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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.
Austin Williams, Lance Drouet, Sandra Bogetic
Nuclear Science and Engineering | Volume 200 | Number 4 | April 2026 | Pages 976-990
Regular Research Article | doi.org/10.1080/00295639.2025.2500259
Articles are hosted by Taylor and Francis Online.
A key characteristic in neutron transport is nuclear data. Cross-section uncertainty is not used in MCNP6.3 to propagate response uncertainty without external analysis. The TOol For Fast Error Estimation (TOFFEE) is a Python-based code developed to automate the propagation of cross-section uncertainty for MCNP evaluations. TOFFEE implements the sandwich rule to calculate the uncertainty from cross sections with sensitivity coefficients from MCNP6.3 and ENDF/B covariance data. In this paper, TOFFEE has been tested with benchmark experiments, and it has been compared to the uncertainty quantification capabilities of Sampler and TSUNAMI, within SCALE, to verify the application’s capabilities.