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Conference Spotlight
2026 ANS Winter Conference & Expo
November 15–18, 2026
Phoenix, AZ|Arizona Grand Resort & Spa
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Nuclear Science and Engineering
October 2026
Nuclear Technology
Fusion Science and Technology
Latest News
PPPL develops framework for unifying tokamak ML control models
Princeton Plasma Physics Laboratory announced that researchers at the lab, in collaboration with Princeton University, have developed a general algorithm for prediction and control in tokamak systems and have tested it at DIII-D, as presented in a recent Nuclear Fusion paper.
According to the paper, most machine learning (ML)–based tools for use in fusion machines have been implemented as stand-alone demonstrations, aiming to predict the plasma profile, suppress a form of instability, for example. PPPL’s project provides a framework that aims to accommodate these disparate models into an integrated system, which the team calls PACMAN (Prediction and Control Using Machine Learning).
Technical Session|Sponsored by RPSD
Tuesday, June 15, 2021|2:15–4:00PM EDT
Session Chair:
Andrew Rosenstrom
Alternate Chair:
Lucas M. Rolison
Session Organizer:
Amir A. Bahadori
Staff Producer:
Julie Bry (ANS)
To access the session recording, you must be logged in and registered for the meeting.
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KSU TRIGA Mark II Nuclear Reactor MCNP6 Model Improvements for Cell Irradiation Facility Design
Eric Giunta (Kansas State Univ.), Rabab Elzohery (Kansas State Univ.), Angela Gearhardt (Kansas State Univ.), John C. Boyington (Kansas State Univ.), Alan T. Cebula (Kansas State Univ.), Jeremy Roberts (Kansas State Univ.), Amir A. Bahadori (Kansas State Univ.)
Paper
Breakdown of Assumptions for 1D Radiation Transport in Air: Effects from Ground
L. M. Rolison (LANL), M. L. Fensin (LANL)
Variance Reduction Complications when Computing an Energy Dependent Dose Response in a Single Calculation
M. L. Fensin (LANL)
