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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.
W. Ciechanowicz
Nuclear Science and Engineering | Volume 57 | Number 1 | May 1975 | Pages 39-52
Technical Paper | doi.org/10.13182/NSE75-A40341
Articles are hosted by Taylor and Francis Online.
The aim of the paper is to show how the complex, overall burnup optimization problem, t subject to the constraint of the desired power distribution, can be solved by decomposition into less complex coordinated subproblems. The solution has been obtained by use of the multilevel approach. The advantage of this approach is that it makes the computer solution of the problem of optimization practical. Two decomposition structures are considered: one for discrete and one for continuous reactor refueling. In the second case we deal with the optimization problem subject to the constraint in a form of an inequality containing a differentiable operator. To solve this problem the generalized Kuhn-Tucker theorem is used. To determine the optimum control of the desired power distribution, the Kulikowski approach is applied. As a result, the cyclic optimization process for both structures is obtained in which the information is exchanged between suitable level controllers.