Neural Network Model Of The PXIE RFQ Cooling System and Resonant Frequency Response

Conference · Wed Jun 01 00:00:00 EDT 2016

DOI:https://doi.org/10.18429/JACoW-IPAC2016-THPOY020· OSTI ID:1339127

Edelen, Auralee ^[1]; Biedron, Sandra ^[2]; Bowring, Daniel ^[1]; Chase, Brian ^[1]; Edelen, Jonathan ^[1]; Milton, Stephen ^[2]; Steimel, Jim ^[1]

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1. Fermilab
2. Colorado State U., Fort Collins

As part of the PIP-II Injector Experiment (PXIE) accel-erator, a four-vane radio frequency quadrupole (RFQ) accelerates a 30-keV, 1-mA to 10-mA H' ion beam to 2.1 MeV. It is designed to operate at a frequency of 162.5 MHz with arbitrary duty factor, including continuous wave (CW) mode. The resonant frequency is controlled solely by a water-cooling system. We present an initial neural network model of the RFQ frequency response to changes in the cooling system and RF power conditions during pulsed operation. A neural network model will be used in a model predictive control scheme to regulate the resonant frequency of the RFQ.

• Research Organization: Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
• Sponsoring Organization: USDOE Office of Science (SC), High Energy Physics (HEP)
• DOE Contract Number: AC02-07CH11359
• OSTI ID: 1339127
• Report Number(s): FERMILAB-CONF-16-603-AD; arXiv:1612.07237; 1505489
• Resource Relation: Conference: 7th International Particle Accelerator Conference, Busan, Korea, 05/08-05/13/2016
• Country of Publication: United States
• Language: English

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43 PARTICLE ACCELERATORS