ICALEPCS2019 - List of Keywords (extraction)

Paper	Title	Other Keywords	Page
MOPHA068	Improving Reliability of the Fast Extraction Kicker Timing Control at the AGS	kicker, software, timing, controls	373
	P.K. Kankiya, J.P. Jamilkowski BNL, Upton, New York, USA
	Funding: Work supported by Brookhaven Science Associates, LLC under Contract No. DE-SC0012704 with the U.S. Department of Energy. The fast extraction kicker system at AGS to RHIC transport line uses Stanford Research DG535 delay generators to time, synchronize, and trigger charging power supplies and high-level thyratron trigger pulse generators. This timing system has been upgraded to use an SRS DG645 instrument due to reliability issues with the aforementioned model and slow response time of GPIB buses. The new model provides the relative timing of the separate kicker modules of the assembly from a synchronized external trigger with the RF system. Specifications of the timing scheme, an algorithm to load settings synchronized with RHIC real-time events, and performance analysis of the software will be presented in the paper.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-MOPHA068
About •	paper received ※ 12 July 2019 paper accepted ※ 10 October 2019 issue date ※ 30 August 2020
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

MOPHA088	Consolidation of Re-Triggering System of LHC Beam Dumping System at CERN	operation, simulation, dumping, coupling	412
	N. Magnin, W. Bartmann, C. Bracco, E. Carlier, G. Gräwer, T.D. Mottram, E. Renner, Rodziewicz, J.P. Rodziewicz, V. Senaj, C. Wiesner CERN, Geneva, Switzerland
	The Trigger Synchronization and Distribution System (TSDS) is a core part of the LHC Beam Dump System (LBDS). It comprises redundant Re-Trigger Lines (RTLs) that allow fast re-triggering of all high-voltage pulsed generators in case one self-triggers, resulting in a so-called asynchronous dump. For reliability reasons, the TSDS relies on many RTL redundant trigger sources that do not participate directly to the execution of a normal dump. After every dump, signals propagating on the RTLs are analyzed by Post Operation Check (POC) systems, to validate the correct performance and synchronization of all redundant triggers. The LBDS operated reliably since the start-up of LHC in 2008, but during the Run 2 of the LHC, new failure modes were identified that could incur damage for the beam dump block. In order to correct these failure modes, an upgrade of the TSDS is realized during the LS2. This paper reviews the experience gained with the LBDS during Run 2 of the LHC operation and describes the new architecture of the TSDS being implemented. Measurements and simulations of signals propagating on the RTL are presented, and the analysis performed by the POC systems are explained.
	Poster MOPHA088 [2.435 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-MOPHA088
About •	paper received ※ 30 September 2019 paper accepted ※ 10 October 2019 issue date ※ 30 August 2020
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEMPL001	An Application of Machine Learning for the Analysis of Temperature Rise on the Production Target in Hadron Experimental Facility at J-PARC	target, operation, proton, EPICS	992
	K. Agari, H. Akiyama, Y. Morino, Y. Sato, A. Toyoda KEK, Tsukuba, Japan
	Hadron Experimental Facility (HEF) is designed to handle an intense slow-extraction proton beam from the 30 GeV Main Ring (MR) of Japan Proton Accelerator Research Complex (J-PARC). Proton beams of 5·10¹³ protons per spill during 2 seconds in the 5.2 seconds accelerator operating cycle were extracted from MR to HEF in the 2018 run. In order to evaluate soundness of the target, we have analyzed variation of temperature rise on the production target, which depends on the beam conditions on the target. Predicted temperature rise is calculated from the existing data of the beam intensity, the spill length (duration of the beam extraction) and the beam position on the target, using a linear regression analysis with a machine learning library, Scikit-learn. As a result, the predicted temperature rise on the production target shows good agreement with the measured one. We have also examined whether the present method of the predicted temperature rise from the existing data can be applied to unknown data in the future runs. The present paper reports the status of the measurement system of temperature rise on the target with machine learning in detail.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-WEMPL001
About •	paper received ※ 28 September 2019 paper accepted ※ 10 October 2019 issue date ※ 30 August 2020
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPHA065	Upgraded Beam Instrumentation DAQ for GSI and FAIR: Overview and First Experiences	controls, timing, injection, software	1248
	T. Hoffmann, H. Bräuning GSI, Darmstadt, Germany
	As construction of the FAIR accelerator complex progresses, the existing heavy ion synchroton SIS18, the storage ring ESR and the high energy beam transfer lines HEBT have been upgraded to the future control system. Within this upgrade the beam instrumentation (BI) data acquisition systems (DAQ) have been heavily modernized too. These are now integrated into the control system with its White Rabbit based timing system, data supply (i.e. ion species, energy, etc) and services like archiving. Dedicated clients running in the main control room allow visualization and correlation of the data and status of the BI devices. The DAQ hardware has been upgraded using new state-of-the-art components. With a trend to slowly phase out VME based systems, solutions based on standard Industrial PC for few channels as well as on the new µTCA standard for many channels have been successfully implemented. This contribution will give an overview over the upgraded BI-DAQ systems like current transformers and counter applications for ionization chambers, scintillators, and more. It will also present first experiences during beam operation with the new control system, which started summer last year.
	Poster WEPHA065 [2.710 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-WEPHA065
About •	paper received ※ 30 September 2019 paper accepted ※ 09 October 2019 issue date ※ 30 August 2020
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPHA163	NXCALS - Architecture and Challenges of the Next CERN Accelerator Logging Service	software, controls, operation, hardware	1465
	J.P. Wozniak, C. Roderick CERN, Geneva, Switzerland
	CERN’s Accelerator Logging Service (CALS) is in production since 2003 and stores data from accelerator infrastructure and beam observation devices. Initially expecting 1 TB/year, the Oracle based system has scaled to cope with 2.5 TB/day coming from >2.3 million signals. It serves >1000 users making an average of 5 million extraction requests per day. Nevertheless, with a large data increase during LHC Run 2 the CALS system began to show its limits, particularly for supporting data analytics. In 2016 the NXCALS project was launched with the aim of replacing CALS from Run 3 onwards, with a scalable system using "Big Data" technologies. The NXCALS core is production-ready, based on open-source technologies such as Hadoop, HBase, Spark and Kafka. This paper will describe the NXCALS architecture and design choices, together with challenges faced while adopting these technologies. This includes: write/read performance when dealing with vast amounts of data from heterogenous data sources with strict latency requirements; how to extract, transform and load >1 PB of data from CALS to NXCALS. NXCALS is not CERN-specific and can be relevant to other institutes facing similar challenges.
	Poster WEPHA163 [1.689 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-WEPHA163
About •	paper received ※ 29 September 2019 paper accepted ※ 09 October 2019 issue date ※ 30 August 2020
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Other Keywords

Page

MOPHA068

Improving Reliability of the Fast Extraction Kicker Timing Control at the AGS

kicker, software, timing, controls

373

P.K. Kankiya, J.P. Jamilkowski
BNL, Upton, New York, USA

Funding: Work supported by Brookhaven Science Associates, LLC under Contract No. DE-SC0012704 with the U.S. Department of Energy.
The fast extraction kicker system at AGS to RHIC transport line uses Stanford Research DG535 delay generators to time, synchronize, and trigger charging power supplies and high-level thyratron trigger pulse generators. This timing system has been upgraded to use an SRS DG645 instrument due to reliability issues with the aforementioned model and slow response time of GPIB buses. The new model provides the relative timing of the separate kicker modules of the assembly from a synchronized external trigger with the RF system. Specifications of the timing scheme, an algorithm to load settings synchronized with RHIC real-time events, and performance analysis of the software will be presented in the paper.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-MOPHA068

About •

paper received ※ 12 July 2019 paper accepted ※ 10 October 2019 issue date ※ 30 August 2020

Export •

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

MOPHA088

Consolidation of Re-Triggering System of LHC Beam Dumping System at CERN

operation, simulation, dumping, coupling

412

N. Magnin, W. Bartmann, C. Bracco, E. Carlier, G. Gräwer, T.D. Mottram, E. Renner, Rodziewicz, J.P. Rodziewicz, V. Senaj, C. Wiesner
CERN, Geneva, Switzerland

The Trigger Synchronization and Distribution System (TSDS) is a core part of the LHC Beam Dump System (LBDS). It comprises redundant Re-Trigger Lines (RTLs) that allow fast re-triggering of all high-voltage pulsed generators in case one self-triggers, resulting in a so-called asynchronous dump. For reliability reasons, the TSDS relies on many RTL redundant trigger sources that do not participate directly to the execution of a normal dump. After every dump, signals propagating on the RTLs are analyzed by Post Operation Check (POC) systems, to validate the correct performance and synchronization of all redundant triggers. The LBDS operated reliably since the start-up of LHC in 2008, but during the Run 2 of the LHC, new failure modes were identified that could incur damage for the beam dump block. In order to correct these failure modes, an upgrade of the TSDS is realized during the LS2. This paper reviews the experience gained with the LBDS during Run 2 of the LHC operation and describes the new architecture of the TSDS being implemented. Measurements and simulations of signals propagating on the RTL are presented, and the analysis performed by the POC systems are explained.

Poster MOPHA088 [2.435 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-MOPHA088

About •

paper received ※ 30 September 2019 paper accepted ※ 10 October 2019 issue date ※ 30 August 2020

Export •

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

WEMPL001

An Application of Machine Learning for the Analysis of Temperature Rise on the Production Target in Hadron Experimental Facility at J-PARC

target, operation, proton, EPICS

992

K. Agari, H. Akiyama, Y. Morino, Y. Sato, A. Toyoda
KEK, Tsukuba, Japan

Hadron Experimental Facility (HEF) is designed to handle an intense slow-extraction proton beam from the 30 GeV Main Ring (MR) of Japan Proton Accelerator Research Complex (J-PARC). Proton beams of 5·10¹³ protons per spill during 2 seconds in the 5.2 seconds accelerator operating cycle were extracted from MR to HEF in the 2018 run. In order to evaluate soundness of the target, we have analyzed variation of temperature rise on the production target, which depends on the beam conditions on the target. Predicted temperature rise is calculated from the existing data of the beam intensity, the spill length (duration of the beam extraction) and the beam position on the target, using a linear regression analysis with a machine learning library, Scikit-learn. As a result, the predicted temperature rise on the production target shows good agreement with the measured one. We have also examined whether the present method of the predicted temperature rise from the existing data can be applied to unknown data in the future runs. The present paper reports the status of the measurement system of temperature rise on the target with machine learning in detail.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-WEMPL001

About •

paper received ※ 28 September 2019 paper accepted ※ 10 October 2019 issue date ※ 30 August 2020

Export •

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

WEPHA065

Upgraded Beam Instrumentation DAQ for GSI and FAIR: Overview and First Experiences

controls, timing, injection, software

1248

T. Hoffmann, H. Bräuning
GSI, Darmstadt, Germany

As construction of the FAIR accelerator complex progresses, the existing heavy ion synchroton SIS18, the storage ring ESR and the high energy beam transfer lines HEBT have been upgraded to the future control system. Within this upgrade the beam instrumentation (BI) data acquisition systems (DAQ) have been heavily modernized too. These are now integrated into the control system with its White Rabbit based timing system, data supply (i.e. ion species, energy, etc) and services like archiving. Dedicated clients running in the main control room allow visualization and correlation of the data and status of the BI devices. The DAQ hardware has been upgraded using new state-of-the-art components. With a trend to slowly phase out VME based systems, solutions based on standard Industrial PC for few channels as well as on the new µTCA standard for many channels have been successfully implemented. This contribution will give an overview over the upgraded BI-DAQ systems like current transformers and counter applications for ionization chambers, scintillators, and more. It will also present first experiences during beam operation with the new control system, which started summer last year.

Poster WEPHA065 [2.710 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-WEPHA065

About •

paper received ※ 30 September 2019 paper accepted ※ 09 October 2019 issue date ※ 30 August 2020

Export •

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

WEPHA163

NXCALS - Architecture and Challenges of the Next CERN Accelerator Logging Service

software, controls, operation, hardware

1465

J.P. Wozniak, C. Roderick
CERN, Geneva, Switzerland

CERN’s Accelerator Logging Service (CALS) is in production since 2003 and stores data from accelerator infrastructure and beam observation devices. Initially expecting 1 TB/year, the Oracle based system has scaled to cope with 2.5 TB/day coming from >2.3 million signals. It serves >1000 users making an average of 5 million extraction requests per day. Nevertheless, with a large data increase during LHC Run 2 the CALS system began to show its limits, particularly for supporting data analytics. In 2016 the NXCALS project was launched with the aim of replacing CALS from Run 3 onwards, with a scalable system using "Big Data" technologies. The NXCALS core is production-ready, based on open-source technologies such as Hadoop, HBase, Spark and Kafka. This paper will describe the NXCALS architecture and design choices, together with challenges faced while adopting these technologies. This includes: write/read performance when dealing with vast amounts of data from heterogenous data sources with strict latency requirements; how to extract, transform and load >1 PB of data from CALS to NXCALS. NXCALS is not CERN-specific and can be relevant to other institutes facing similar challenges.

Poster WEPHA163 [1.689 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-WEPHA163

About •

paper received ※ 29 September 2019 paper accepted ※ 09 October 2019 issue date ※ 30 August 2020

Export •

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