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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.
Yixiang Gan, Francisco Hernandez, Dorian Hanaor, Ratna Annabattula, Marc Kamlah, Pavel Pereslavtsev
Fusion Science and Technology | Volume 66 | Number 1 | July-August 2014 | Pages 83-90
Technical Paper | doi.org/10.13182/FST13-727
Articles are hosted by Taylor and Francis Online.
Due to neutron irradiation, solid breeder blankets are subjected to complex thermo-mechanical conditions. Within one breeder unit, the ceramic breeder bed is composed of spherical-shaped lithium orthosilicate pebbles, and as a type of granular material, it exhibits strong coupling between temperature and stress fields. In this paper, we study these thermo-mechanical problems by developing a thermal discrete element method (Thermal-DEM). This proposed simulation tool models each individual ceramic pebble as one element and considers grain-scale thermo-mechanical interactions between elements. A small section of solid breeder pebble bed in a helium-cooled pebble bed (HCPB) is modelled using thousands of individual pebbles and subjected to volumetric heating profiles calculated from neutronics under ITER-relevant conditions. We consider heat transfer at the grain scale between pebbles through both solid-to-solid contacts and the interstitial gas phase, and we calculate stresses arising from thermal expansion of pebbles. The overall effective conductivity of the bed depends on the resulting compressive stress state during the neutronic heating. The Thermal-DEM method proposed in this study provides access to the grain-scale information, which is beneficial for HCPB design and breeder material optimization, and a better understanding of overall thermo-mechanical responses of the breeder units under fusion-relevant conditions.