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
DTRA’s advancements in nuclear and radiological detection
A new, more complex nuclear age has begun. Echoing the tensions of the Cold War amid rapidly evolving nuclear and radiological threats, preparedness in the modern age is a contest of scientific innovation. The Research and Development Directorate (RD) at the Defense Threat Reduction Agency (DTRA) is charged with winning this contest.
Nam Zin Cho, Seungsu Yuk, Han Jong Yoo, Sunghwan Yun
Nuclear Science and Engineering | Volume 175 | Number 3 | November 2013 | Pages 227-238
Technical Paper | doi.org/10.13182/NSE12-68
Articles are hosted by Taylor and Francis Online.
In current practice of nuclear reactor design analysis, the whole-core diffusion nodal method is used in which nodal parameters are provided by a single-assembly lattice physics calculation with the zero net current boundary condition. Thus, the whole-core solution is not transport, because the interassembly transport effect is not incorporated. In this paper, the overlapping local/global iteration framework that removes the limitation of the current method is described. It consists of two-level iterative computations: half-assembly overlapping local problems embedded in a global problem. The local problem can employ heterogeneous fine-group deterministic or continuous-energy stochastic (Monte Carlo) transport methods, while the global problem is a homogenized coarse-group transport-equivalent model based on partial current-based coarse-mesh finite difference methodology. The method is tested on several highly heterogeneous multislab problems and a two-dimensional small core problem, with encouraging results.