TUA1WC —  WG-C   (19-Jun-18   08:30—10:30)
Chair: F.G. Garcia, Fermilab, Batavia, Illinois, USA
Paper Title Page
TUA1WC01 Installation and Commissioning of the Upgraded SARAF 4-rods RFQ -1
  • L. Weissman, D. Berkovits, B. Kaizer, J. Luner, D. Nusbaum, A. Perry, J. Rodnizki, A. Shor, I. Silverman
    Soreq NRC, Yavne, Israel
  • A. Bechtold
    NTG Neue Technologien GmbH & Co KG, Gelnhausen, Germany
  Acceleration of a 1mA Continuous Wave (CW) deuteron (A/Q=2) beam at SARAF has been accomplished for the first time. A 5.3 mA pulsed deuteron beam has been accelerated as well. These achievements cap a series of major modifications to the Radio Frequency Quadrupole (RFQ) 4-rods structure which included the incorporation of a new end flange, introduction of an additional RF power coupler and, most recently, installation of a new set of rod electrodes. The new rod modulation has been designed to enable deuteron beam acceleration at a lower inter-electrode voltage, to a slightly reduced final energy of 1.27 MeV/u and with stringent constraints on the extant of beam tails in the longitudinal phase space. This report will focus primarily on the installation and testing of the new rods. The successful conditioning campaign to 200 kW, ~10% above than the working point for deuteron operation, will be described. Beam commissioning with proton and deuteron beams will also be detailed. Results of beam measurements will be presented, including the characterization of the output beam in the transverse and longitudinal phase space. Finally, future possible improvements are discussed.  
slides icon Slides TUA1WC01 [12.606 MB]  
Recent Progress on the ESS Project  
  • M. Eshraqi
    ESS, Lund, Sweden
  The European Spallation Source, ESS, will be the world's brightest neutron source driven by the highest power linac, when it enters into operations. Different parts of the 5 MW ESS linac are being installed in Lund, Sweden and beam commissioning of the source is planned for early summer this year. This contribution will present a summary of the status of the project, including progress in the design, manufacturing and testing of different beam line components of the linac.  
slides icon Slides TUA1WC02 [3.422 MB]  
FRIB SRF Cryomodule Performance Testing and Status  
  • J.T. Popielarski, W. Chang, C. Compton, W. Hartung, S.H. Kim, S.J. Miller, L. Popielarski, K. Saito, S. Stark, T. Xu
    FRIB, East Lansing, Michigan, USA
  Funding: *Work supported by the U.S. Department of Energy Office of Science under Cooperative Agreement DE-SC0000661
Construction of a new accelerator for nuclear physics research, the Facility for Rare Isotope Beams (FRIB), is underway at Michigan State University (MSU). The FRIB linac will use superconducting resonators operating at a temperature of 2 K to accelerate ions to 200 MeV per nucleon. The linac requires 104 quarter wave resonators (0.085 MHz, β=0.041 and 0.085) and 220 half wave resonators (322 MHz, β= 0.29 and 0.53), all made from sheet Nb. Production resonators are being fabricated by cavity vendors; the resonators are etched, rinsed, and tested in MSU's certification test facility. Cavity certification testing is done before the installation of the high-power input coupler and tuner. After certification and cryomodule assembly, the resonators are tested in the cryomodule before installation into the FRIB tunnel. The cryomodule test goals are to verify integrated operation of the resonators, RF couplers, tuners, RF controls, and superconducting solenoids. To date, 22 out of 46 cryomodules have been completed, and 18 have been certified. Cavity and cryomodule certification test results are presented in this paper.
slides icon Slides TUA1WC03 [2.744 MB]  
Applications of Neural Networks to the Modeling and Control of Particle Accelerators  
  • A.L. Edelen
    CSU, Fort Collins, Colorado, USA
  Particle accelerators are host to myriad control challenges: they involve a multitude of interacting systems, are often subject to tight performance demands, in many cases exhibit nonlinear behavior, sometimes are not well-characterized due to practical and/or fundamental limitations, and should be able to run for extended periods of time with minimal interruption. One avenue toward improving the way these systems are controlled is to incorporate techniques from machine learning. Within machine learning, neural networks in particular are appealing because they are highly flexible, they are well-suited to problems with nonlinear behavior and large parameter spaces, and their recent success in other fields is an encouraging indicator that they are now technologically mature enough to be fruitfully applied to particle accelerators. This talk will highlight how machine learning in general can be applied to particle accelerator modeling and control by discussing several examples that were focused specifically on neural network-based approaches for several particle accelerator systems and subsystems.  
slides icon Slides TUA1WC04 [57.957 MB]