A benchmark for Monte Carlo simulations in gamma-ray spectrometry Part II: True coincidence summing correction factors.

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.

Risk assessment for the optimization of the grid of a telemetric network monitoring system.

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.

Coincidence summing corrections using PENELOPE/PENNUC Monte Carlo code for volume sources of different densities.

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.

A benchmark for Monte Carlo simulation in gamma-ray spectrometry.

Monte Carlo (MC) simulation is widely used in gamma-ray spectrometry, however, its implementation is not always easy and can provide erroneous results. The present action provides a benchmark for several MC software for selected cases. The examples are based on simple geometries, two types of germanium detectors and four kinds of sources, to mimic eight typical measurement conditions.