T, Bovone G, Rack A, Mauro D, Barth C, Matera D, Buta F, Senatore C

机构信息

Department of Quantum Matter Physics, University of Geneva, Geneva, Switzerland.

ESRF - The European Synchrotron, Grenoble, France.

出版信息

Sci Rep. 2021 Apr 8;11(1):7767. doi: 10.1038/s41598-021-87475-6.

DOI:10.1038/s41598-021-87475-6
PMID:33833396
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8032674/
Abstract

The electro-mechanical and electro-thermal properties of high-performance Restacked-Rod-Process (RRP) NbSn wires are key factors in the realization of compact magnets above 15 T for the future particle physics experiments. Combining X-ray micro-tomography with unsupervised machine learning algorithm, we provide a new tool capable to study the internal features of RRP wires and unlock different approaches to enhance their performances. Such tool is ideal to characterize the distribution and morphology of the voids that are generated during the heat treatment necessary to form the NbSn superconducting phase. Two different types of voids can be detected in this type of wires: one inside the copper matrix and the other inside the NbSn sub-elements. The former type can be related to Sn leaking from sub-elements to the copper matrix which leads to poor electro-thermal stability of the whole wire. The second type is detrimental for the electro-mechanical performance of the wires as superconducting wires experience large electromagnetic stresses in high field and high current conditions. We analyze these aspects thoroughly and discuss the potential of the X-ray tomography analysis tool to help modeling and predicting electro-mechanical and electro-thermal behavior of RRP wires and optimize their design.

摘要

高性能重新堆叠棒工艺（RRP）铌锡线的机电和电热性能是实现未来粒子物理实验中15 T以上紧凑型磁体的关键因素。将X射线显微断层扫描与无监督机器学习算法相结合，我们提供了一种新工具，能够研究RRP线的内部特征，并开启不同的方法来提高其性能。这种工具非常适合表征在形成NbSn超导相所需的热处理过程中产生的孔隙的分布和形态。在这类线材中可以检测到两种不同类型的孔隙：一种在铜基体内部，另一种在NbSn子元件内部。前一种类型可能与锡从子元件泄漏到铜基体有关，这会导致整根线的电热稳定性较差。第二种类型对线材的机电性能有害，因为超导线材在高场和高电流条件下会承受较大的电磁应力。我们全面分析了这些方面，并讨论了X射线断层扫描分析工具在帮助建模和预测RRP线的机电和电热行为以及优化其设计方面的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ad/8032674/da32d733cd25/41598_2021_87475_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ad/8032674/5535f08bd852/41598_2021_87475_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ad/8032674/4a198559710c/41598_2021_87475_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ad/8032674/449b8c8a0969/41598_2021_87475_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ad/8032674/306cb06108d5/41598_2021_87475_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ad/8032674/cdc5ef9ee7b1/41598_2021_87475_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ad/8032674/5a07ba719172/41598_2021_87475_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ad/8032674/ef324766c530/41598_2021_87475_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ad/8032674/158d228b6870/41598_2021_87475_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ad/8032674/2acc1fa642e0/41598_2021_87475_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ad/8032674/da32d733cd25/41598_2021_87475_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ad/8032674/5535f08bd852/41598_2021_87475_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ad/8032674/4a198559710c/41598_2021_87475_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ad/8032674/449b8c8a0969/41598_2021_87475_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ad/8032674/306cb06108d5/41598_2021_87475_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ad/8032674/cdc5ef9ee7b1/41598_2021_87475_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ad/8032674/5a07ba719172/41598_2021_87475_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ad/8032674/ef324766c530/41598_2021_87475_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ad/8032674/158d228b6870/41598_2021_87475_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ad/8032674/2acc1fa642e0/41598_2021_87475_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ad/8032674/da32d733cd25/41598_2021_87475_Fig10_HTML.jpg

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