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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.
Jinkai Wang, Warren D. Reece
Nuclear Science and Engineering | Volume 167 | Number 2 | February 2011 | Pages 154-164
Technical Paper | doi.org/10.13182/NSE09-94
Articles are hosted by Taylor and Francis Online.
The relative yields of delayed neutrons and the half-lives of their precursor nuclei are usually determined indirectly by the least-squares method based on the differences between experimental and fitted data. It is noted that the recommended values from ENDF/B-VII, ENDF/B-VI.8, JENDL-3.3, JEF-2.2, and JEFF-3.1 are significantly different. To evaluate these parameters, the measured data sets used in this research were simulated by the Monte Carlo method, and they were strict Poisson distributed data generated from Keepin's six-group data. Three different numerical methods (matrix inverse with singular value decomposition, Levenberg-Marquardt, and quasi Newton) with different regularization techniques were applied to estimate the parameter values. The fitted results were proven to be very unstable, and their calculated results were very different even for the same data set. Further investigation found ill-conditioned problems to be the reason for this instability. A better numerical method was suggested in this research.