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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.
Satoshi Takeda, Takanori Kitada
Nuclear Science and Engineering | Volume 197 | Number 8 | August 2023 | Pages 1621-1633
Technical papers from: PHYSOR 2022 | doi.org/10.1080/00295639.2022.2123679
Articles are hosted by Taylor and Francis Online.
Assuming that the discrepancy between the experimental value and the calculation value comes from the cross section, experimental error, and calculation error, Bayesian estimation of the cross section and these errors were studied. Uncertainty of the discrepancy between the experimental value and the design value is discussed by comparing the present estimation and the bias factor method. Comparison of the formulas shows that the design value obtained by the bias factor method is consistent with that obtained by estimation of the cross section and calculation error of the target system. In addition, the uncertainty of the discrepancy between the experimental value and the design value can be reduced by considering a correlation of the experimental error between the mock-up experiment and the target system. A case study was performed using mixed oxide critical assembly benchmarks. The result shows that the experimental value of the target system can be accurately predicted by considering the cross section, experimental error, and calculation error.