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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.
Andreas Szeless, Lawrence Ruby
Nuclear Science and Engineering | Volume 45 | Number 1 | July 1971 | Pages 7-13
Technical Paper | doi.org/10.13182/NSE71-A20340
Articles are hosted by Taylor and Francis Online.
A method has been devised to calculate exactly the probability distribution of reactor neutron noise. The distribution is calculated from a complicated generating function which has been known for some time. The method depends on the success achieved in obtaining a closed-form expression for the n'th derivative of a differentiable r-fold composite function. As an application of the technique, exact probability distributions are calculated for a variety of parameters. The resultant distributions are compared with the approximative negative binomial distribution. In some cases, rather similar variances are found, where the negative binomial is not expected to be a good approximation to the exact distribution. The explanation lies in an interlacing of the exact and approximative distributions. A procedure is described for fitting an experimental distribution to the exact distribution, thereby obtaining the best values of the parameters α1 and Y1 ∞. When the negative binomial is a good approximation to the exact distribution, only the product α1 Y1 ∞ can be obtained by the fitting procedure. In such cases, a Feynman-variance experiment can be performed to determine the parameters separately.
