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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.
J. T. Fisher, J. W. Leachman
Fusion Science and Technology | Volume 64 | Number 3 | September 2013 | Pages 525-529
Fusion Technologies: Heating and Fueling | Proceedings of the Twentieth Topical Meeting on the Technology of Fusion Energy (TOFE-2012) (Part 2) Nashville, Tennessee, August 27-31, 2012 | doi.org/10.13182/FST13-A19146
Articles are hosted by Taylor and Francis Online.
Twin screw extrusion is anticipated to meet the pellet fueling demands of tokamak fusion devices. The twin-screw design principle has been proven by a functional prototype extruder at Oak Ridge National Laboratory (ORNL); however numerical models necessary for design optimization have yet to be validated due to system complexity. Characteristic measurements of solid flow during extrusion are difficult for any extruder and are exacerbated by the cryogenic environment necessary to solidify solid hydrogen. In this paper, we first discuss current modeling efforts to establish needs for experimental measurements and then present the design and construction status of a diagnostic twin-screw extruder to address these needs. Development is underway of a mass transfer analysis that predicts volumetric efficiency and augments an existing 1st order model of extrudate temperature. These predictive models are necessary for design and operation of hydrogenic twin screw extruders for fueling tokamaks, including ITER.