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 Nuclear Energy Conference & Expo (NECX)
August 24–27, 2026
Dallas, TX|Hilton Anatole
Latest Magazine Issues
Jul 2026
Jan 2026
2026
Latest Journal Issues
Nuclear Science and Engineering
August 2026
Nuclear Technology
July 2026
Fusion Science and Technology
Latest News
The deadline arrives: Checking in on the Reactor Pilot Program
On May 23, 2025, President Trump signed Executive Order 14301, “Reforming Nuclear Reactor Testing at the DOE,” which instructed the Department of Energy to create a Reactor Pilot Program (RPP)—a new system in which companies could pursue DOE authorization to build and test their first-of-a-kind nuclear technologies. EO 14301 set an ambitious goal for that program: three reactors achieving criticality by July 4, 2026.
Hui Zhang, E. E. Lewis
Nuclear Science and Engineering | Volume 137 | Number 1 | January 2001 | Pages 14-22
Technical Paper | doi.org/10.13182/NSE01-A2172
Articles are hosted by Taylor and Francis Online.
An adaptive grid method is presented for the solution of neutron diffusion problems in two dimensions. The primal hybrid finite elements employed in the variational nodal method are used to reduce the diffusion equation to a coupled set of elemental response matrices. An a posteriori error estimator is developed to indicate the magnitude of local errors stemming from the low-order elemental interface approximations. An iterative procedure is implemented in which p refinement is applied locally by increasing the polynomial order of the interface approximations. The automated algorithm utilizes the a posteriori estimator to achieve local error reductions until an acceptable level of accuracy is reached throughout the problem domain. Application to a series of X-Y benchmark problems indicates the reduction of computational effort achievable by replacing uniform with adaptive refinement of the spatial approximations.