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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.
Harshavardhan Kadvekar, Sana Khan, Sangeetha Prasanna Ram, Jayalekshmi Nair, S. Ganesan
Nuclear Science and Engineering | Volume 183 | Number 3 | July 2016 | Pages 356-370
Technical Paper | doi.org/10.13182/NSE15-103
Articles are hosted by Taylor and Francis Online.
In a majority of the cases, error propagation studies in nuclear science and engineering use the sandwich formula, which is strictly applicable when the probability density function of the random input quantities (e.g., the basic cross-section data) are determined completely by the mean and covariances. The use of the sandwich formula, which is also referred to in the literature as traditional first-order sensitivity analysis or adjoint-based sensitivity and uncertainty analysis, requires the assumption of linearity assumption and relatively small errors. For the first time, this paper examines the application of unscented transformation (UT) technique, which is used in control and reliability engineering, to error propagation in the nuclear field for nonlinear cases. Using different examples, this paper shows that this deterministic method of UT produces better results compared to the conventional sandwich formula for error propagation. An example on error propagation given in the literature is revisited, and a calculation of the efficiency of a gamma-ray detector is also presented for illustrative purposes using the UT method.