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Conference Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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Chris Wagner: The role of Eden Radioisotopes in the future of nuclear medicine
Chris Wagner has more than 40 years of experience in nuclear medicine, beginning as a clinical practitioner before moving into leadership roles at companies like Mallinckrodt (now Curium) and Nordion. His knowledge of both the clinical and the manufacturing sides of nuclear medicine laid the groundwork for helping to found Eden Radioisotopes, a start-up venture that intends to make diagnostic and therapeutic raw material medical isotopes like molybdenum-99 and lutetium-177.
Juan Jose Ortiz, Ignacio Requena
Nuclear Science and Engineering | Volume 143 | Number 3 | March 2003 | Pages 254-267
Technical Paper | doi.org/10.13182/NSE03-A2334
Articles are hosted by Taylor and Francis Online.
The problem of optimizing refueling in a nuclear boiling water reactor is difficult since it concerns combinatorial optimization and it is NP-Complete. In order to solve this problem, many techniques have been applied, ranging from expert systems to genetic algorithms. In most of these procedures, nuclear reactor simulators are used, which require a longer computation time, to evaluate the goodness of the proposed solutions. As the processes are iterative, many evaluations with the simulator are necessary, and this makes the process extremely slow. In this paper, the use of trained neural networks (NNs) is proposed as an alternative to the simulator, and the results of the NN training are shown in order to predict some variables of interest in the optimization, such as the effective multiplication factor and some thermal limits, related to safety aspects. Finally, a study about the effect of modifying several NN parameters is shown.