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Going Nuclear: Notes from the officially unofficial book tour
I work in the analytical labs at one of Europe’s oldest and largest nuclear sites: Sellafield, in northwestern England. I spend my days at the fume hood front, pipette in one hand and radiation probe in the other (and dosimeter pinned to my chest, of course). Outside the lab, I have a second job: I moonlight as a writer and public speaker. My new popular science book—Going Nuclear: How the Atom Will Save the World—came out last summer, and it feels like my life has been running at full power ever since.
Han Gon Kim, Soon Heung Chang, Byung Ho Lee
Nuclear Science and Engineering | Volume 115 | Number 2 | October 1993 | Pages 152-163
Technical Paper | doi.org/10.13182/NSE93-A28525
Articles are hosted by Taylor and Francis Online.
The Optimal Fuel Shuffling System (OFSS) was developed for the optimal design of pressurized water reactor (PWR) fuel loading patterns. An optimal loading pattern is defined in which the local power peaking factor is lower than a predetermined value during one cycle and the effective multiplication factor is maximized to extract the maximum energy. The OFSS is a hybrid system in which a rule-based system, fuzzy logic, and an artificial neural network (ANN) are connected with each other. The rule-based system classifies loading patterns into two types by using several heuristic rules and a fuzzy rule. The fuzzy rule is introduced to achieve a more effective and faster search. Its membership function is automatically updated in accordance with the prediction results. The ANN predicts core parameters for the patterns generated from the rule-based system. A backpropagation network is used for fast prediction of the core parameters. The ANN and fuzzy logic can be used to improve the capabilities of existing algorithms. The OFSS was demonstrated and validated for cycle 1 of theKori-1 PWR.