Method and apparatus for real-time learning-based augmented irradiation control and optimization
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United States of America Patent
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Oct 1, 2024
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Nov 18, 2021
app pub date -
Apr 21, 2021
filing date -
May 18, 2020
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Abstract
A machine-learning tool learns from sensors' data of a nuclear reactor at steady state and maps them to controls of the nuclear reactor. The tool learns all given ranges of normal operation and responses for corrective measures. The tool may train another learning tool (or the same tool) that forecasts the behavior of the reactor based on real-time changes (e.g., every 10 seconds). The tool implements an optimization technique for differing half-life materials to be placed in the reactor. The tool maximizes isotope production based on optimal controls of the reactor.
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