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Conference Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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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Powering the future: How the DOE is fueling nuclear fuel cycle research and development
As global interest in nuclear energy surges, the United States must remain at the forefront of research and development to ensure national energy security, advance nuclear technologies, and promote international cooperation on safety and nonproliferation. A crucial step in achieving this is analyzing how funding and resources are allocated to better understand how to direct future research and development. The Department of Energy has spearheaded this effort by funding hundreds of research projects across the country through the Nuclear Energy University Program (NEUP). This initiative has empowered dozens of universities to collaborate toward a nuclear-friendly future.
M. Goldstein, E. Greenspan
Nuclear Science and Engineering | Volume 76 | Number 3 | December 1980 | Pages 308-322
Technical Paper | doi.org/10.13182/NSE80-A21321
Articles are hosted by Taylor and Francis Online.
A recursive Monte Carlo (RMC) method for estimating the importance function distribution in three-dimensional systems, intended for importance sampling applications, is developed. The method consists of dividing the system into relatively thin geometrical regions and solving the inhomogeneous forward transport equation for each of the regions. The RMC method is found to possess a number of unique features, including the ability to infer the importance function distributions pertaining to many different detectors from essentially a single Monte Carlo run. Various technical questions concerned with the practical application of the RMC method, including the questions of the accumulation of statistical and systematic errors and their dependence on the details of the system division and source batch size, are investigated. A promising algorithm for the application of the method is formulated. The practicality and efficiency of the RMC method is investigated for a number of monoenergetic problems.
