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Division Spotlight
Robotics & Remote Systems
The Mission of the Robotics and Remote Systems Division is to promote the development and application of immersive simulation, robotics, and remote systems for hazardous environments for the purpose of reducing hazardous exposure to individuals, reducing environmental hazards and reducing the cost of performing work.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
Standards Program
The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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Nuclear Technology
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Fusion Science and Technology
Latest News
New model describes how tokamak shape affects plasma stability
A new theoretical model about stabilizing plasma in tokamak fusion reactors is described in three papers from a study that was led by research physicist Jason Parisi of Princeton Plasma Physics Laboratory. Two papers—“Kinetic-ballooning-limited pedestals in spherical tokamak plasmas” and “Stability and transport of gyrokinetic critical pedestals”—appear in the International Atomic Energy Agency journal Nuclear Fusion. The other paper—“Kinetic-ballooning-bifurcation in tokamak pedestals across shaping and aspect-ratio”—appears in Physics of Plasmas.
Ryota Omori, Yasushi Sakakibara, Atsuyuki Suzuki
Nuclear Technology | Volume 118 | Number 1 | April 1997 | Pages 26-31
Technical Paper | Kiyose Birthday Anniversary Special / Enrichment and Reprocessing System | doi.org/10.13182/NT97-A35353
Articles are hosted by Taylor and Francis Online.
Applications of genetic algorithms (GAs) to optimization problems in the solvent extraction process for spent nuclear fuel are described. Genetic algorithms have been considered a promising tool for use in solving optimization problems in complicated and nonlinear systems because they require no derivatives of the objective function. In addition, they have the ability to treat a set of many possible solutions and consider multiple objectives simultaneously, so they can calculate many pareto optimal points on the trade-off curve between the competing objectives in a single iteration, which leads to small computing time. Genetic algorithms were applied to two optimization problems. First, process variables in the partitioning process were optimized using a weighted objective function. It was observed that the average fitness of a generation increased steadily as the generation proceeded and satisfactory solutions were obtained in all cases, which means that GAs are an appropriate method to obtain such an optimization. Secondly, GAs were applied to a multiobjective optimization problem in the co-decontamination process, and the trade-off curve between the loss of uranium and the solvent flow rate was successfully obtained. For both optimization problems, CPU time with the present method was estimated to be several tens of times smaller than with the random search method.