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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.
Yassin A. Hassan, Wael A. Ibrahim
Nuclear Technology | Volume 119 | Number 1 | July 1997 | Pages 11-28
Technical Paper | Heat Transfer and Fluid Flow | doi.org/10.13182/NT77-A35391
Articles are hosted by Taylor and Francis Online.
Turbulent flow is characterized by random fluctuations in the fluid velocity and by intense mixing of the fluid. A wide range of eddies exists in the flow field. Because these eddies carry mass, momentum, and energy, this enhanced mixing can sometimes lead to serious problems, such as tube vibrations in many engineering systems that include fluid-tube bundle combinations. Nuclear fuel bundles and pressurized water reactor (PWR) steam generators are existing examples of fluid-tube bundle combinations in nuclear power plants. One of the critical areas in PWR steam generators is the weld between the tubes and the tube plate. Fluid-induced vibration problems are often discovered during the operation of such systems because some of the fluid-tube interaction characteristics are not fully understood. Large-eddy simulation, incorporated in three-dimensional computer codes, became one of the promising techniques to estimate flow turbulence. An investigation of the complex flow turbulence in tube bundles was carried out. Simulation of flow across tube bundles with various pitch-to-diameter ratios was performed. Power spectral densities of drag and lift coefficients were used for comparison with experimental data. Estimation of flow-length scales and other important turbulence-related parameters were obtained. Finally, important characteristics of the turbulent flow field were presented with the aid offlow visualization, using both vector and vorticity plots and the flow paths of flow tracers embedded in the flow field.