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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.
Chang Je Park, Nam Zin Cho
Nuclear Science and Engineering | Volume 142 | Number 1 | September 2002 | Pages 64-74
Technical Note | doi.org/10.13182/NSE02-A2288
Articles are hosted by Taylor and Francis Online.
In solving the discrete ordinates neutron transport equation, the additive angular dependent rebalance (AADR) acceleration method proposed by the authors previously is simple to implement, unconditionally stable, and very effective. For slab geometry problems, it is demonstrated via Fourier analysis that the spectral radii of the AADR acceleration in S4-like and DP1-like rebalances as well as DP0-like rebalance are less than that of diffusion synthetic acceleration (DSA). This AADR acceleration method is easily extendable to DPN-like and low-order SN-like rebalancing, and it does not require consistent discretizations between the high-order and low-order equations as does DSA. The continuous Fourier analysis is also performed for rectangular geometry. This Fourier analysis shows that the AADR with directional S2-like weighting functions, which uses two different rebalance factors for the x and y directions per octant, provides better results than the AADR with the normal S2-like weighting functions, which uses a single weighting function per octant. The low-order equation in AADR is solved by a preconditioned Bi-CGSTAB algorithm, which reduces computational burden significantly.
