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2026 ANS Annual Conference
May 31–June 3, 2026
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.
D. B. James
Nuclear Technology | Volume 2 | Number 5 | October 1966 | Pages 379-389
Technical Paper and Note | doi.org/10.13182/NT66-A27614
Articles are hosted by Taylor and Francis Online.
The kinetics of the sorption of plutonium (IV) on Dowex 1 × 4 from nitrate solutions are presented. Sorption rates from various nitric acid and mixed aluminum-nitrate/nitric-acid solvents were studied. The particle-diffusion controlled reaction proceeds with an apparent average diffusion coefficient which decreases exponentially with increasing plutonium sorption. The results agree reasonably well with a computer solution of Fick's law with the local intraparticle diffusion coefficient proportional to the local intraparticle fraction of unreacted exchange sites. The trace-sorption diffusion coefficient is strongly dependent upon the composition of the aqueous phase, and is empirically shown to be roughly inversely proportional to the product of the trace-sorption distribution coefficient and the ratio of the hydronium ion-to-water concentrations. These kinetic results and previously reported equilibrium parameters may be coupled with the fundamental partial-differential equation which describes the operation of a fixed-bed anion-exchange column to allow computer optimization of plant-scale processing equipment. The effects of the variation of such parameters as volume and mass flow rate, temperature, plutonium feed concentration, and macro concentrations of aluminum nitrate in the feed are qualitatively discussed for one equipment design.