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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.
Joong Seok Suh, Samuel H. Levine
Nuclear Science and Engineering | Volume 105 | Number 4 | August 1990 | Pages 371-382
Technical Paper | doi.org/10.13182/NSE90-A21471
Articles are hosted by Taylor and Francis Online.
An efficient reload core design method, applicable to a commercial pressurized water reactor, has been developed. The objective of the reload core design is to achieve the maximum cycle length. The optimization of the reload core design is effected in three stages:. Use a linear programming method to find an optimum beginning-of-cycle (BOC) k∞ distribution, which yields maximum keffat the end of cycle when depleted by the Haling power distribution. Individual fuel assemblies are then loaded into the core using the optimum BOC k∞ distribution as a guide. Compute the optimum burnable poison requirements in parts per million/billion and their corresponding boron carbide weight percents for the fresh fuel assemblies using the gradient projection method. Deplete the optimum design using an accurate analysis. The application of the method to Three Mile Island Unit 1 (TMI-1) cycles 5 and 6 has shown that an optimum loading pattern for maximum cycle length is a low-leakage core. Compared with the TMI-1 loading patterns, the optimization has yielded an increase in cycle length by 12 effective full-power days (EFPDs) in cycle 6 and 41 EFPDs in cycle 5 plus saving about $3 million in fuel cost. The reason for the greater improvement in cycle 5 is that the cycle 5 loading pattern was a high-leakage core and the optimum design is a low-leakage core. The computer time required for computing one reload core design is ∼400 s on the IBM-3090 computer.