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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.
H. Andrews, S. Phongikaroon
Nuclear Technology | Volume 207 | Number 4 | April 2021 | Pages 617-626
Technical Paper | doi.org/10.1080/00295450.2020.1776538
Articles are hosted by Taylor and Francis Online.
This study sets out to demonstrate the capability of using electrochemistry and laser-induced breakdown spectroscopy (LIBS) for concentration prediction of multiple species in a molten salt system at 773 K. Samples contained UCl3 ranging from 0 to 10 wt%, GdCl3 ranging from 0 to 5 wt%, and MgCl2 ranging from 0 to 1.5 wt%, with LiCl-KCl eutectic salt as the remainder. Multivariate models were produced using semi-differential cyclic voltammograms (SDCVs) and normalized spectra acquired from LIBS. The SDCV model best predicted UCl3 levels, while the LIBS model best predicted GdCl3 and MgCl2 concentrations. A third model was developed by fusing the SDCV and LIBS signals. This model predicted UCl3 well and predicted GdCl3 and MgCl2 better than previous models. This model was then evaluated by using blind samples. The model predictions correlated well with inductively coupled plasma mass spectroscopy measurements, passing a t-test at a 95% confidence level.