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Division Spotlight
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.
Meeting 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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Latest News
NRC cuts fees by 50 percent for advanced reactor applicants
The Nuclear Regulatory Commission has announced it has amended regulations for the licensing, inspection, special projects, and annual fees it will charge applicants and licensees for fiscal year 2025.
Federico Di Rocco, Dan G. Cacuci, Madalina C. Badea
Nuclear Science and Engineering | Volume 185 | Number 3 | March 2017 | Pages 549-603
Technical Paper | doi.org/10.1080/00295639.2017.1279943
Articles are hosted by Taylor and Francis Online.
This paper provides the results of the adjoint sensitivity model developed in the accompanying Part I for a natural draft counter-flow cooling tower. The selected responses are (1) outlet air temperature, (2) outlet water temperature, (3) outlet water mass flow rate, (4) air outlet relative humidity, and (5) air mass flow rate. Explicit expressions for the best-estimate nominal values of the model parameters and responses are also provided, together with the best-estimate reduced standard deviations of the predicted model parameters and responses. The results stemming from this work show that the PM_CMPS procedure reduces the predicted standard deviations of all responses and model parameters.
