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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.
David A. White, Suttichai Assabumrungrat, Ahmad Moheb
Nuclear Technology | Volume 120 | Number 2 | November 1997 | Pages 149-157
Technical Paper | Radioisotopes and Isotope | doi.org/10.13182/NT97-A35423
Articles are hosted by Taylor and Francis Online.
The methodology for the optimization of an electrolytic plant for the production of deuterium is described. The basis of the optimization is to minimize the amount of electricity used in the electrolytic process, and this is assumed to be proportional to the total amount of gas evolution from the plant. Because the plant consists of two sections, i.e., the feed cascade and the reflux cascade, the conditions where the amount of gas evolution in each cascade is minimum were developed separately. The no-entropy condition, where two feed streams fed to a stage must have the same composition, was used in the optimization of the reflux cascade. From the results of the optimization, it was found that the location of the feed inlet to the reflux cascade and the number of stages in the reflux cascade are the major parameters in the optimization and, also, that the number of stages in the feed cascade does not significantly affect the optimum gas evolution results.