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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.
Jean-Marc Depinay, Michel Caillaud, Remi Sentis
Nuclear Science and Engineering | Volume 152 | Number 1 | January 2006 | Pages 48-55
Technical Paper | doi.org/10.13182/NSE06-A2562
Articles are hosted by Taylor and Francis Online.
Application of the Monte Carlo method to deep-penetration transport problems often requires a biasing technique based on the use of an importance function. Here, in the framework of a multigroup model, we use an importance function in the form Ig([arrow over]x, [arrow over]) = eKg[arrow over].[arrow over]x[varphi]g([arrow over]), where g is the energy group index that ranges from 1 to G and [arrow over] is a vector usually fixed empirically. We describe an algorithm to find a good set of coefficients Kg and a good set of functions [varphi]g. To do this, we solve a system derived from the homogenous adjoint equations. We give two numerical examples where we show how these importance functions can enhance the accuracy of the computation.