Paper | Title | Page |
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THPOJO12 | LCLS-II-HE Cryomodule Testing at Fermilab | 721 |
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22 Linac Coherent Light Source II (LCLS-II) cryomodules were successfully tested at the Cryomodule Test Facility (CMTF) at Fermilab. Following the completion of the LCLS-II testing program, CMTF has shifted to testing cryomodules for the LCLS-II High Energy upgrade (LCLS-II-HE). The first LCLS-II-HE cryomodule, the verification cryomodule (vCM), was successfully tested and verified the readiness of LCLS-II-HE cryomodule testing at CMTF, and production cryomodule testing has begun. Presented here are the production cryomodule test acceptance criteria, testing plan, and cryomodule test results so far. | ||
Poster THPOJO12 [0.899 MB] | ||
DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-LINAC2022-THPOJO12 | |
About • | Received ※ 18 August 2022 — Revised ※ 27 August 2022 — Accepted ※ 06 September 2022 — Issue date ※ 15 September 2022 | |
Cite • | reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml) | |
THPOPA15 | Anomaly Detection Based Quench Detection System for CW Operation of SRF Cavities | 775 |
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Funding: This work is supported by DASHH (Data Science in Hamburg - HELMHOLTZ Graduate School for the Structure of Matter) under Grant No.: HIDSS-0002. Superconducting radio frequency (SRF) cavities are used in modern particle accelerators to take advantage of their very high quality factor (Q). A higher Q means that a higher RF field can be sustained, and a higher acceleration can be produced in the cavity for length unity. However, in certain situations, e.g., too high RF field, the SRF cavities can experience quenches that risk creating damage due to the rapid increase in the heat load. This is especially negative in continuous wave (CW) operation due to the impossibility of the system to recover during the off-load period. The design goal of a quench-detection system is to protect the system without being a limiting factor during the operation. In this paper, we compare two different classification approaches for improving a quench detection system. We perform tests using traces recorded from LCLS-II and show that the ARSENAL classifier outperforms a CNN classifier in terms of accuracy. |
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DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-LINAC2022-THPOPA15 | |
About • | Received ※ 24 August 2022 — Accepted ※ 25 August 2022 — Issue date ※ 23 September 2022 | |
Cite • | reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml) | |