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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.
Kaushik Chatterjee, Mohammad Modarres
Nuclear Science and Engineering | Volume 170 | Number 2 | February 2012 | Pages 136-150
Technical Paper | doi.org/10.13182/NSE11-27
Articles are hosted by Taylor and Francis Online.
In probabilistic safety assessments of pressurized water reactors, it is imperative to assess the potential and frequency of steam generator tube ruptures. Estimation of the frequency of steam generator tube ruptures has traditionally been based on historical occurrences, which are not applicable to new designs of steam generators with different geometries, material properties, degradation mechanisms, and thermal-hydraulic behaviors. This paper presents a new probabilistic mechanistic-based approach for estimating steam generator tube rupture frequency that is based on the principle that the failure of passive systems is governed by degradation or unfavorable conditions created through the underlying operating conditions and underlying mechanical, electrical, thermal, and chemical processes. This developed approach identifies, probabilistically models, and simulates potential degradations in new and existing steam generator designs to assess degradation versus time, until such degradation exceeds a known endurance limit. An example application of the proposed reliability prediction approach is presented for a new design of small modular reactor steam generators consisting of helically coiled tubes fabricated with advanced tube materials. This developed probabilistic physics-of-failure-based approach, when combined with probabilistic safety assessment techniques, can provide an effective tool for the evaluation of the safety and reliability of steam generators, particularly new steam generator designs used in advanced reactors.