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2026 ANS Annual Conference
May 31–June 3, 2026
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.
P. Goldschmidt
Nuclear Science and Engineering | Volume 49 | Number 3 | November 1972 | Pages 263-273
Technical Paper | doi.org/10.13182/NSE72-A22541
Articles are hosted by Taylor and Francis Online.
Pontryagin’s Maximum Principle and Robbins’ Criterion allow us to find, in the general case of intermediate reactors, the distribution of fuel enrichment that minimizes the critical mass of a reactor of given power and subject to constraints on the maximum power density and on the enrichment. The two group diffusion model is used in slab geometry. The optimal sequence of control (enrichment) zones is made up of a central constant power density zone, a zone of maximum enrichment, a zone of variable enrichment (where the control is singular) and finally an external zone of minimum enrichment (or a reflector). In the particular case of fast reactors the optimal solution does not include the singular control zone.