To expand the availability of electricity generated from nuclear power, have started developing designs for small modular reactors (SMRs), which could take less time and money to construct compared to existing reactors.
Toward this effort, a study conducted at Purdue University has made progress in enabling artificial intelligence to improve monitoring and control of SMRs, possibly offering a way to further cut costs of their operation and maintenance so that they can be more economically viable.
The study, published in , showed how a machine learning algorithm could rapidly learn about the physics behind a measurement of how steadily a reactor is producing power, and predict changes in this indicator over time with 99% accuracy.