| Paper | Title | Page |
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| THPDP081 | Exploring Ethernet-Based CAMAC Replacements at ATLAS | 1542 |
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Funding: This work was supported by the US Department of Energy, Office of Nuclear Physics, under Contract No. DE-AC02-06CH11357. This research used resources of ANL’s ATLAS facility. The Argonne Tandem Linear Accelerating System (ATLAS) facility at Argonne National Laboratory is researching ways at avoiding a crisis caused by the end-of-life issues with its 30 year-old CAMAC system. Replacement parts for CAMAC have long since been unavailable causing the potential for long periods of accelerator down times once the limited CAMAC spares are exhausted. ATLAS has recently upgraded the Ethernet in the facility from a 100-Mbps (max) to a 1-Gbps network. Therefore, an Ethernet-based data acquisition system is desirable. The data acquisition replacement requires reliability, speed, and longevity to be a viable upgrade to the facility. In addition, the transition from CAMAC to a modern data acquisition system will be done with minimal interruption of operations. |
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| DOI • | reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THPDP081 | |
| About • | Received ※ 10 October 2023 — Revised ※ 11 October 2023 — Accepted ※ 13 October 2023 — Issued ※ 20 October 2023 | |
| Cite • | reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml) | |
| THPDP082 | Teaching an Old Accelerator New Tricks | 1545 |
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Funding: This work was supported by the U.S. Department of Energy, under Contract No. DE-AC02-06CH11357. This research used resources of ANLs ATLAS facility, which is a DOE Office of Science User Facility. The Argonne Tandem Linac Accelerator System (ATLAS) has been a National User Facility since 1985. In that time, many of the systems that help operators retrieve, modify, and store beamline parameters have not kept pace with the advancement of technology. Development of a new method of storing and retrieving beamline parameters resulted in the testing and installation of a time-series database as a potential replacement for the traditional relational database. InfluxDB was selected due to its self-hosted Open-Source version availability as well as the simplicity of installation and setup. A program was written to periodically gather all accelerator parameters in the control system and store them in the time-series database. This resulted in over 13,000 distinct data points, captured at 5-minute intervals. A second test captured 35 channels on a 1-minute cadence. Graphing of the captured data is being done on Grafana, an Open-Source version is available that co-exists well with InfluxDB as the back-end. Grafana made visualizing the data simple and flexible. The testing has allowed for the use of modern graphing tools to generate new insights into operating the accelerator, as well as opened the door to building large data sets suitable for Artificial Intelligence and Machine Learning applications. |
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| DOI • | reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THPDP082 | |
| About • | Received ※ 10 October 2023 — Revised ※ 11 October 2023 — Accepted ※ 06 December 2023 — Issued ※ 13 December 2023 | |
| Cite • | reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml) | |