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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.
John F. Geldard, Leigh Phillips, Adolph L. Beyerlein
Nuclear Technology | Volume 70 | Number 3 | September 1985 | Pages 394-400
Technical Paper | Chemical Processing | doi.org/10.13182/NT85-A15965
Articles are hosted by Taylor and Francis Online.
Distribution coefficient correlations for U(IV) and Pu(III) are obtained in terms of a modified form of the total nitrate ion salting strength that was successfully used to obtain distribution coefficient correlations for U(VI) and Pu(IV) in the earlier work of G. L. Richardson. The modification of salting strength was needed to account for the fact that the U(IV) distribution coefficients measured under conditions where U(VI) is present consistently fall below those obtained when it is absent. The correlations were incorporated into the mixer-settler computer model PUBG, and in the simulation of a 20-stage IB partitioning contactor, calculated product stream concentrations were in excellent agreement with experiment. Earlier mixersettler computer models, which failed to account for U(IV) distribution coefficients, predicted that U(IV) remained in the aqueous product stream, which is contrary to the experimental measurements.