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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.
Hunter Andrews, Supathorn Phongikaroon
Nuclear Technology | Volume 205 | Number 7 | July 2019 | Pages 891-904
Technical Paper – Selected papers from the 2018 ANS Student Conference | doi.org/10.1080/00295450.2018.1551988
Articles are hosted by Taylor and Francis Online.
Four different concentrations of SmCl3 in LiCl-KCl were tested using cyclic voltammetry to determine the diffusion coefficients of Sm(III) and Sm(II) found to be 8.59 × 10−6 ± 1.67 × 10−6 and 8.01 × 10−6 ± 0.98 × 10−6 cm2 s−1, respectively. Ten samples, in the form of salt ingots with SmCl3 concentrations ranging from 0.5 to 10.0 wt% were used for the creation of three laser-induced breakdown spectroscopy (LIBS) calibration models corresponding to 484.4-, 490.5-, and 546.7-nm peaks. Results show that the 490.5-nm peak model had the lowest limit of detection at 0.510 wt%, and all three models had similar root-mean-square errors of calibration values ranging from 0.470 to 0.498 wt%. Four validation samples were then used to test the diffusion and LIBS methods’ ability to estimate concentration. The results of both methods match well with the inductively coupled plasma mass spectroscopy–measured concentrations.