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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.
R. P. Gardner, M. Mickael, K. Verghese
Nuclear Science and Engineering | Volume 98 | Number 1 | January 1988 | Pages 51-63
Technical Paper | doi.org/10.13182/NSE88-A23525
Articles are hosted by Taylor and Francis Online.
A new direction biasing approach to a target point and to finite detectors for Monte Carlo simulation is developed, presented, and tested. It properly accounts for the weight adjustments that must be made for the combined choice of a particular scattering (polar) and rotational (azimuthal) angle to obtain a given biasing angle about either a target point or a finite detector. Sample Monte Carlo simulations for a neutron transport problem with isotropic center-of-mass scattering and a gamma-ray transport problem with Klein-Nishina scattering have been done by both the analog and new direction biasing methods. The results indicate that the direction biasing approach is valid and will be very efficient for deep-penetration problems of these two types.