ICALEPCS2021 - List of Keywords (cavity)

Paper	Title	Other Keywords	Page
TUAL02	Development of a Single Cavity Regulation Based on microTCA.4 for SAPS-TP	controls, hardware, interface, FPGA	286
	W. Long, X. Li, S.H. Liu IHEP, Beijing, People’s Republic of China Y. Liu DNSC, Dongguan, People’s Republic of China
	A domestic hardware platform based on MTCA.4 is developed for a single cavity regulation in Southern Advanced Photon Source Test Platform (SAPS-TP). A multifunction digital processing Advanced Mezzanine Card (AMC) works as the core function module of the whole system, implement high speed data processing, Low-Level Radio Frequency (LLRF) control algorithm and interlock system. Its core data processing chip is a Xilinx ZYNQ SOC, which is embedded an ARM CPU to implement EPICS IOC under embedded Linux. A down-conversion and up-conversion RTM for cavity probes sensing and high power RF source driver can communi-cate with AMC module by a ZONE3 connector. A hosted tuning control FPGA Mezzanine Card (FMC) combines both the piezo controlling and step-motor controlling functions for independent external drive devices. The design of the hardware and software of the platform electronics and some test results are described in this paper. Further test and optimization is under way.
	Slides TUAL02 [10.504 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-TUAL02
About •	Received ※ 10 October 2021 Revised ※ 28 November 2021 Accepted ※ 22 December 2021 Issue date ※ 24 January 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUPV006	Control System of the SPIRAL2 Superconducting Linac Cryogenic System	controls, cryogenics, cryomodule, PLC	382
	A.H. Trudel, G. Duteil, A. Ghribi, Q. Tura GANIL, Caen, France P. Bonnay CEA/INAC, Grenoble Cedex 9, France
	The SPIRAL2 cryogenic system has been designed to cool down and maintain stable operation conditions of the 26 LINAC superconducting resonating cavities at a temperature of 4.5 K or lower. The control system of the cryogenic system of the LINAC is based on an architecture of 20 PLCs. Through an independent network, it drives the instrumentation, the cryogenic equipment, the 26 brushless motors of the frequency tuning system, interfaces the Epics Control System, and communicates process information to the Low Level Radio Frequency, vacuum, and magnet systems. Its functions are to ensure the safety of the cryogenic system, to efficiently control the cooldown of the 19 cryomodules, to enslave the frequency tuning system for the RF operation, and to monitor and analyze the data from the process. A model based Linear Quadratic regulation controls simultaneously both phase separators the liquid helium level and pressure. This control system also makes it possible to perform a number of virtual verification tests via a simulator and a dedicated PLC used to develop advanced model based control, such as a real time heat load estimator based on a Luenberger Filter
	Poster TUPV006 [2.393 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-TUPV006
About •	Received ※ 08 October 2021 Accepted ※ 23 February 2022 Issue date ※ 14 March 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUPV007	Motorized Regulation Systems for the SARAF Project	controls, PLC, feedback, cryomodule	387
	T.J. Joannem, F. Gohier, F. Gougnaud, P. Lotrus CEA-IRFU, Gif-sur-Yvette, France D. Darde CEA, DES-ISAS-DM2S, Université Paris-Saclay, Gif-sur-Yvette, France P. Guiho, A. Roger, N. Solenne CEA-DRF-IRFU, France
	CEA is in charge of the tuning regulation systems for the SARAF-Linac project. These tuning systems will be used with LLRF to regulate the 3 Rebuncher cavities and the HWR cavities of the 4 cryomodules. These systems were already tested on the Rebuncher and Equipped Cavity Test stands to test respectively the warm and cold tunings. This paper describes the hardware and software architectures. Both tuning systems are based on Siemens PLC and EPICS-PLC communication. Ambiant temperature technology is based on SIEMENS motor controller solution whereas the cold one combines Phytron and PhyMOTION solutions.
	Poster TUPV007 [0.892 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-TUPV007
About •	Received ※ 08 October 2021 Revised ※ 22 October 2021 Accepted ※ 05 February 2022 Issue date ※ 10 February 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUPV020	Automatic RF and Electron Gun Filament Conditioning Systems for 6 MeV LINAC	vacuum, electron, controls, gun	437
	A. Majid, D.A. Nawaz, N.U. Saqib, F. Sher PINSTECH, Islamabad, Pakistan
	RF conditioning of vacuum windows and RF cavities is a necessary task for eliminating poor vacuum caused by outgassing and contamination. Also, startup and shutdown process of linear accelerator requires gradual increase and decrease of electron gun filament voltage to avoid damage to the filament. This paper presents an EPICS based multi-loop automatic RF conditioning system and Electron Gun filament conditioning system for Klystron based 6 MeV Linear Accelerator.
	Poster TUPV020 [1.822 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-TUPV020
About •	Received ※ 10 October 2021 Revised ※ 17 October 2021 Accepted ※ 20 November 2021 Issue date ※ 26 December 2021
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPV021	Machine Learning for RF Breakdown Detection at CLARA	network, detector, gun, operation	681
	A.E. Pollard, D.J. Dunning, A.J. Gilfellon STFC/DL/ASTeC, Daresbury, Warrington, Cheshire, United Kingdom
	Maximising the accelerating gradient of RF structures is fundamental to improving accelerator facility performance and cost-effectiveness. Structures must be subjected to a conditioning process before operational use, in which the gradient is gradually increased up to the operating value. A limiting effect during this process is breakdown or vacuum arcing, which can cause damage that limits the ultimate operating gradient. Techniques to efficiently condition the cavities while minimising the number of breakdowns are therefore important. In this paper, machine learning techniques are applied to detect breakdown events in RF pulse traces by approaching the problem as anomaly detection, using a variational autoencoder. This process detects deviations from normal operation and classifies them with near perfect accuracy. Offline data from various sources has been used to develop the techniques, which we aim to test at the CLARA facility at Daresbury Laboratory. These techniques could then be applied generally.
	Poster WEPV021 [1.565 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-WEPV021
About •	Received ※ 09 October 2021 Accepted ※ 21 November 2021 Issue date ※ 24 November 2021
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPV025	Initial Studies of Cavity Fault Prediction at Jefferson Laboratory	cryomodule, SRF, electron, data-acquisition	700
	L.S. Vidyaratne, A. Carpenter, R. Suleiman, C. Tennant, D.L. Turner JLab, Newport News, Virginia, USA K.M. Iftekharuddin, M. Rahman ODU, Norfolk, Virginia, USA
	Funding: This work supported by the U.S. Department of Energy, Office of Science, Office of Nuclear Physics under Contract No. DE-AC05-06OR23177. The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Laboratory is a CW recirculating linac that utilizes over 400 superconducting radio-frequency (SRF) cavities to accelerate electrons up to 12 GeV through 5-passes. Recent work has shown that, given RF signals from a cavity during a fault as input, machine learning approaches can accurately classify the fault type. In this paper we report on initial results of predicting a fault onset using only data prior to the failure event. A data set was constructed using time-series data immediately before a fault (’unstable’) and 1.5 seconds prior to a fault (’stable’) gathered from over 5,000 saved fault events. The data was used to train a binary classifier. The results gave key insights into the behavior of several fault types and provided motivation to investigate whether data prior to a failure event could also predict the type of fault. We discuss our method using a sliding window approach and report on initial results. Recent modifications to the low-level RF control system will provide access to streaming signals and we outline a path forward for leveraging deep learning on streaming data
	Poster WEPV025 [1.111 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-WEPV025
About •	Received ※ 08 October 2021 Revised ※ 19 October 2021 Accepted ※ 11 February 2022 Issue date ※ 05 March 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPV031	Status of the uTCA Digital LLRF design for SARAF Phase II	LLRF, controls, FPGA, interface	720
	J. Fernández, P. Gil, J.G. Ramirez 7S, Peligros (Granada), Spain G. Desmarchelier CEA-DRF-IRFU, France G. Ferrand, F. Gohier, N. Pichoff CEA-IRFU, Gif-sur-Yvette, France
	One of the crucial control systems of any particle ac-celerator is the Low-Level Radio Frequency (LLRF). The purpose of a LLRF is to control the amplitude and phase of the field inside the accelerating cavity. The LLRF is a subsystem of the CEA (Commissariat à l’Energie Atomique) control domain for the SARAF-LINAC (Soreq Applied Research Accelerator Facility ’ Linear Accelera-tor) instrumentation and Seven Solutions has designed, developed, manufactured, and tested the system based on CEA technical specifications. The final version of this digital LLRF will be installed in the SARAF accelerator in Israel at the end of 2021. The architecture, design, and development as well as the performance of the LLRF system will be presented in this paper. The benefits of the proposed architecture and the first results will be shown.
	Poster WEPV031 [2.607 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-WEPV031
About •	Received ※ 08 October 2021 Revised ※ 19 October 2021 Accepted ※ 12 December 2021 Issue date ※ 25 February 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THBR02	White Rabbit and MTCA.4 Use in the LLRF Upgrade for CERN’s SPS	LLRF, controls, FPGA, network	847
	T. Włostowski, K. Adrianek, M. Arruat, P. Baudrenghien, A.C. Butterworth, G. Daniluk, J. Egli, J.R. Gill, T. Gingold, J.D. González Cobas, G. Hagmann, P. Kuzmanović, D. Lampridis, M.M. Lipiński, S. Novel González, J.P. Palluel, M. Rizzi, A. Spierer, M. Sumiński, A. Wujek CERN, Geneva, Switzerland
	The Super Proton Synchrotron (SPS) Low-level RF (LLRF) system at CERN was completely revamped in 2020. In the old system, the digital signal processing was clocked by a submultiple of the RF. The new system uses a fixed-frequency clock derived from White Rabbit (WR). This triggered the development of an eRTM module for generating very precise clock signals to be fed to the optional RF backplane in MTCA.4 crates. The eRTM14/15 sandwich of modules implements a WR node delivering clock signals with a jitter below 100 fs. WR-clocked RF synthesis inside the FPGA makes it simple to reproduce the RF elsewhere by broadcasting the frequency-tuning words over the WR network itself. These words are received by the WR2RF-VME module and used to produce beam-synchronous signals such as the bunch clock and the revolution tick. This paper explains the general architecture of this new LLRF system, highlighting the role of WR-based synchronization. It then goes on to describe the hardware and gateware designs for both modules, along with their supporting software. A recount of our experience with the deployment of the MTCA.4 platform is also provided.
	Slides THBR02 [0.981 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-THBR02
About •	Received ※ 12 October 2021 Revised ※ 24 October 2021 Accepted ※ 03 January 2022 Issue date ※ 28 February 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THPV043	Using AI for Management of Field Emission in SRF Linacs	radiation, operation, detector, linac	970
	A. Carpenter, P. Degtiarenko, R. Suleiman, C. Tennant, D.L. Turner, L.S. Vidyaratne JLab, Newport News, Virginia, USA K.M. Iftekharuddin, M. Rahman ODU, Norfolk, Virginia, USA
	Funding: This work supported by the U.S. Department of Energy, Office of Science, Office of Nuclear Physics under Contract No. DE-AC05-06OR23177. Field emission control, mitigation, and reduction is critical for reliable operation of high gradient superconducting radio-frequency (SRF) accelerators. With the SRF cavities at high gradients, the field emission of electrons from cavity walls can occur and will impact the operational gradient, radiological environment via activated components, and reliability of CEBAF’s two linacs. A new effort has started to minimize field emission in the CEBAF linacs by re-distributing cavity gradients. To measure radiation levels, newly designed neutron and gamma radiation dose rate monitors have been installed in both linacs. Artificial intelligence (AI) techniques will be used to identify cavities with high levels of field emission based on control system data such as radiation levels, cryogenic readbacks, and vacuum loads. The gradients on the most offending cavities will be reduced and compensated for by increasing the gradients on least offensive cavities. Training data will be collected during this year’s operational program and initial implementation of AI models will be deployed. Preliminary results and future plans are presented.
	Poster THPV043 [1.857 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-THPV043
About •	Received ※ 08 October 2021 Revised ※ 21 October 2021 Accepted ※ 21 November 2021 Issue date ※ 14 December 2021
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Other Keywords

Page

TUAL02

Development of a Single Cavity Regulation Based on microTCA.4 for SAPS-TP

controls, hardware, interface, FPGA

286

W. Long, X. Li, S.H. Liu
IHEP, Beijing, People’s Republic of China
Y. Liu
DNSC, Dongguan, People’s Republic of China

A domestic hardware platform based on MTCA.4 is developed for a single cavity regulation in Southern Advanced Photon Source Test Platform (SAPS-TP). A multifunction digital processing Advanced Mezzanine Card (AMC) works as the core function module of the whole system, implement high speed data processing, Low-Level Radio Frequency (LLRF) control algorithm and interlock system. Its core data processing chip is a Xilinx ZYNQ SOC, which is embedded an ARM CPU to implement EPICS IOC under embedded Linux. A down-conversion and up-conversion RTM for cavity probes sensing and high power RF source driver can communi-cate with AMC module by a ZONE3 connector. A hosted tuning control FPGA Mezzanine Card (FMC) combines both the piezo controlling and step-motor controlling functions for independent external drive devices. The design of the hardware and software of the platform electronics and some test results are described in this paper. Further test and optimization is under way.

Slides TUAL02 [10.504 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-TUAL02

About •

Received ※ 10 October 2021 Revised ※ 28 November 2021 Accepted ※ 22 December 2021 Issue date ※ 24 January 2022

Cite •

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

TUPV006

Control System of the SPIRAL2 Superconducting Linac Cryogenic System

controls, cryogenics, cryomodule, PLC

382

A.H. Trudel, G. Duteil, A. Ghribi, Q. Tura
GANIL, Caen, France
P. Bonnay
CEA/INAC, Grenoble Cedex 9, France

The SPIRAL2 cryogenic system has been designed to cool down and maintain stable operation conditions of the 26 LINAC superconducting resonating cavities at a temperature of 4.5 K or lower. The control system of the cryogenic system of the LINAC is based on an architecture of 20 PLCs. Through an independent network, it drives the instrumentation, the cryogenic equipment, the 26 brushless motors of the frequency tuning system, interfaces the Epics Control System, and communicates process information to the Low Level Radio Frequency, vacuum, and magnet systems. Its functions are to ensure the safety of the cryogenic system, to efficiently control the cooldown of the 19 cryomodules, to enslave the frequency tuning system for the RF operation, and to monitor and analyze the data from the process. A model based Linear Quadratic regulation controls simultaneously both phase separators the liquid helium level and pressure. This control system also makes it possible to perform a number of virtual verification tests via a simulator and a dedicated PLC used to develop advanced model based control, such as a real time heat load estimator based on a Luenberger Filter

Poster TUPV006 [2.393 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-TUPV006

About •

Received ※ 08 October 2021 Accepted ※ 23 February 2022 Issue date ※ 14 March 2022

Cite •

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

TUPV007

Motorized Regulation Systems for the SARAF Project

controls, PLC, feedback, cryomodule

387

T.J. Joannem, F. Gohier, F. Gougnaud, P. Lotrus
CEA-IRFU, Gif-sur-Yvette, France
D. Darde
CEA, DES-ISAS-DM2S, Université Paris-Saclay, Gif-sur-Yvette, France
P. Guiho, A. Roger, N. Solenne
CEA-DRF-IRFU, France

CEA is in charge of the tuning regulation systems for the SARAF-Linac project. These tuning systems will be used with LLRF to regulate the 3 Rebuncher cavities and the HWR cavities of the 4 cryomodules. These systems were already tested on the Rebuncher and Equipped Cavity Test stands to test respectively the warm and cold tunings. This paper describes the hardware and software architectures. Both tuning systems are based on Siemens PLC and EPICS-PLC communication. Ambiant temperature technology is based on SIEMENS motor controller solution whereas the cold one combines Phytron and PhyMOTION solutions.

Poster TUPV007 [0.892 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-TUPV007

About •

Received ※ 08 October 2021 Revised ※ 22 October 2021 Accepted ※ 05 February 2022 Issue date ※ 10 February 2022

Cite •

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

TUPV020

Automatic RF and Electron Gun Filament Conditioning Systems for 6 MeV LINAC

vacuum, electron, controls, gun

437

A. Majid, D.A. Nawaz, N.U. Saqib, F. Sher
PINSTECH, Islamabad, Pakistan

RF conditioning of vacuum windows and RF cavities is a necessary task for eliminating poor vacuum caused by outgassing and contamination. Also, startup and shutdown process of linear accelerator requires gradual increase and decrease of electron gun filament voltage to avoid damage to the filament. This paper presents an EPICS based multi-loop automatic RF conditioning system and Electron Gun filament conditioning system for Klystron based 6 MeV Linear Accelerator.

Poster TUPV020 [1.822 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-TUPV020

About •

Received ※ 10 October 2021 Revised ※ 17 October 2021 Accepted ※ 20 November 2021 Issue date ※ 26 December 2021

Cite •

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

WEPV021

Machine Learning for RF Breakdown Detection at CLARA

network, detector, gun, operation

681

A.E. Pollard, D.J. Dunning, A.J. Gilfellon
STFC/DL/ASTeC, Daresbury, Warrington, Cheshire, United Kingdom

Maximising the accelerating gradient of RF structures is fundamental to improving accelerator facility performance and cost-effectiveness. Structures must be subjected to a conditioning process before operational use, in which the gradient is gradually increased up to the operating value. A limiting effect during this process is breakdown or vacuum arcing, which can cause damage that limits the ultimate operating gradient. Techniques to efficiently condition the cavities while minimising the number of breakdowns are therefore important. In this paper, machine learning techniques are applied to detect breakdown events in RF pulse traces by approaching the problem as anomaly detection, using a variational autoencoder. This process detects deviations from normal operation and classifies them with near perfect accuracy. Offline data from various sources has been used to develop the techniques, which we aim to test at the CLARA facility at Daresbury Laboratory. These techniques could then be applied generally.

Poster WEPV021 [1.565 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-WEPV021

About •

Received ※ 09 October 2021 Accepted ※ 21 November 2021 Issue date ※ 24 November 2021

Cite •

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

WEPV025

Initial Studies of Cavity Fault Prediction at Jefferson Laboratory

cryomodule, SRF, electron, data-acquisition

700

L.S. Vidyaratne, A. Carpenter, R. Suleiman, C. Tennant, D.L. Turner
JLab, Newport News, Virginia, USA
K.M. Iftekharuddin, M. Rahman
ODU, Norfolk, Virginia, USA

Funding: This work supported by the U.S. Department of Energy, Office of Science, Office of Nuclear Physics under Contract No. DE-AC05-06OR23177.
The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Laboratory is a CW recirculating linac that utilizes over 400 superconducting radio-frequency (SRF) cavities to accelerate electrons up to 12 GeV through 5-passes. Recent work has shown that, given RF signals from a cavity during a fault as input, machine learning approaches can accurately classify the fault type. In this paper we report on initial results of predicting a fault onset using only data prior to the failure event. A data set was constructed using time-series data immediately before a fault (’unstable’) and 1.5 seconds prior to a fault (’stable’) gathered from over 5,000 saved fault events. The data was used to train a binary classifier. The results gave key insights into the behavior of several fault types and provided motivation to investigate whether data prior to a failure event could also predict the type of fault. We discuss our method using a sliding window approach and report on initial results. Recent modifications to the low-level RF control system will provide access to streaming signals and we outline a path forward for leveraging deep learning on streaming data

Poster WEPV025 [1.111 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-WEPV025

About •

Received ※ 08 October 2021 Revised ※ 19 October 2021 Accepted ※ 11 February 2022 Issue date ※ 05 March 2022

Cite •

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

WEPV031

Status of the uTCA Digital LLRF design for SARAF Phase II

LLRF, controls, FPGA, interface

720

J. Fernández, P. Gil, J.G. Ramirez
7S, Peligros (Granada), Spain
G. Desmarchelier
CEA-DRF-IRFU, France
G. Ferrand, F. Gohier, N. Pichoff
CEA-IRFU, Gif-sur-Yvette, France

One of the crucial control systems of any particle ac-celerator is the Low-Level Radio Frequency (LLRF). The purpose of a LLRF is to control the amplitude and phase of the field inside the accelerating cavity. The LLRF is a subsystem of the CEA (Commissariat à l’Energie Atomique) control domain for the SARAF-LINAC (Soreq Applied Research Accelerator Facility ’ Linear Accelera-tor) instrumentation and Seven Solutions has designed, developed, manufactured, and tested the system based on CEA technical specifications. The final version of this digital LLRF will be installed in the SARAF accelerator in Israel at the end of 2021. The architecture, design, and development as well as the performance of the LLRF system will be presented in this paper. The benefits of the proposed architecture and the first results will be shown.

Poster WEPV031 [2.607 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-WEPV031

About •

Received ※ 08 October 2021 Revised ※ 19 October 2021 Accepted ※ 12 December 2021 Issue date ※ 25 February 2022

Cite •

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

THBR02

White Rabbit and MTCA.4 Use in the LLRF Upgrade for CERN’s SPS

LLRF, controls, FPGA, network

847

T. Włostowski, K. Adrianek, M. Arruat, P. Baudrenghien, A.C. Butterworth, G. Daniluk, J. Egli, J.R. Gill, T. Gingold, J.D. González Cobas, G. Hagmann, P. Kuzmanović, D. Lampridis, M.M. Lipiński, S. Novel González, J.P. Palluel, M. Rizzi, A. Spierer, M. Sumiński, A. Wujek
CERN, Geneva, Switzerland

The Super Proton Synchrotron (SPS) Low-level RF (LLRF) system at CERN was completely revamped in 2020. In the old system, the digital signal processing was clocked by a submultiple of the RF. The new system uses a fixed-frequency clock derived from White Rabbit (WR). This triggered the development of an eRTM module for generating very precise clock signals to be fed to the optional RF backplane in MTCA.4 crates. The eRTM14/15 sandwich of modules implements a WR node delivering clock signals with a jitter below 100 fs. WR-clocked RF synthesis inside the FPGA makes it simple to reproduce the RF elsewhere by broadcasting the frequency-tuning words over the WR network itself. These words are received by the WR2RF-VME module and used to produce beam-synchronous signals such as the bunch clock and the revolution tick. This paper explains the general architecture of this new LLRF system, highlighting the role of WR-based synchronization. It then goes on to describe the hardware and gateware designs for both modules, along with their supporting software. A recount of our experience with the deployment of the MTCA.4 platform is also provided.

Slides THBR02 [0.981 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-THBR02

About •

Received ※ 12 October 2021 Revised ※ 24 October 2021 Accepted ※ 03 January 2022 Issue date ※ 28 February 2022

Cite •

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

THPV043

Using AI for Management of Field Emission in SRF Linacs

radiation, operation, detector, linac

970

A. Carpenter, P. Degtiarenko, R. Suleiman, C. Tennant, D.L. Turner, L.S. Vidyaratne
JLab, Newport News, Virginia, USA
K.M. Iftekharuddin, M. Rahman
ODU, Norfolk, Virginia, USA

Funding: This work supported by the U.S. Department of Energy, Office of Science, Office of Nuclear Physics under Contract No. DE-AC05-06OR23177.
Field emission control, mitigation, and reduction is critical for reliable operation of high gradient superconducting radio-frequency (SRF) accelerators. With the SRF cavities at high gradients, the field emission of electrons from cavity walls can occur and will impact the operational gradient, radiological environment via activated components, and reliability of CEBAF’s two linacs. A new effort has started to minimize field emission in the CEBAF linacs by re-distributing cavity gradients. To measure radiation levels, newly designed neutron and gamma radiation dose rate monitors have been installed in both linacs. Artificial intelligence (AI) techniques will be used to identify cavities with high levels of field emission based on control system data such as radiation levels, cryogenic readbacks, and vacuum loads. The gradients on the most offending cavities will be reduced and compensated for by increasing the gradients on least offensive cavities. Training data will be collected during this year’s operational program and initial implementation of AI models will be deployed. Preliminary results and future plans are presented.

Poster THPV043 [1.857 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-THPV043

About •

Received ※ 08 October 2021 Revised ※ 21 October 2021 Accepted ※ 21 November 2021 Issue date ※ 14 December 2021

Cite •

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