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
Feb 2026
Jul 2025
Latest Journal Issues
Nuclear Science and Engineering
February 2026
Nuclear Technology
January 2026
Fusion Science and Technology
Latest News
Uranium prices reach highest level since February 2024
The end-of-January spot price for uranium was $94.28 per pound, according to uranium fuel provider Cameco. That was the highest spot price posted by the company since the $95.00 per pound it listed at the end of February 2024. Spot prices during 2025 ranged from a low of $64.23 per pound at the end of March to a high of $82.63 per pound at the end of September.
Jean Tommasi, Maxence Maillot, Gérald Rimpault
Nuclear Science and Engineering | Volume 184 | Number 2 | October 2016 | Pages 174-189
Technical Paper | doi.org/10.13182/NSE16-4
Articles are hosted by Taylor and Francis Online.
In neutron chain systems with material symmetries, various k-eigenvalues of the neutron balance equation beyond the dominant one may be degenerate. Eigenfunctions can be partitioned into several classes according to their invariance properties with respect to the symmetry operations (mirror symmetries and rotations) keeping the material distribution in the system unchanged. Their calculation can be limited to a fraction of the system (sector) provided that innovative boundary conditions matching the symmetry classes are used, and whole-system eigenfunctions can then be unfolded from the solutions obtained over the sector. With power iteration as the method for searching k-eigenvalues, this use of the material symmetries to split the global problem into a variety of smaller-sized problems has several computational advantages: lower computation times and memory requirements, increased dominance ratios, lowered possible degeneracies in each subproblem, and possible parallel (separated) treatment of the subproblems. The implementation is discussed in a companion paper using diffusion and transport theories.