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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.
Su-Jin Jeon, Jae-Sang Lee, Do-Hyun Kim, Seok-Ho Hong, Chun-Sik Lee, Young-Wan Choi
Nuclear Technology | Volume 206 | Number 7 | July 2020 | Pages 1075-1085
Regular Technical Paper | doi.org/10.1080/00295450.2019.1697175
Articles are hosted by Taylor and Francis Online.
A homography method to correct position errors generated in the Compton imaging system using a resistive network is presented. The Compton imaging system is composed of a scatterer and an absorber in multichannel arrays for high resolution and can detect gamma rays emitted from radioisotopes. Resistive networks are often used in this system to efficiently reduce the number of channels. However, this can cause position errors, and the spatial resolution deteriorates according to the resistance value of the network, type of detector array, and characteristics of the preamplifier used. Therefore, before tracking the position of the source, it is necessary to correct the position errors of images obtained from the scatterer and absorber. Also, a new correction method should consider the characteristics of the readout circuits based on the resistive network. In this work, the position errors are corrected using homography, which is a coordinate transformation method. To verify the corrections using homography transformation, we modeled the current pulse generated from the detector and designed an automatic channel selection circuit to input each channel of the resistive network. From experiments, we first obtained the positions with distortions according to the setup of readout circuits and corrected these errors by applying the homography transformation method. Consequently, the distortions were significantly corrected, and the error rates of the positions compared with those of the ideal grid were greatly reduced by up to 0.36%.