Artifical intelligence techniques for tuning linear induction accelerators

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We developed an expert system that acts as an intelligent assistant for tuning particle beam generators called MAESTRO, Model and Expert System Resource for Operators. MAESTRO maintains a knowledge base of the accelerator containing not only the interconnections of the beamline components, but also their physical attributes such as measured magnetic tilts, offsets, and field profiles. MAESTRO incorporates particle trajectory and beam envelope models which are coupled to the knowledge base permitting large numbers of real-time orbit and envelope calculations in the control-room environment. To date we have used this capability in three ways: First, to implement a tuning algorithm ... continued below

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Lager, D.; Brand, H.; Chambers, F.; Coffield, F.; Maurer, W. & Turner, W. May 1, 1991.

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Description

We developed an expert system that acts as an intelligent assistant for tuning particle beam generators called MAESTRO, Model and Expert System Resource for Operators. MAESTRO maintains a knowledge base of the accelerator containing not only the interconnections of the beamline components, but also their physical attributes such as measured magnetic tilts, offsets, and field profiles. MAESTRO incorporates particle trajectory and beam envelope models which are coupled to the knowledge base permitting large numbers of real-time orbit and envelope calculations in the control-room environment. To date we have used this capability in three ways: First, to implement a tuning algorithm for minimizing transverse beam motion. Second, to produce a beam waist with arbitrary radius at the entrance to a brightness diagnostic. And finally, to measure beam energy along the accelerator by fitting orbits to focusing and steering sweeps.

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5 p.; Other: FDE: PDF; PL:

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OSTI as DE98052024

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  • 1991 Institute of Electrical and Electronics Engineers (IEEE) particle accelerator conference (PAC), San Francisco, CA (United States), 6-11 May 1991

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  • Other: DE98052024
  • Report No.: UCRL-JC--105674
  • Report No.: CONF-910505--
  • Grant Number: W-7405-ENG-48
  • Office of Scientific & Technical Information Report Number: 645319
  • Archival Resource Key: ark:/67531/metadc698236

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  • May 1, 1991

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  • Aug. 14, 2015, 8:43 a.m.

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  • April 21, 2016, 9:35 p.m.

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Lager, D.; Brand, H.; Chambers, F.; Coffield, F.; Maurer, W. & Turner, W. Artifical intelligence techniques for tuning linear induction accelerators, article, May 1, 1991; California. (digital.library.unt.edu/ark:/67531/metadc698236/: accessed August 16, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.