ICALEPCS2023 - List of Keywords (cryogenics)

Paper	Title	Other Keywords	Page
TU2AO02	Textual Analysis of ICALEPCS and IPAC Conference Proceedings: Revealing Research Trends, Topics, and Collaborations for Future Insights and Advanced Search	cavity, controls, laser, LLRF	309
	A. Sulc, A. Eichler, T. Wilksen DESY, Hamburg, Germany
	Funding: This work was supported by HamburgX grant LFF-HHX-03 to the Center for Data and Computing in Natural Sciences (CDCS) from the Hamburg Ministry of Science, Research, Equalities and Districts. In this paper, we show a textual analysis of past ICALEPCS and IPAC conference proceedings to gain insights into the research trends and topics discussed in the field. We use natural language processing techniques to extract meaningful information from the abstracts and papers of past conference proceedings. We extract topics to visualize and identify trends, analyze their evolution to identify emerging research directions and highlight interesting publications based solely on their content with an analysis of their network. Additionally, we will provide an advanced search tool to better search in the existing papers to prevent duplication and easier reference findings. Our analysis provides a comprehensive overview of the research landscape in the field and helps researchers and practitioners to better understand the state-of-the-art and identify areas for future research.
	Slides TU2AO02 [12.762 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TU2AO02
About •	Received ※ 30 September 2023 — Revised ※ 11 October 2023 — Accepted ※ 18 November 2023 — Issued ※ 29 November 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUPDP091	Upgrade of the Process Control System for the Cryogenic Installation of the CERN LHC Atlas Liquid Argon Calorimeter	controls, PLC, software, operation	752
	C.F. Fluder, C. Fabre, L.G. Goralczyk, M. Pezzetti, A. Zmuda CERN, Meyrin, Switzerland K.M. Mastyna AGH, Cracow, Poland
	The ATLAS (LHC detector) Liquid Argon Calorimeter is classified as a critical cryogenic system due to its requirement for uninterrupted operation. The system has been in continuous nominal operation since the start-up of the LHC, operating with very high reliability and availability. Over this period, control system maintenance was focused on the most critical hardware and software interventions, without direct impact on the process control system. Consequently, after several years of steady state operation, the process control system became obsolete (reached End of Life), requiring complex support and without the possibility of further improvements. This led to a detailed review towards a complete upgrade of the PLC hardware and process control software. To ensure uninterrupted operation, longer equipment lifecycle, and further system maintainability, the latest technology was chosen. This paper presents the methodology used for the process control system upgrade during development and testing phases, as well as the experience gained during deployment. It details the architecture of the new system based on a redundant (Hot Standby) PLC solution, the quality assurance protocol used during the hardware validation and software testing phases, and the deployment procedure.
	Poster TUPDP091 [1.886 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUPDP091
About •	Received ※ 03 October 2023 — Accepted ※ 06 December 2023 — Issued ※ 11 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUPDP138	Exploratory Data Analysis on the RHIC Cryogenics System Compressor Dataset	operation, network, data-analysis, controls	907
	Y. Gao, K.A. Brown, R.J. Michnoff, L.K. Nguyen, A.Z. Zarcone, B. van Kuik BNL, Upton, New York, USA A.D. Tran FRIB, East Lansing, Michigan, USA
	Funding: Work supported by Brookhaven Science Associates, LLC under Contract No. DE-SC0012704 with the U.S. Department of Energy. The Relativistic Heavy Ion Collider (RHIC) Cryogenic Refrigerator System is the cryogenic heart that allows RHIC superconducting magnets to operate. Parts of the refrigerator are two stages of compression composed of ten first and five second-stage compressors. Compressors are critical for operations. When a compressor faults, it can impact RHIC beam operations if a spare compressor is not brought online as soon as possible. The potential of applying machine learning to detect compressor problems before a fault occurs would greatly enhance Cryo operations, allowing an operator to switch to a spare compressor before a running compressor fails, minimizing impacts on RHIC operations. In this work, various data analysis results on historical compressor data are presented. It demonstrates an autoencoder-based method, which can catch early signs of compressor trips so that advance notices can be sent for the operators to take action.
	Poster TUPDP138 [2.897 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUPDP138
About •	Received ※ 05 October 2023 — Revised ※ 22 October 2023 — Accepted ※ 30 November 2023 — Issued ※ 11 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THPDP065	Unified Software Production Process for CERN Cryogenic Control Applications	controls, PLC, software, SCADA	1480
	M. Pezzetti, TB. Barbe, C.F. Fluder, TK. Kubla, AT. Tovar-Gonzalez CERN, Meyrin, Switzerland SR. Rog AGH, Cracow, Poland
	The software engineering of process control system for CERN cryogenic installations is based on an automatic code production methodology and continuous integration practice. This solution was initially developed for the LHC Accelerator applications, then adapted to LHC Detectors, test facilities and non-LHC cryogenic facilities. Over the years, this approach allowed the successful implementation of many control system upgrades, as well as the development of new applications while improving quality assurance and minimizing manpower resources. The overall complexity of automatic software production chains, their challenging maintenance, deviation between software production methods for different cryogenic domains and frequent evolution of CERN frameworks led to the system’s complete review. A new unified software production system was designed for all cryogenic domains and industrial technologies used. All previously employed frameworks, tools, libraries, code templates were classified, homogenized and implemented as common submodules, while projects specific configuration were grouped in custom application files. This publication presents the new unified software production solution, benefits from shared methodology between different cryogenics domains, as well as a summary of two years of experience with several cryogenic applications from different PLCs technologies.
	Poster THPDP065 [0.531 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THPDP065
About •	Received ※ 04 October 2023 — Revised ※ 25 October 2023 — Accepted ※ 12 December 2023 — Issued ※ 21 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Other Keywords

Page

Textual Analysis of ICALEPCS and IPAC Conference Proceedings: Revealing Research Trends, Topics, and Collaborations for Future Insights and Advanced Search

cavity, controls, laser, LLRF

309

A. Sulc, A. Eichler, T. Wilksen
DESY, Hamburg, Germany

Funding: This work was supported by HamburgX grant LFF-HHX-03 to the Center for Data and Computing in Natural Sciences (CDCS) from the Hamburg Ministry of Science, Research, Equalities and Districts.
In this paper, we show a textual analysis of past ICALEPCS and IPAC conference proceedings to gain insights into the research trends and topics discussed in the field. We use natural language processing techniques to extract meaningful information from the abstracts and papers of past conference proceedings. We extract topics to visualize and identify trends, analyze their evolution to identify emerging research directions and highlight interesting publications based solely on their content with an analysis of their network. Additionally, we will provide an advanced search tool to better search in the existing papers to prevent duplication and easier reference findings. Our analysis provides a comprehensive overview of the research landscape in the field and helps researchers and practitioners to better understand the state-of-the-art and identify areas for future research.

Slides TU2AO02 [12.762 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TU2AO02

About •

Received ※ 30 September 2023 — Revised ※ 11 October 2023 — Accepted ※ 18 November 2023 — Issued ※ 29 November 2023

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUPDP091

Upgrade of the Process Control System for the Cryogenic Installation of the CERN LHC Atlas Liquid Argon Calorimeter

controls, PLC, software, operation

752

C.F. Fluder, C. Fabre, L.G. Goralczyk, M. Pezzetti, A. Zmuda
CERN, Meyrin, Switzerland
K.M. Mastyna
AGH, Cracow, Poland

The ATLAS (LHC detector) Liquid Argon Calorimeter is classified as a critical cryogenic system due to its requirement for uninterrupted operation. The system has been in continuous nominal operation since the start-up of the LHC, operating with very high reliability and availability. Over this period, control system maintenance was focused on the most critical hardware and software interventions, without direct impact on the process control system. Consequently, after several years of steady state operation, the process control system became obsolete (reached End of Life), requiring complex support and without the possibility of further improvements. This led to a detailed review towards a complete upgrade of the PLC hardware and process control software. To ensure uninterrupted operation, longer equipment lifecycle, and further system maintainability, the latest technology was chosen. This paper presents the methodology used for the process control system upgrade during development and testing phases, as well as the experience gained during deployment. It details the architecture of the new system based on a redundant (Hot Standby) PLC solution, the quality assurance protocol used during the hardware validation and software testing phases, and the deployment procedure.

Poster TUPDP091 [1.886 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUPDP091

About •

Received ※ 03 October 2023 — Accepted ※ 06 December 2023 — Issued ※ 11 December 2023

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUPDP138

Exploratory Data Analysis on the RHIC Cryogenics System Compressor Dataset

operation, network, data-analysis, controls

907

Y. Gao, K.A. Brown, R.J. Michnoff, L.K. Nguyen, A.Z. Zarcone, B. van Kuik
BNL, Upton, New York, USA
A.D. Tran
FRIB, East Lansing, Michigan, USA

Funding: Work supported by Brookhaven Science Associates, LLC under Contract No. DE-SC0012704 with the U.S. Department of Energy.
The Relativistic Heavy Ion Collider (RHIC) Cryogenic Refrigerator System is the cryogenic heart that allows RHIC superconducting magnets to operate. Parts of the refrigerator are two stages of compression composed of ten first and five second-stage compressors. Compressors are critical for operations. When a compressor faults, it can impact RHIC beam operations if a spare compressor is not brought online as soon as possible. The potential of applying machine learning to detect compressor problems before a fault occurs would greatly enhance Cryo operations, allowing an operator to switch to a spare compressor before a running compressor fails, minimizing impacts on RHIC operations. In this work, various data analysis results on historical compressor data are presented. It demonstrates an autoencoder-based method, which can catch early signs of compressor trips so that advance notices can be sent for the operators to take action.

Poster TUPDP138 [2.897 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUPDP138

About •

Received ※ 05 October 2023 — Revised ※ 22 October 2023 — Accepted ※ 30 November 2023 — Issued ※ 11 December 2023

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THPDP065

Unified Software Production Process for CERN Cryogenic Control Applications

controls, PLC, software, SCADA

1480

M. Pezzetti, TB. Barbe, C.F. Fluder, TK. Kubla, AT. Tovar-Gonzalez
CERN, Meyrin, Switzerland
SR. Rog
AGH, Cracow, Poland

The software engineering of process control system for CERN cryogenic installations is based on an automatic code production methodology and continuous integration practice. This solution was initially developed for the LHC Accelerator applications, then adapted to LHC Detectors, test facilities and non-LHC cryogenic facilities. Over the years, this approach allowed the successful implementation of many control system upgrades, as well as the development of new applications while improving quality assurance and minimizing manpower resources. The overall complexity of automatic software production chains, their challenging maintenance, deviation between software production methods for different cryogenic domains and frequent evolution of CERN frameworks led to the system’s complete review. A new unified software production system was designed for all cryogenic domains and industrial technologies used. All previously employed frameworks, tools, libraries, code templates were classified, homogenized and implemented as common submodules, while projects specific configuration were grouped in custom application files. This publication presents the new unified software production solution, benefits from shared methodology between different cryogenics domains, as well as a summary of two years of experience with several cryogenic applications from different PLCs technologies.

Poster THPDP065 [0.531 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THPDP065

About •

Received ※ 04 October 2023 — Revised ※ 25 October 2023 — Accepted ※ 12 December 2023 — Issued ※ 21 December 2023

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)