ABSTRACT
The goal of this study is to provide a benchmark for the use of Monte Carlo simulation when applied to coincidence summing corrections. The examples are based on simple geometries: two types of germanium detectors and four kinds of sources, to mimic eight typical measurement conditions. The coincidence corrective factors are computed for four radionuclides. The exercise input files and calculation results with practical recommendations are made available for new users on a dedicated webpage.
ABSTRACT
The goal of this work was to develop a methodology for risk assessment in case of an accident originating from a nuclear power plant, and consequently, to improve the relevant radiation monitoring network. In specific, the study involved risk estimation in Greece from a transboundary nuclear power plant accident. The tool employed was JRODOS (Java-based Real-time Decision Support), which is a system for off-site emergency management of radioactive material in the environment. This tool, widely used to generate and study scenarios for nuclear accidents worldwide, provides valuable insight to facilitate emergency preparedness and response. The probability of the plume arriving at numerous regions within the country was calculated, along with the maximum dose rates in case of transport. A risk assessment was performed, and geographical regions were prioritized in terms of risk-based environmental radioactivity burden. A total of 29 administrative districts were identified as low to medium-risk regions. Acquired results were used to determine the optimal spatial distribution of detectors for upgrading the existing monitoring network of environmental radioactivity.
Subject(s)
Civil Defense , Radiation Monitoring , Radioactive Hazard Release , Radiation Monitoring/methods , Nuclear Power Plants , Risk AssessmentABSTRACT
This work aims at providing a Monte-Carlo based methodology for calculating true coincidence correction (TCC) factors for volume sources of varying density. All simulations were carried out using the most recent version of Monte Carlo code PENELOPE. The main program PENMAIN was used for the calculation of full energy peak efficiencies. The subroutine PENNUC was utilized for the same calculation while taking summation effects into account. It was applied to Eu-152 and Cs-134 volume sources of 9 different densities, whilst the effect of the source's density on the TCC factor was investigated. There are differences between current results and the ones calculated by the TrueCoinc software. A relative bias up to 15% was observed, while the mean relative bias was 4.5%. The different approaches between the two codes could explain these deviations.
