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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.
G. Reffo, F. Fabbri, K. Wisshak, F. Käppeler
Nuclear Science and Engineering | Volume 83 | Number 3 | March 1983 | Pages 401-407
Technical Note | doi.org/10.13182/NSE83-A17576
Articles are hosted by Taylor and Francis Online.
Capture gamma-ray spectra of 240Pu, 242Pu, and 238U were calculated in the framework of the spherical optical model and the statistical model. A consistent set of input parameters was determined from available experimental information or from model-guided systematics. The complete gamma-ray cascades were calculated considering all possible transitions up to multiplicity seven. All experimental information on level schemes and gamma-ray transition probabilities of the compound nuclei was explicitly included as input. The capture gamm-ray spectra were used to correct experimental data for the capture cross sections of 240Pu and 242Pu from a relative measurement using a Moxon-Rae detector with a graphite converter and with 197Au and 238U as standards. This correction is required to take into account that the detector efficiency is not exactly proportional to the gamma-ray energy. The resulting correction factors proved to be negligible for measurements relative to 238U; whereas, they are ∼3% if gold is used as a standard.