ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
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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.
Meeting Spotlight
ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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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Latest News
Norway’s Halden reactor takes first step toward decommissioning
The government of Norway has granted the transfer of the Halden research reactor from the Institute for Energy Technology (IFE) to the state agency Norwegian Nuclear Decommissioning (NND). The 25-MWt Halden boiling water reactor operated from 1958 to 2018 and was used in the research of nuclear fuel, reactor internals, plant procedures and monitoring, and human factors.
Seung Hwan Seong, Un Chul Lee, Si Hwan Kim, Jin Wook Jang
Nuclear Technology | Volume 128 | Number 2 | November 1999 | Pages 276-283
Technical Paper | Reactor Operations and Control | doi.org/10.13182/NT99-A3031
Articles are hosted by Taylor and Francis Online.
A new analytic model based on hidden-layer neural networks is designed to analyze load-follow operation in a pressurized water reactor (PWR). The new model is mainly made up of four error backpropagation neural networks and procedures to calculate core parameters such as k and xenon distributions in a transient core. The first two neural networks are designed to retrieve the power distribution, the third is for axial offset, and the fourth is for reactivity corresponding to a given core condition. The training data sets are generated by three-dimensional nodal code and the measured data of the first-day load-follow operation. The simulation results of the 5-day load-follow test in a PWR using the new analytic model show that it is an attractive tool for plant simulations in terms of accuracy, computing time, cost, and adaptability to measurements.