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Division Spotlight
Operations & Power
Members focus on the dissemination of knowledge and information in the area of power reactors with particular application to the production of electric power and process heat. The division sponsors meetings on the coverage of applied nuclear science and engineering as related to power plants, non-power reactors, and other nuclear facilities. It encourages and assists with the dissemination of knowledge pertinent to the safe and efficient operation of nuclear facilities through professional staff development, information exchange, and supporting the generation of viable solutions to current issues.
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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ANS 2025 election is open
The American Nuclear Society election is now open. Members can vote for the Society’s next vice president/president-elect and treasurer as well as six board members (four U.S. directors, one non-U.S. director, and one student director). Completed ballots must be submitted by 1:00 p.m. (EDT) on Tuesday, April 15, 2025.
Gerald L. Atkinson, William Kerr, James J. Duderstadt
Nuclear Science and Engineering | Volume 51 | Number 3 | July 1973 | Pages 324-330
Technical Paper | doi.org/10.13182/NSE73-A26609
Articles are hosted by Taylor and Francis Online.
The discrete ordinates algorithm in plane geometry is formulated within a mathematical framework which allows a detailed analysis of its convergence properties. The infinity norm of the iteration matrix is explicitly calculated for a slab geometry with a homogeneous isotropically scattering medium. This approach permits the calculation of a new convergence criterion which, along with the demonstrated convergence properties of the SN algorithm, guarantees that the fractional iterative error is arbitrarily small.
