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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.
M. P. Sharma, A. K. Nayak
Nuclear Science and Engineering | Volume 188 | Number 2 | November 2017 | Pages 175-186
Technical Paper | doi.org/10.1080/00295639.2017.1339539
Articles are hosted by Taylor and Francis Online.
The Advanced Heavy Water Reactor (AHWR) is a vertical pressure tube–type, heavy water–moderated, and boiling light water–cooled natural-circulation–based reactor. The fuel bundle of AHWR contains 54 fuel rods arranged in three concentric rings of 12, 18, and 24 fuel rods. This fuel bundle is divided into a number of imaginary interacting flow passages called subchannels. Transition from a single-phase to a two-phase flow condition occurs in the reactor rod bundle with an increase in power. Predicting the thermal margin of the reactor has necessitated determining the diversion cross flow of coolant among these subchannels under two-phase flow. Thus, it is vital to evaluate cross flow between subchannels of the AHWR rod bundle. In this paper, experiments were carried out to investigate the diversion cross-flow phenomena for single- and two-phase flow in the simulated subchannels of the reactor. The size of the rod and the pitch in the test were the same as that of the actual rod bundle in the prototype. The cross-flow tests were carried out at atmospheric condition without adding heat. In addition, the capability of the existing correlation is also checked to predict the cross-flow resistance coefficient, and it is found that none of these models accurately predict the measured cross-flow resistance coefficient for the AHWR rod bundle. In view of this, a new model applicable to AHWR has been presented that predicts the cross-flow resistance coefficient quite accurately.