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Denver, CO|Sheraton Denver
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AI at work: Southern Nuclear’s adoption of Copilot agents drives fleet forward
Southern Nuclear is leading the charge in artificial intelligence integration, with employee-developed applications driving efficiencies in maintenance, operations, safety, and performance.
The tools span all roles within the company, with thousands of documented uses throughout the fleet, including improved maintenance efficiency, risk awareness in maintenance activities, and better-informed decision-making. The data-intensive process of preparing for and executing maintenance operations is streamlined by leveraging AI to put the right information at the fingertips for maintenance leaders, planners, schedulers, engineers, and technicians.
Felix C. Difilippo
Nuclear Science and Engineering | Volume 143 | Number 3 | March 2003 | Pages 240-253
Technical Paper | doi.org/10.13182/NSE02-34
Articles are hosted by Taylor and Francis Online.
Under the auspices of the International Atomic Energy Agency, a series of well-documented benchmark experiments were performed at the Proteus facility of the Swiss Paul Scherrer Institute. Thirteen critical pebble bed reactor configurations were assembled, with ten of them deterministic with a precise location of the low-enriched fuel and moderator pebbles. Seven of these configurations were modeled with a very high spatial resolution with the Monte Carlo code MCNP with details that go from the fuel kernel (0.5 mm in diameter) to the walls surrounding the facility. The calculations of the k's of the configurations agree quite well with the experiments (within a fraction of a dollar). A sensitivity analysis is included to discuss the possibility of a small bias; also biases introduced by customary approximations of production codes were calculated. The experiments and the analysis of this paper might be very useful tools to check the calculational accuracy of procedures used in the emerging work related to pebble bed modular gas-cooled reactors.