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.
Robin P. Gardner, Lianyan Liu
Nuclear Science and Engineering | Volume 133 | Number 1 | September 1999 | Pages 80-91
Technical Paper | doi.org/10.13182/NSE99-A2074
Articles are hosted by Taylor and Francis Online.
The generation of first estimate geometry-independent fine-mesh three-dimensional importance maps with simple one-dimensional diffusion models is demonstrated for the Monte Carlo simulation of the neutron porosity oil well logging tool response benchmark problem. By combining the approach of using simple one-dimensional steady-state diffusion models for calculating neutron adjoint flux with the geometry-independent fine-mesh-based Monte Carlo importance approach previously developed, an automated and efficient variance reduction method is obtained for this specific problem. A surprising result is that the converged figures of merit after iteration are consistently larger when the initial importance map is based on the one-dimensional diffusion model rather than that obtained from an analog Monte Carlo simulation.