Author: Madden, T.J.
Paper Title Page
MOPAB046 Plan for Operating the APS-Upgrade Booster with a Frequency Sweep 201
 
  • J.R. Calvey, T.G. Berenc, A.R. Brill, L. Emery, T. Fors, K.C. Harkay, T.J. Madden, N. Sereno, U. Wienands
    ANL, Lemont, Illinois, USA
  • A. Gu
    UCB, Berkeley, California, USA
 
  The APS-Upgrade presents several challenging demands to the booster synchrotron. Swap-out injection requires the booster to capture a high charge bunch (up to 17 nC), accelerate it to 6 GeV, and maintain a low emittance at extraction for injection into the storage ring. To accommodate these conflicting demands, the RF frequency will be ramped between injection and extraction. However, the RF cavity tuners will remain static, which means the couplers will need to withstand a high reflected power at extraction. This paper presents a plan for a system that will meet the requirements for injection efficiency, extracted emittance, and equivalent power at the coupler. Results from tracking simulations and beam studies with a frequency ramp will also be shown.  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-MOPAB046  
About • paper received ※ 28 May 2021       paper accepted ※ 02 June 2021       issue date ※ 26 August 2021  
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TUPAB354 352-MHz Solid State RF System Development at the Advanced Photon Source 2335
 
  • D. Horan, D.J. Bromberek, N.P. DiMonte, A. Goel, T.J. Madden, A. Nassiri, G. Trento, G.J. Waldschmidt
    ANL, Lemont, Illinois, USA
 
  Development effort is underway on a 352MHz, 200kW solid state rf system intended as the base design to replace the existing klystron-based rf systems presently in use at the Advanced Photon Source (APS). A sixteen-input, 200kW final combining cavity was designed, built, and successfully tested to 29kW CW in combiner mode, and to 200kW CW in back-feed mode, where an external klystron was used to transmit power into the combining cavity. A four-port waveguide combiner was also tested in both backfeed and combiner mode to 193kW and 26kW respectively. Slow and fast interlock systems were designed and implemented to support the testing process. An EPICS and Programmable Logic Controller (PLC)-based system was developed to control, communicate with, and monitor the rf amplifiers used in the combiner-mode test, and to monitor and log system performance parameters relating to the combining cavity. Low-level rf control of the cavity in 29kW combiner-mode operation was achieved using the existing APS analog low-level rf hardware. Test data and design details are presented.  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-TUPAB354  
About • paper received ※ 18 May 2021       paper accepted ※ 31 May 2021       issue date ※ 19 August 2021  
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WEPAB323 High Performance DAQ Infrastructure to Enable Machine Learning for the Advanced Photon Source Upgrade 3434
 
  • G. Shen, N.D. Arnold, T.G. Berenc, J. Carwardine, E. Chandler, T. Fors, T.J. Madden, D.R. Paskvan, C. Roehrig, S.E. Shoaf, S. Veseli
    ANL, Lemont, Illinois, USA
 
  Funding: Argonne National Laboratory’s work was supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under contract DE-AC02-06CH11357.
It is well known that the efficiency of an advanced control algorithm like machine learning is as good as its data quality. Much recent progress in technology enables the massive data acquisition from a control system of modern particle accelerator, and the wide use of embedded controllers, like field-programmable gate arrays (FPGA), provides an opportunity to collect fast data from technical subsystems for monitoring, statistics, diagnostics or fault recording. To improve the data quality, at the APS Upgrade project, a general-purpose data acquisition (DAQ) system is under active development. The APS-U DAQ system collects high-quality fast data from underneath embedded controllers, especially the FPGAs, with the manner of time-correlation and synchronously sampling, which could be used for commissioning, performance monitoring, troubleshooting, and early fault detection, etc. This paper presents the design and latest progress of APS-U high-performance DAQ infrastructure, as well as its preparation to enable the use of machine learning technology for APS-U, and its use cases at APS.
 
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-WEPAB323  
About • paper received ※ 19 May 2021       paper accepted ※ 24 June 2021       issue date ※ 29 August 2021  
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