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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.
Shi-Ping Teng, Duaine G. Lindstrom
Nuclear Science and Engineering | Volume 69 | Number 3 | March 1979 | Pages 363-366
Technical Paper | doi.org/10.13182/NSE79-A19953
Articles are hosted by Taylor and Francis Online.
The criticality constants of fissile solutions containing borated Raschig rings are evaluated using the Monte Carlo code KENO IV with various geometry models. In addition to those used by other investigators, a new geometry model, the random geometry model, is presented to simulate the system of randomly oriented Raschig rings in solution. A technique to obtain the material thickness distribution functions of solution and rings for use in the random geometry model is also presented. Comparison between the experimental data and the calculated results using the Monte Carlo method with various geometry models indicates that the random geometry model is a reasonable alternative to models previously used in describing the system of Raschig-ring-filled solution. The random geometry model also provides a solution to the problem of describing an array containing Raschig-ring-filled tanks that is not available to techniques using other models.