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.
Thayz Gomes Ferreira, Alexis Jinaphanh, Davide Mancusi, Andrea Zoia
Nuclear Science and Engineering | Volume 200 | Number 4 | April 2026 | Pages 943-975
Regular Research Article | doi.org/10.1080/00295639.2025.2496859
Articles are hosted by Taylor and Francis Online.
In this work, we examine the behavior of zero-variance Monte Carlo games for radiation shielding problems in the presence of neutron multiplication, whose prominent application is the analysis of in-core and ex-core detector responses during reactor start-up. Prompted by previous investigations, which had shown that the conflict between the importance of the fissile regions and the importance of the detector might lead to numerical instabilities in Consistent Adjoint-Driven Importance Sampling (CADIS) strategies, we set out to explore these techniques within a simple benchmark configuration where exact zero-variance sampling can be implemented. The configurations examined here do not display any of the instabilities observed for CADIS-like schemes including neutron multiplication, which might be due to the use of branchless sampling for the collision events. Furthermore, our findings establish a clear framework that can be more broadly applied for the analysis of the robustness of ideal CADIS schemes.