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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.
R. Bovalini, F. D’Auria, G. M. Galassi
Nuclear Science and Engineering | Volume 115 | Number 2 | October 1993 | Pages 89-111
Technical Paper | doi.org/10.13182/NSE93-A28521
Articles are hosted by Taylor and Francis Online.
A methodology is described that can be used for the extrapolation of thermal-hydraulic phenomena measured in differently scaled integral test facilities to nuclear reactor plant conditions. The use of a system code in this context is confirmed to be of fundamental importance, provided that the code’s scaling capability has been demonstrated. The starting data base for the proposed study consists of the measured quantities and corresponding RELAP5/MOD2 code calculation results related to a boiling water reactor small-break loss-of-coolant accident (SBLOCA) counterpart test activity, a pressurized water reactor (PWR) natural-circulation type test activity, and a PWR SBLOCA counterpart test activity. The proof that this methodology can be used for evaluating uncertainties in predicting transient behavior in nuclear power plants is the main result of this study. Data have been obtained that give a value of the foreseeable error ranges in the provision of plant behavior in the three cases considered.