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Mathematics & Computation
Division members promote the advancement of mathematical and computational methods for solving problems arising in all disciplines encompassed by the Society. They place particular emphasis on numerical techniques for efficient computer applications to aid in the dissemination, integration, and proper use of computer codes, including preparation of computational benchmark and development of standards for computing practices, and to encourage the development on new computer codes and broaden their use.
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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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Grant awarded for advanced reactor workforce needs in southeast U.S.
North Carolina State University and the Electric Power Research Institute have been awarded a $500,000 grant by the NC Collaboratory for “An Assessment to Define Advanced Reactor Workforce Needs,” a project that aims to investigate job needs to help enable new nuclear development and deployment in North Carolina and surrounding areas.
Henry Lichtenstein
Nuclear Science and Engineering | Volume 133 | Number 3 | November 1999 | Pages 258-268
Technical Paper | doi.org/10.13182/NSE99-A2086
Articles are hosted by Taylor and Francis Online.
An adaptive reduced-source approach is utilized for a Monte Carlo transport solution for the one-speed finite slab problem in [x,] geometry. Although a solution for the underlying problem has been available to arbitrary precision for some time, the purpose here is to demonstrate how the convergence afforded by traditional (nonadaptive) Monte Carlo can be improved significantly, without compromising its precision. It is demonstrated that the reduced-source Monte Carlo technique obtains multiple-orders-of-magnitude improvement over traditional Monte Carlo convergence for the two-dimensional transport problem treated. The goal is that ongoing research will obtain exponential convergence for practical applications that are not tractable with methodology currently available.