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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.
Wenchao Zhang, Robin P. Gardner
Nuclear Science and Engineering | Volume 151 | Number 3 | November 2005 | Pages 361-373
Computer Code Abstract | doi.org/10.13182/NSE05-A2556
Articles are hosted by Taylor and Francis Online.
A Monte Carlo simulation code, CEARPGA II, has been developed to generate the complete set of library spectra that are required for the application of the Monte Carlo-Library Least-Squares approach in prompt-gamma-ray neutron activation analysis. Compared to the previous version, the CEARPGA I code, several important improvements have been made including eliminating the "big weight" problem by implementing the Analog Linear Interpolation technique, generating the appropriate detector response functions using improved simulation models that account for NaI detector nonlinearity and flat continua, generating the neutron activation backgrounds by directly sampling detector-activated gamma-ray energies, generating the natural background libraries by interpolating the energy-score tables, and tracking the annihilation gamma rays from the pair production interaction that occurs outside the detector. The coal sample spectrum calculated with the CEARPGA II code is benchmarked against those calculated from the CEARPGA I code, the MCNP code, and experimentally measured data.