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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
2024 ANS Winter Conference and Expo
November 17–21, 2024
Orlando, FL|Renaissance Orlando at SeaWorld
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
Japanese researchers test detection devices at West Valley
Two research scientists from Japan’s Kyoto University and Kochi University of Technology visited the West Valley Demonstration Project in western New York state earlier this fall to test their novel radiation detectors, the Department of Energy’s Office of Environmental Management announced on November 19.
Adam J. Rau, William J. Walters
Nuclear Science and Engineering | Volume 195 | Number 10 | October 2021 | Pages 1017-1035
Technical | doi.org/10.1080/00295639.2021.1905431
Articles are hosted by Taylor and Francis Online.
Monte Carlo methods are useful for simulating new reactor designs, but even with advances in computing, these methods still require a significant amount of time to perform transient or multiphysics calculations coupled with thermal modeling.
This work demonstrates a hybrid reactor physics method that uses Monte Carlo to precalculate an initial database of fission matrix parameters, then combines these results for fast calculations on arbitrary system states. This paper extends previous work that demonstrated these methods on the Penn State Breazeale Reactor (PSBR). Approaches for reducing time and memory cost and increasing the accuracy in reproducing Monte Carlo output are considered. For modeling fuel temperature, a representative temperature distribution is used while tallying the initial fission matrix database. Different approaches for modeling the coupling between individual control rod insertions as well as control and fuel temperature effects are presented as well.
Individual solutions are completed in less than 1 s on a single core, and error with respect to Monte Carlo is within 35 pcm for multiplication factor, 0.6% root-mean square, and 2.8% maximum for the normalized three-dimensional fission source distribution on critical, steady-state configurations. Further qualification on different reactor types is needed, but the simplicity and flexibility of this method make further development promising.