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Division Spotlight
Human Factors, Instrumentation & Controls
Improving task performance, system reliability, system and personnel safety, efficiency, and effectiveness are the division's main objectives. Its major areas of interest include task design, procedures, training, instrument and control layout and placement, stress control, anthropometrics, psychological input, and motivation.
Meeting Spotlight
Conference on Nuclear Training and Education: A Biennial International Forum (CONTE 2025)
February 3–6, 2025
Amelia Island, FL|Omni Amelia Island Resort
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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Christmas Night
Twas the night before Christmas when all through the houseNo electrons were flowing through even my mouse.
All devices were plugged in by the chimney with careWith the hope that St. Nikola Tesla would share.
Nickolas J. Adamowicz, Annalisa Manera, Edward W. Larsen
Nuclear Science and Engineering | Volume 197 | Number 2 | February 2023 | Pages 262-278
Technical Paper | doi.org/10.1080/00295639.2022.2112900
Articles are hosted by Taylor and Francis Online.
The coarse-mesh finite difference (CMFD) method is commonly used to accelerate the iterative convergence of single-physics neutron transport problems. For multiphysics problems, the neutron cross sections depend on the temperature and density, both of which depend on the fission heat source; the resulting nonlinear feedback can significantly degrade the performance of CMFD and even cause instability. In this paper, we propose, for a class of one-dimensional (1-D) model multiphysics problems, a new nonlinearly implicit low-order (NILO) CMFD (NILO-CMFD) acceleration method to improve the performance of CMFD-based methods for solving loosely coupled multiphysics problems. Our numerical testing and Fourier analysis show that for the 1-D model problems, the new NILO-CMFD method achieves the same rapid convergence rate that CMFD achieves for single-physics problems.