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
March 2026
Fusion Science and Technology
Latest News
DOE awards ANS-backed workforce consortium $19.2M
The Department of Energy’s Office of Nuclear Energy recently awarded about $49.7 million to 10 university-led projects aiming to develop nuclear workforce training programs around the country.
DOE-NE issued its largest award, $19.2 million, to the newly formed Great Lakes Partnership to Enhance the Nuclear Workforce (GLP). This regional consortium, which is led by the University of Toledo and includes the American Nuclear Society, will use the funds to fill a variety of existing gaps in the nuclear workforce pipeline.
Joel A. Kulesza, Roger L. Martz
Nuclear Technology | Volume 195 | Number 1 | July 2016 | Pages 55-70
Technical Paper | doi.org/10.13182/NT15-122
Articles are hosted by Taylor and Francis Online.
This paper provides results for calculations performed using MCNP6’s unstructured mesh (UM) capabilities based on the three problems described in the Kobayashi benchmark suite. These calculations are performed to provide a comprehensive and consistent basis for the verification and validation of MCNP6’s constructive solid geometry (CSG) and UM neutron transport capabilities relative to a well-known analytic benchmark. First, preexisting MCNP5 CSG models are updated and reexecuted to form a basis of comparison with UM for both the consistency of the numeric results and speed of execution. Next, a series of UM calculations is performed using first- and second-order tetrahedral and hexahedral elements with mesh generated using Abaqus. In addition, a different first-order tetrahedral mesh is generated with Attila4MC in order to investigate the effect on the results. When executed, the results for both CSG and UM agree among themselves and with the benchmark quantities within reasonable statistical fluctuations (at worst, the results agree within 2σ or 10% but generally within 1σ or 5%) and recognizing from historical work that improved agreement is possible with additional variance-reduction effort. As expected, for the simple geometries herein, we find the CSG calculations completing approximately ten times faster than the comparable fastest UM calculations. We find minor speed differences (~1%) between multigroup and continuous-energy nuclear data and significant speed differences (factor ~100) between different element types. As such, the timing results support the recommendation that users run with the simplest UM element type that adequately represents the problem geometry, ideally first-order hexahedra, and with the most convenient nuclear data energy treatment.