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2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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Fusion Science and Technology
Latest News
Princeton-led team develops AI for fusion plasma monitoring
A new AI software tool for monitoring and controlling the plasma inside nuclear fuel systems has been developed by an international collaboration of scientists from Princeton University, Princeton Plasma Physics Laboratory (PPPL), Chung-Ang University, Columbia University, and Seoul National University. The software, which the researchers call Diag2Diag, is described in the paper, “Multimodal super-resolution: discovering hidden physics and its application to fusion plasmas,” published in Nature Communications.
H. Okuda
Nuclear Science and Engineering | Volume 64 | Number 1 | September 1977 | Pages 41-48
Technical Paper | doi.org/10.13182/NSE77-A27075
Articles are hosted by Taylor and Francis Online.
Plasma simulation models that use particles and that have been developed for studying the microscopic behavior of a confined plasma in a magnetic field are described. The first model is developed to investigate the anomalous diffusion of particles and energy due to low-frequency electrostatic microinstabilities in cylindrical and toroidal systems. The model makes use of the combination of eigenfunction expansion in one direction and the multipole expansion on a two-dimensional spatial grid for solving Maxwell's equations and for pushing particles. The second model is developed to study the neutral-beam injection heating of a tokamak plasma, taking into account the spatial variation of plasma parameters and the finite ion-beam banana orbit. The self-consistent electric and magnetic fields are totally ignored in this model, and the Fokker-Planck collisions on the beam ions due to background ions and electrons are built in through the Monte Carlo method.