Calculation of HPGe efficiency for environmental samples: comparison of EFFTRAN and GEANT4

Nikolić, Jelena Krneta; Vidmar, T.; Joković, D.; Rajačić, Milica; Todorović, Dragana

doi:10.1016/j.nima.2014.06.044

Cited by 37 publications

(10 citation statements)

References 11 publications

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“…is was achieved by fitting the experimental efficiencies with a function given in (5). is calibration curve was used to calculate the efficiencies for the energies that are emitted by the radionuclides contained in the reference samples: …”

Section: Resultsmentioning

confidence: 99%

“…In this way, the uncertainty can be estimated to be around 1% for crystal diameter and length, and crystal cavity diameter and length. According to this estimation, the contribution u D can be obtained by combining these uncertainties as a square root of sum of squares [5].…”

Section: Semiempirical Efficiency Calibration: Efftran and Mefftranmentioning

confidence: 99%

“…In that case, the calculations conducted in the laboratory produced results that differ from the experimental ones for 2-3%. [5].…”

Section: Journal Of Spectroscopymentioning

confidence: 99%

“…Monte Carlo simulation codes are developed to simulate the response of complex particle detectors and for variety of different high energy and nuclear interactions [4]. In case of gamma spectrometry, these codes need defining appropriate processes for interaction of gamma photons with the detector and the corresponding database used in the development of the application for the particular detector, which may be time-consuming and may require proficiency in programming language [5]. Once an application is developed, the use is relatively easy and the results are straightforward.…”

Section: Introductionmentioning

confidence: 99%

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Semiempirical Efficiency Calibration in Semiconductor HPGe Gamma-Ray Spectroscopy

Nikolić

Rajačić

Todorović

et al. 2018

Journal of Spectroscopy

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One of the main problems in quantitative gamma-ray spectroscopy is the determination of detection efficiency, for different energies, source-detector geometries, and composition of samples or sources. ere are, in principle, three approaches to this issue: experimental, numerical, and semiempirical. Semiempirical approach is based on the calculation of the efficiency for the measured sample on the basis of an experimental efficiency measured on the same detector, but with a calibration source that can be of different size, geometry, density, or composition-the so-called efficiency transfer. e aim of this paper is to analyze the semiempirical approach, using EFFTRAN and MEFFTRAN software as a typical example. ese software were used in the Department of Radiation and Environmental Protection, Vinča Institute of Nuclear Sciences, on three HPGe detectors. e results were compared to the experimentally obtained efficiency, and further validation is performed by measuring reference materials issued within the framework of several interlaboratory intercomparisons. e analysis of the results showed that the efficiency transfer produces good results with the discrepancies within the limits of the measurement uncertainty. Also, for intercomparison measurement, u test criterion for the trueness of the result was applied showing that the majority of the obtained results were acceptable. Some difficulties were identified, and the ways to overcome them were discussed.

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Section: Resultsmentioning

confidence: 99%

Section: Semiempirical Efficiency Calibration: Efftran and Mefftranmentioning

confidence: 99%

“…In that case, the calculations conducted in the laboratory produced results that differ from the experimental ones for 2-3%. [5].…”

Section: Journal Of Spectroscopymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Semiempirical Efficiency Calibration in Semiconductor HPGe Gamma-Ray Spectroscopy

Nikolić

Rajačić

Todorović

et al. 2018

Journal of Spectroscopy

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“…One of the main concerns in gamma spectrometry is the proper characterization of the efficiency curve in the energy range of interest for environmental radioactivity measurements. In this frame, Monte Carlo (MC) methods are powerful tools not only for the efficiency determination (Blank et al, 2015;Eren et al, 2015;Conti et al, 2013;Nikolic et al, 2014;Salvat et al, 2011;Agostinelli et al, 2003), but also for dead layer estimation (Chham et al, 2015;Andreotti et al, 2014;Ródenas et al, 2007), uncertainty analysis or true coincidence summing analysis Lépy et al, 2012). Some of the data required for the detector simulation are found in the certificate provided by the manufacturer, where the main characteristics are described.…”

Section: Introductionmentioning

confidence: 99%

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

Gallardo

Querol

Ortiz

et al. 2015

Radiation Physics and Chemistry

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ElsevierGallardo Bermell, S.; Querol Vives, A.; Ortiz Moragón, J.; Ródenas Diago, J.; Verdú Martín, GJ.; Villanueva López, JF. (2015). Uncertainty analysis in environmental radioactivity measurements using the Monte Carlo code MCNP5. Radiation Physics and Chemistry. 116:214-218. doi:10.1016/j.radphyschem.2015.05.023. Uncertainty analysis in environmental radioactivity measurements using the Monte Carlo code MCNP5 ABSTRACTHigh 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).

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Detection efficiency calculations using Geant4 for a broad-energy germanium gamma spectrometer

Liu

Ungar

Pierce

et al. 2017

J Radioanal Nucl Chem

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Calculation of HPGe efficiency for environmental samples: comparison of EFFTRAN and GEANT4

Cited by 37 publications

References 11 publications

Semiempirical Efficiency Calibration in Semiconductor HPGe Gamma-Ray Spectroscopy

Semiempirical Efficiency Calibration in Semiconductor HPGe Gamma-Ray Spectroscopy

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

Detection efficiency calculations using Geant4 for a broad-energy germanium gamma spectrometer

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