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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.
Thomas E. Booth, Shane P. Pederson
Nuclear Science and Engineering | Volume 110 | Number 3 | March 1992 | Pages 254-261
Technical Paper | doi.org/10.13182/NSE92-A23897
Articles are hosted by Taylor and Francis Online.
Historically, Monte Carlo variance reduction techniques have been developed one at a time in response to calculational needs. The theoretical basis is provided for obtaining unbiased Monte Carlo estimates from all possible combinations of variance reduction techniques. Hitherto, the techniques have not been proven to be unbiased in arbitrary combinations. The authors are unaware of any Monte Carlo techniques (in any linear process) that are not treated by the theorem herein.