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Effectiveness of Radiation Transport Variance Reduction Methods for Wide-Area Environmental Contamination Assay Applications

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

This study compares the accuracy, efficiency, and reliability of variance reduction (VR) methods for Monte Carlo radiation transport simulations involving wide-area ground plane (i.e., “surface”) and buried (i.e., “volumetric”) gamma source emissions from environmental soil. The simulation models are idealized external exposure scenarios intended as a basis for deriving site-specific dose-based or carcinogenic risk–based regulatory limits in the radiological site remediation process. These simulations are computationally resource intensive since particle tracks are transported from an extremely large source region to a relatively small detector region. For each simulation, several VR methods are compared with metrics of accuracy, efficiency, and reliability. The MCNP deterministic transport (DXTRAN) VR method was most effective for problems involving sources emitting low-energy gamma rays, and a coupled multicode method was more effective for problems involving sources emitting higher-energy gamma rays that undergo significant attenuation in the soil.

Original languageEnglish
Pages (from-to)2157-2173
Number of pages17
JournalNuclear Science and Engineering
Volume198
Issue number11
DOIs
StatePublished - 2024
Externally publishedYes

Funding

Special thanks are due Seth Johnson (ORNL High-Performance Computing Methods for Nuclear Applications Group) for providing ongoing technical advice throughout this effort. In addition, the authors would like to thank the ORNL Nuclear Energy and Fuel Cycle Division for the allocation of parallel computing resources.

Keywords

  • Monte Carlo
  • environmental assay
  • gamma spectrometry
  • radiation transport
  • variance reduction

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