ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
Explore the many uses for nuclear science and its impact on energy, the environment, healthcare, food, and more.
Explore membership for yourself or for your organization.
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!
Latest Magazine Issues
Jul 2025
Jan 2025
Latest Journal Issues
Nuclear Science and Engineering
August 2025
Nuclear Technology
Fusion Science and Technology
July 2025
Latest News
Hash Hashemian: Visionary leadership
As Dr. Hashem M. “Hash” Hashemian prepares to step into his term as President of the American Nuclear Society, he is clear that he wants to make the most of this unique moment.
A groundswell in public approval of nuclear is finding a home in growing governmental support that is backed by a tailwind of technological innovation. “Now is a good time to be in nuclear,” Hashemian said, as he explained the criticality of this moment and what he hoped to accomplish as president.
N. Shenhav, Y. Segal, A. Notea
Nuclear Science and Engineering | Volume 80 | Number 1 | January 1982 | Pages 61-73
Technical Paper | doi.org/10.13182/NSE82-A21404
Articles are hosted by Taylor and Francis Online.
A general approach to the application of neutron count moment analysis to passive assay is presented. The higher moments of the neutron count distribution are derived with the aid of the probability generating function and are used to formulate an analytic relation between the measurement uncertainty and the assay system parameters. The measurement uncertainty, expressed by the relative resolving power function, for the reduced variance method is developed and analyzed in detail. The study suggests an iterative approach for data processing where the interpretational models are chosen to yield the lowest possible resolving power.
