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
2026 ANS Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
Latest Magazine Issues
Mar 2026
Jul 2025
Latest Journal Issues
Nuclear Science and Engineering
March 2026
Nuclear Technology
February 2026
Fusion Science and Technology
January 2026
Latest News
ORNL–General Atomics partnership on ceramic matrix composites
A memorandum of understanding has been signed by Oak Ridge National Laboratory and General Atomics Electromagnetic Systems (GA-EMS) with the objective of working together on advanced ceramic matrix composite materials for applications in extreme environments. Materials that can withstand extreme temperatures, radiation, corrosion, and mechanical stress are required in aerospace, defense, energy, and other sectors.
According to the agreement, the San Diego–based GA-EMS will use resources from ORNL’s Manufacturing Demonstration Facility to develop “scalable, efficient manufacturing techniques for extreme environment materials including precursors, fibers, composites, and coatings utilized in carbon/carbon (C/C), carbon/silicon carbide (C/SiC), and SiC/SiC composite systems.”
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.
