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
June 2026
Nuclear Technology
March 2026
Fusion Science and Technology
May 2026
Latest News
DOE selects first companies for nuclear launch pad
The Department of Energy’s Office of Nuclear Energy and the National Reactor Innovation Center have announced their first selections for the Nuclear Energy Launch Pad: three companies developing microreactors and one developing fuel supply.
The four companies—Deployable Energy, General Matter, NuCube Energy, and Radiant Industries—were selected from the initial pool of Reactor Pilot Program and Fuel Line Pilot Program applicants, the two precursor programs to the launch pad.
M. Hursin, B. Collins, Y. Xu, T. Downar
Nuclear Science and Engineering | Volume 176 | Number 2 | February 2014 | Pages 186-200
Technical Paper | doi.org/10.13182/NSE12-4
Articles are hosted by Taylor and Francis Online.
During the last several years, a class of algorithms has been developed based on two-dimensional–one-dimensional (2D-1D) decomposition of the reactor transport problem. The current 2D-1D algorithm implemented in the DeCART (Deterministic Core Analysis based on Ray Tracing) code solves a set of coupled 2D planar transport and 1D axial diffusion equations. This method has been successfully applied to several light water reactor analysis problems. However, applications with strong axial heterogeneities have exposed the limitations of the current diffusion solvers used for the axial solution. The work reported in this paper is the implementation of a discrete ordinates (Sn)-based axial solver in DeCART. An Sn solver is chosen to preserve the consistency of the angular discretization between the radial method of characteristics and axial solvers. This paper presents the derivation of the nodal expansion method (NEM)-Sn equations and its implementation in DeCART. The subplane spatial refinement method is introduced to reduce the computational cost and improve the accuracy of the calculations. The NEM-Sn axial solver is tested using the C5G7 benchmark. The DeCART results with the axial diffusion solver shows keff errors of approximately −95, −74, and −110 pcm for the unrodded configuration, rodded configuration A, and rodded configuration B, respectively. These errors decrease to approximately −40, −11, and −12 pcm by using the NEM-Sn solver. In terms of pin power distribution, the use of the NEM-Sn solver has a small effect, except for the heavily rodded configuration. The implementation of the subplane scheme makes it possible to maintain a coarse axial mesh and therefore to reduce the computational cost of the three-dimensional calculations without reducing the accuracy of the solution.