Uncertainty analysis in environmental radioactivity measurements using the Monte Carlo code MCNP5

High Purity Germanium (HPGe) detectors are widely used for environmental radioactivity measurements due to their excellent energy resolution. Monte Carlo (MC) codes are a useful tool to complement experimental measurements in calibration procedures at the laboratory. However, the efficiency curve of...

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Detalles Bibliográficos
Autores: Gallardo Bermell, Sergio|||0000-0002-3703-9983, Ródenas Diago, José|||0000-0003-3283-9188, Verdú Martín, Gumersindo Jesús|||0000-0001-5098-080X, Villanueva López, José Felipe|||0000-0002-7684-6884, Querol Vives, Andrea, Ortiz Moragón, Josefina
Tipo de recurso: artículo
Fecha de publicación:2015
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/65523
Acceso en línea:https://riunet.upv.es/handle/10251/65523
Access Level:acceso abierto
Palabra clave:HPGe detector
Monte Carlo
Efficiency
Uncertainties
ESTADISTICA E INVESTIGACION OPERATIVA
INGENIERIA NUCLEAR
Descripción
Sumario:High Purity Germanium (HPGe) detectors are widely used for environmental radioactivity measurements due to their excellent energy resolution. Monte Carlo (MC) codes are a useful tool to complement experimental measurements in calibration procedures at the laboratory. However, the efficiency curve of the detector can vary due to uncertainties associated with measurements. These uncertainties can be classified into some categories: geometrical parameters of the measurement (distance source-detector, volume of the source), properties of the radiation source (radionuclide activity, branching ratio), and detector characteristics (Ge dead layer, active volume, end cap thickness). The Monte Carlo simulation can be also affected by other kind of uncertainties mainly related to cross sections and to the calculation itself. Normally, all these uncertainties are not well known and it is required a deep analysis to determine their effect on the detector efficiency. In this work, the Noether-Wilks formula is used to carry out the uncertainty analysis. A Probability Density Function (PDF) is assigned to each variable involved in the sampling process. The size of the sampling is determined from the characteristics of the tolerance intervals by applying the Noether Wilks formula. Results of the analysis transform the efficiency curve into a region of possible values into the tolerance intervals. Results show a good agreement between experimental measurements and simulations for two different matrices (water and sand).