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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.
Young Jin Kim,* Thomas J. Downar, Alexander Sesonske
Nuclear Science and Engineering | Volume 96 | Number 2 | June 1987 | Pages 85-101
Technical Paper | doi.org/10.13182/NSE87-A16369
Articles are hosted by Taylor and Francis Online.
A method was developed to optimize pressurized water reactor low-leakage core reload designs that features the decoupling and sequential optimization of the fuel arrangement and control problems. The two-stage optimization process provides the maximum cycle length for a given fresh fuel loading subject to power peaking constraints. In the first stage, a best fuel arrangement is determined at the end of cycle (EOC) in the absence of all control poisons by employing a direct search method. The constant power, Haling depletion is used to provide the cycle length and EOC power peaking for each candidate core fuel arrangement. In the second stage, the core control poison requirements to meet the core peaking constraints throughout the cycle are determined using an approximate nonlinear programming technique. For the core description, the design method utilizes a currently recognized licensing-type code, SIMULATE-E, that was adapted to the CYBER-205 computer. The methodology was applied to the core reload design for cycles 9 and 10 of the Commonwealth Edison Company (CECo) Zion-1 reactor. The results showed that, compared with the reference design used by CECo, the optimum loading pattern for cycle 9 yielded almost a 9% increase in the cycle length while reducing core vessel fluence by 30%. Cycle length increase is a direct measure of economic savings for a given fuel loading. The results of cycle 10 optimization produced similar improvements. Should cycle length constraints apply, the procedure could be used to yield a decrease in fuel enrichment, with comparable savings resulting.