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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.
Leo B. Levitt
Nuclear Science and Engineering | Volume 31 | Number 3 | March 1968 | Pages 500-504
Technical Paper | doi.org/10.13182/NSE68-A17593
Articles are hosted by Taylor and Francis Online.
A method of increasing the sampling efficiency in Monte Carlo calculations of thick shield penetration has been developed. The procedure alters the effective mean-free-path in such a way as to maximize the rate of convergence of the transmission probability. The approach is semiempirical in nature and has been shown to be remarkably insensitive to geometry. The primary dependence appears to be on the nonabsorption probability at each collision, with secondary dependence on the distance to escape. The procedure is simple enough to permit its incorporation into existing Monte Carlo codes with a minimum of programming effort.