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2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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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.
R. D. Lawrence, J. J. Dorning
Nuclear Science and Engineering | Volume 64 | Number 2 | October 1977 | Pages 492-507
Technical Paper | doi.org/10.13182/NSE77-A27385
Articles are hosted by Taylor and Francis Online.
A smoothing and extrapolation method is applied to the point kinetics equations and the one-dimensional space-dependent reactor kinetics equations. The simple smoothing procedure is shown to be very efficient in reducing the oscillatory errors that occur when the standard Padé(1,1) and Crank-Nicholson approximations are applied to stiff reactor kinetics equations. Fourth-order accuracy is achieved by applying a single Richardson extrapolation (on a global basis) to the smoothed results obtained from values calculated using two time-step grids. The numerical results for point kinetics demonstrate that the method is particularly efficient for very stiff problems such as subcritical and delayed supercritical transients in fast reactors. Application of the method to two one-dimensional kinetics benchmark problems solved using a standard space-dependent computer code that utilizes the Crank-Nicholson approximation leads to significant reduction in the overall computational effort required to achieve a given accuracy.