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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.
Robin Klein Meulekamp, Steven C. van der Marck
Nuclear Science and Engineering | Volume 152 | Number 2 | February 2006 | Pages 142-148
Technical Paper | doi.org/10.13182/NSE03-107
Articles are hosted by Taylor and Francis Online.
New Monte Carlo estimators of the effective delayed neutron fraction eff are presented in this paper. By looking at the physical interpretation of the adjoint function, one can incorporate its effect on the delayed neutron fraction without explicitly calculating the adjoint function itself. We have implemented these estimators into MCNP. In a standard keff calculation, the code now reports a eff value. The method does not slow down the code by more than 0.5%. We propose an extensive experimental benchmark set for eff, which we use to test our method and two known approximate methods. Our method reproduces all experimental values.