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Framatome signs contracts with Sizewell C
French nuclear developer Framatome is slated to deliver key equipment for Sizewell C Ltd.’s two large reactors planned for the United Kingdom’s Suffolk coast.
The agreement, reportedly worth multiple billions of euros, was announced this week and will involve Framatome from the design phase until commissioning. The company also agreed to a long-term fuel supply deal. Framatome is 80.5 percent owned by France’s EDF and 19.5 percent owned by Mitsubishi Heavy Industries.
Akio Yamamoto
Nuclear Technology | Volume 144 | Number 1 | October 2003 | Pages 63-75
Technical Paper | Nuclear Plant Operations and Control | doi.org/10.13182/NT03-A3429
Articles are hosted by Taylor and Francis Online.
In this paper, neural networks are used to predict core characteristics, and the predicted results are used to screen poor loading patterns in order to improve optimization efficiency. The radial peaking factor, cycle length, and maximum burnup through the cycle depletion calculations were evaluated by the neural network, and these core characteristics were used for screening. The screened loading patterns were evaluated by the core calculation code as ordinary in-core optimizations. The calculation results of the test problem indicated that the loading pattern screening using the neural network effectively improves the optimization results. Since the computation time for a cycle depletion calculation with the neural network is quite short, the computation load for the screening is negligible. Since the neural network is periodically retrained using the latest evaluation results of the core calculation code, its prediction accuracy is continuously improved during the optimization. The typical prediction accuracies of the radial peaking factor, cycle length, and maximum burnup in the latter part of the optimizations were 3 to 4%, 0.01 to 0.02 GWd/t, and 0.2 GWd/t, respectively, in the test problem. These accuracies are satisfactory for loading pattern screening.