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
Apr 2026
Jan 2026
Latest Journal Issues
Nuclear Science and Engineering
May 2026
Nuclear Technology
February 2026
Fusion Science and Technology
Latest News
Shine receives $263M conditional DOE loan to complete isotope facility
Fusion technology company Shine has been issued a conditional commitment for a loan of up to $263 million by the Department of Energy’s Office of Energy Dominance Financing (EDF) to support the construction of the company’s medical isotope production facility in Janesville, Wis.
Martin Frank, Jonas Kusch, Thomas Camminady, Cory D. Hauck
Nuclear Science and Engineering | Volume 194 | Number 11 | November 2020 | Pages 971-988
Technical Paper | doi.org/10.1080/00295639.2020.1730665
Articles are hosted by Taylor and Francis Online.
Solving the radiative transfer equation with the discrete ordinates (S) method leads to a nonphysical imprint of the chosen quadrature set on the solution. To mitigate these so-called ray effects, we propose a modification of the S method that we call artificial scattering S (as-S). The method adds an artificial forward-peaked scattering operator that generates angular diffusion to the solution and thereby mitigates ray effects. Similar to artificial viscosity for spatial discretizations, the additional term vanishes as the number of ordinates approaches infinity. Our method allows an efficient implementation of explicit and implicit time integration according to standard S solver technology. For two test cases, we demonstrate a significant reduction of error for the as-S method when compared to the standard S method, both for explicit and implicit computations. Furthermore, we show that a prescribed numerical precision can be reached with less memory due to the reduction in the number of ordinates.