U.S. Representative Greg Pence (second from right), a member of the U.S. House Energy and Commerce Committee, toured Purdue Reactor 1, Indiana's first and only nuclear reactor, with Purdue University engineering professors and research leaders in August 2023. (Purdue University Photo/Kelsey Lefever)
Purdue University's research reactor serves as a test bed for optimizing the performance of small modular reactors.
WEST LAFAYETTE, Ind. — To expand the availability of nuclear-generated electricity, several countries have begun developing designs for small modular reactors (SMRs), which could potentially take less time and cost to build than existing nuclear reactors.
Towards this end, research conducted at Purdue University has made progress in leveraging artificial intelligence to improve the monitoring and control of SMRs, potentially offering a way to further reduce the costs of operating and maintaining SMRs and make them more economically viable.
The study, published in Nature Scientific Reports, showed how machine learning algorithms could quickly learn about the physics that measures how reliably a nuclear reactor is generating power, and predict changes in this metric over time with 99% accuracy.
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