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
Latest News
ANS joins others in seeking to discuss SNF/HLW impasse
The American Nuclear Society joined seven other organizations to send a letter to Energy Secretary Christopher Wright on July 8, asking to meet with him to discuss “the restoration of a highly functioning program to meet DOE’s legal responsibility to manage and dispose of the nation’s commercial and legacy defense spent nuclear fuel (SNF) and high-level radioactive waste (HLW).”
H. Park, D. A. Knoll, C. K. Newman
Nuclear Science and Engineering | Volume 172 | Number 1 | September 2012 | Pages 52-65
Technical Paper | doi.org/10.13182/NSE11-81
Articles are hosted by Taylor and Francis Online.
We present a nonlinear acceleration algorithm for a transport criticality problem. The algorithm combines the well-known nonlinear diffusion acceleration (NDA) algorithm with a recently developed, Newton-based nonlinear criticality acceleration (NCA) algorithm. The algorithm first employs NDA to reduce the system to scalar flux, then NCA is applied to the resulting drift-diffusion system. We apply a nonlinear elimination technique to eliminate the eigenvalue constraint equation from the Jacobian matrix. Numerical results show that the algorithm can reduce the CPU time by a factor of 30 to 400 compared to traditional power iterations (PIs) combined with standard source iterations and by a factor of 3 to 5 compared to application of NDA combined with inner PIs.