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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.
W. Ciechanowicz
Nuclear Science and Engineering | Volume 57 | Number 1 | May 1975 | Pages 39-52
Technical Paper | doi.org/10.13182/NSE75-A40341
Articles are hosted by Taylor and Francis Online.
The aim of the paper is to show how the complex, overall burnup optimization problem, t subject to the constraint of the desired power distribution, can be solved by decomposition into less complex coordinated subproblems. The solution has been obtained by use of the multilevel approach. The advantage of this approach is that it makes the computer solution of the problem of optimization practical. Two decomposition structures are considered: one for discrete and one for continuous reactor refueling. In the second case we deal with the optimization problem subject to the constraint in a form of an inequality containing a differentiable operator. To solve this problem the generalized Kuhn-Tucker theorem is used. To determine the optimum control of the desired power distribution, the Kulikowski approach is applied. As a result, the cyclic optimization process for both structures is obtained in which the information is exchanged between suitable level controllers.