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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.
Daniel Rozon, Wei Shen
Nuclear Science and Engineering | Volume 138 | Number 1 | May 2001 | Pages 1-25
Technical Paper | doi.org/10.13182/NSE138-1-25
Articles are hosted by Taylor and Francis Online.
For both pressurized water reactor (PWR) and Canada deuterium uranium (CANDU) tandem analysis, the Direct Use of spent PWR fuel In CANDU reactor (DUPIC) fuel cycle in a CANDU 6 reactor is studied using the DRAGON/DONJON chain of codes with the ENDF/B-V and ENDF/B-VI libraries. The reference feed material is a 17 × 17 French standard 900-MW(electric) PWR fuel. The PWR spent-fuel composition is obtained from two-dimensional DRAGON assembly transport and depletion calculations. After a number of years of cooling, this defines the initial fuel nuclide field in the CANDU unit cell calculations in DRAGON, where it is further depleted with the same neutron group structure. The resulting macroscopic cross sections are condensed and tabulated to be used in a full-core model of a CANDU 6 reactor to find an optimized channel fueling rate distribution on a time-average basis. Assuming equilibrium refueling conditions and a particular refueling sequence, instantaneous full-core diffusion calculations are finally performed with the DONJON code, from which both the channel power peaking factors and local parameter effects are estimated. A generic study of the DUPIC fuel cycle is carried out using the linear reactivity model for initial enrichments ranging from 3.2 to 4.5 wt% in a PWR. Because of the uneven power histories of the spent PWR assemblies, the spent PWR fuel composition is expected to differ from one assembly to the next. Uneven mixing of the powder during DUPIC fuel fabrication may lead to uncertainties in the composition of the fuel bundle and larger peaking factors in CANDU. A mixing method for reducing composition uncertainties is discussed.
