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.
Division Spotlight
Fuel Cycle & Waste Management
Devoted to all aspects of the nuclear fuel cycle including waste management, worldwide. Division specific areas of interest and involvement include uranium conversion and enrichment; fuel fabrication, management (in-core and ex-core) and recycle; transportation; safeguards; high-level, low-level and mixed waste management and disposal; public policy and program management; decontamination and decommissioning environmental restoration; and excess weapons materials disposition.
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
A look inside NIST’s work to optimize cancer treatment and radiation dosimetry
In an article just published by the Taking Measure blog of the National Institute of Standards and Technology, Stephen Russek—who leads the Imaging Physics Project in the Magnetic Imaging Group at NIST and codirects the MRI Biomarker Measurement Service—describes his team’s work using phantom stand-ins for human tissue.
Thomas E. Booth
Nuclear Science and Engineering | Volume 154 | Number 1 | September 2006 | Pages 48-62
Technical Paper | doi.org/10.13182/NSE05-05
Articles are hosted by Taylor and Francis Online.
A method for simultaneously obtaining the two largest eigenvalues and their associated eigenfunctions is demonstrated mathematically and empirically. The method uses estimates of the eigenvalue in two different regions rather than the single estimate traditionally used. The method can be generalized to obtain the several largest eigenfunctions, if those are desired as well. Additionally, it is shown that using multiple estimates of the eigenvalues accelerates the convergence of the eigenfunctions.
