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The present paper illustrates the use of artificial neural networks for computing the maximum fuel cladding temperature reached during a complete group distribution blockage scenario in an RBMK-1500 nuclear reactor. The uncertainties associated to the neural predictions are quantified by resorting to the bootstrap technique. The trained neural networks are further used to perform a sensitivity analysis...
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