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

A.L. Edelen (Colorado State U.) S.G. Biedron (Colorado State U.; B.E. Chase; J.P. Edelen; J. Steimel (Fermilab); Ljubljana U.) S.V. Milton (Colorado State U.) D. Bowring

arxiv: 1612.07237 · v1 · pith:O5OXI7FZnew · submitted 2016-12-21 · ⚛️ physics.acc-ph

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

A.L. Edelen (Colorado State U.) S.G. Biedron (Colorado State U. , Ljubljana U.) S.V. Milton (Colorado State U.) D. Bowring , B.E. Chase , J.P. Edelen , J. Steimel (Fermilab) This is my paper

classification ⚛️ physics.acc-ph

keywords frequencymodelnetworkneuralresonantsystemcoolingpxie

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As part of the PIP-II Injector Experiment (PXIE) accelerator, 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.

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

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