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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.
J. B. Fussell
Nuclear Science and Engineering | Volume 52 | Number 4 | December 1973 | Pages 421-432
Technical Paper | doi.org/10.13182/NSE73-A23308
Articles are hosted by Taylor and Francis Online.
A model is presented for formulating the Boolean failure logic, called the fault tree, for electrical systems from associated schematic diagrams and system-independent component information. The model is developed in detail for electrical systems, while its implication and terminology extend to all fault tree construction. The methodology is verified as formal by fault trees constructed by a computer—with typical execution times for a fault tree with 100 gates on the order of 7 sec (on the UNIVAC 1108 computer). The model, called Synthetic Tree Model, is a synthesis technique for piecing together, with proper editing, a fault tree from system-independent component information beginning with the main failure of interest and proceeding to more basic failures. The resultant fault trees are in conventional format, use conventional symbols, and are, consequently, immediately compatible with existing solution techniques. While Synthetic Tree Model develops the fault tree to the level of primary failures, extensions of the model could handle secondary failures, i.e., failure-related feedback between components.