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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.
Tadashi Yoshida
Nuclear Science and Engineering | Volume 72 | Number 3 | December 1979 | Pages 361-365
Technical Note | doi.org/10.13182/NSE79-A20393
Articles are hosted by Taylor and Francis Online.
A method is presented for determining by numerical integration a diffusion coefficient, Dz, applicable to the axial direction of a control rod follower region in a sodium-cooled fast reactor. By comparing criticality values from transport and diffusion theory for a simplified reactor model, we are able to show that this Dz applies well to the followers from the viewpoint of the calculated criticality factor, keff. By use of the same model, an inter comparison is also made between the present and other definitions of Dz. By using the present Dz, as a conclusion, we show that the currently used D (= 1/3Σ) for control rod followers leads to an underestimation of keff by ∼0.3% for a typical 300-MW(electric) class liquid-metal fast breeder reactor with one-third of the control rods inserted, which may increase to 0.4 to 0.5% for a case where all control rods are withdrawn.