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
Industry Update—February 2026
Here is a recap of recent industry happenings:
Supply chain contract signed for Aurora
Oklo, the California-based developer of the Aurora Powerhouse sodium-cooled fast-neutron reactor, has signed a contract with Siemens Energy that is meant to de-risk supply chain and production timeline challenges for Oklo. Under the terms, Siemens will design and deliver the power conversion system for the Powerhouse, which is to be deployed at Idaho National Laboratory.
M. R. Dorr, J. F. Painter, S. T. Perkins
Nuclear Science and Engineering | Volume 94 | Number 2 | October 1986 | Pages 157-166
Technical Paper | doi.org/10.13182/NSE86-A27450
Articles are hosted by Taylor and Francis Online.
A new algorithm for modeling charged-particle transport in a fully ionized plasma is presented. A standard multigroup discretization of the Fokker-Planck-Boltzmann equation is transport-corrected to implicitly include the anisotropic effects of both coulomb scattering and nuclear reactions. This allows the subsequent application of the Levermore flux-limited diffusion theory, which was originally developed for isotropic radiative transfer calculations. A finite differencing of the resulting spatial transport operator is constructed so as to yield centered and upwinded operators in the diffusion and free-streaming limits, respectively. The time integration is performed by the general purpose ordinary differential equation solver TORANAGA. This approach results in a highly vectorizable algorithm that has been implemented on the CRAY-1. Some numerical results are presented that compare this algorithm to the corresponding, but far more expensive, Monte Carlo calculations.