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Conference Spotlight
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.
Woan Hwang, Cheol Nam, Thak Sang Byun, Young Cheol Kim
Nuclear Technology | Volume 123 | Number 2 | August 1998 | Pages 130-141
Technical Paper | Fuel Cycle and Management | doi.org/10.13182/NT98-A2887
Articles are hosted by Taylor and Francis Online.
Computational models for analyzing in-reactor behavior of metallic fuel pins in liquid-metal reactors under steady-state conditions are developed and implemented in the Metal fuel performance Analysis (computer) Code for Simulating the In-reactor behavior under Steady-state conditions (MACSIS). Sodium logging and constituent redistribution effects are considered in calculating the temperature profile. The model for the radial redistribution of the fuel constituent is based on the thermotransport theory. The fission gas release model takes multibubble size distribution into account to characterize the lenticular bubble shape and the saturation condition on the grain boundary. Finally, the clad strains are calculated from the amount of fission gas released and interface pressure. Sample calculations are performed to verify each model. The results show that in general, the predictions of MACSIS agree well with the available irradiation data.