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Recent Advancements in the DIII-D Plasma Control System

  • M. W. Margo
  • , H. Shen
  • , B. Penaflor
  • , B. Sammuli
  • , D. Piglowski
  • , D. Eldon
  • , J. Barr
  • , D. Orozco
  • , H. Anand
  • , A. Moser
  • , E. Cho
  • , T. Pederson
  • , J. Le
  • , C. Lasnier
  • , K. Erickson
  • , R. Reed

Research output: Contribution to journalArticlepeer-review

Abstract

The plasma control system (PCS) is a critical application required for daily operation of the DIII-D tokamak. Continuous expansion and upgrades to its hardware and software require a careful balance between the need to sustain high operations availability and the introduction of new real-time (RT) acquisition and control schemes. A number of new and improved diagnostics and controls have been added to the PCS. Expansion of the Upper Divertor Viewing (UDV) bolometer diagnostic now covers the tokamak upper divertor region and 8 new UDV channels have been added to the PCS data suite. To improve protection of the vessel, heat-flux and surface temperature control using real time infrared (IRTV) diagnostics have been successfully demonstrated. Neural network models have been added to the system to support experiments in disruption avoidance. In response to the increasing demand for software enhancements during operations, a testbed that closely mirrors the production hardware and software has been recently constructed and commissioned. It significantly increases the variety of testing that can be performed. Therefore, it is now possible to simultaneously operate DIII-D while validating new control algorithms for future experiments. In conjunction with an expansion of regular code reviews, the deployment of the testbed has resulted in greater reliability even with an increasing number and frequency of updates. Details of the specific hardware and software enhancements made along with improvements to testing and software quality assurance will be presented.

Original languageEnglish (US)
Pages (from-to)3535-3541
Number of pages7
JournalIEEE Transactions on Plasma Science
Volume52
Issue number9
DOIs
StatePublished - 2024

All Science Journal Classification (ASJC) codes

  • Nuclear and High Energy Physics
  • Condensed Matter Physics

Keywords

  • Algorithm development
  • machine learning
  • plasma control

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