Intercomparison of methods for coincidence summing corrections in gamma-ray spectrometry—part II (volume sources)

Lépy, Marie‐Christine; Altzitzoglou, T.; Anagnostakis, M.J.; Capogni, M.; Ceccatelli, A.; Felice, P. De; Djurašević, M.; Dryák, P.; Fazio, A.; Ferreux, L.; Giampaoli, A.; Han, Jeongran; Hurtado, Santiago; Kandić, Aleksandar; Kanisch, Günter; Karfopoulos, K.; Klemola, S; Kovář, Petr; Laubenstein, M.; Lee, Jang Hern; Lee, K.B.; Pierre, Sylvie; Carvalhal, G.; Sima, O.; Tạo, Châu Văn; Thanh, Tran Thien; Vidmar, T.; Vukanac, Ivana; Yang, Min

doi:10.1016/j.apradiso.2012.02.079

Cited by 39 publications

(10 citation statements)

References 16 publications

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“…If the correction factors of the individual software were compared with the mean of the three softwares the result would appear to be much more concurrent (3.7% deviation at the most). This approach has been used in several intercomparison studies [4][5][6]. However, it does not reveal how accurate softwares are, only how well they agree with each other.…”

Section: Resultsmentioning

confidence: 99%

“…Some previously conducted studies were designed in order to minimize differences by only comparing the theoretical correction factors (with the same detector model and decay data). Reasonable agreement between the softwares was achieved for pure γ-γ coincidence [4,5]. However, γ-X coincidences was found to be more difficult to correct for and large discrepancies were observed for some softwares [4][5][6].…”

Section: Introductionmentioning

confidence: 94%

“…Reasonable agreement between the softwares was achieved for pure γ-γ coincidence [4,5]. However, γ-X coincidences was found to be more difficult to correct for and large discrepancies were observed for some softwares [4][5][6]. This is highly unsatisfying and does not reveal which calculation code that can be considered as fit-for-purpose.…”

Section: Introductionmentioning

confidence: 98%

“…The calculation and comparison of correction factors for γ-γ and γ-X coincidences of 133 Ba and 152 Eu and different methods or softwares has been extensively investigated [4][5][6][7][8][9]. Agarwal et al [10,11] compares the correction factors of 125 Sb with MCNP to experimental data.…”

Section: Introductionmentioning

confidence: 99%

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Experimental validation of corrections factors for γ–γ and γ–X coincidence summing of 133Ba, 152Eu, and 125Sb in volume sources

Jönsson

Kastlander

Vidmar

et al. 2019

J Radioanal Nucl Chem

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True coincidence summing correction factors for 133 Ba, 152 Eu and 125 Sb were determined experimentally for a small volume source and compared with correction factors obtained with three softwares (EFFTRAN-X, GESPECOR and VGSL). The radionuclides investigated have a relatively challenging decay scheme and their spectra are known to suffer from losses due to summation (γ-γ, γ-X and X-X) when measured at close distances on a HPGe detector sensitive to low energy photons. This study shows that the softwares were in good agreement with each other and the experimental data and the calculated activity was consistent with the activity in the volume source.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

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Experimental validation of corrections factors for γ–γ and γ–X coincidence summing of 133Ba, 152Eu, and 125Sb in volume sources

Jönsson

Kastlander

Vidmar

et al. 2019

J Radioanal Nucl Chem

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“…The extension from point to volume sources was achieved by the "LS-curve" method (Vidmar and Korun, 2006;Vidmar and Kanisch, 2010;Lépy et al, 2012). Approximate total efficiency curves required by such calculations were obtained with the gamma-ray spectrometry simulation tool GESPECOR (Sima et al, 2001).…”

Section: Appendix a Details Of Gamma-ray Spectrometric Analysis With mentioning

confidence: 99%

Does the Fukushima NPP disaster affect the caesium activity of North Atlantic Ocean fish?

Kanisch¹,

Aust²

2013

Biogeosciences

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Fillet samples of marine fish collected from the East/West Greenland currents (GC) and from the Baltic Sea (BS) have been investigated by gamma-ray spectrometry within the regular German monitoring programme. In samples of the second half of 2011, ¹³⁴Cs traces have been detected that are suggested to originate from the Fukushima fallout that was deposited in March/April 2011 over the northern North Atlantic and accumulated by fish. The radionuclide ¹³⁴Cs (half-life 2 yr) was indeed detected with quite small activities at about 0.0036 Bq kg⁻¹ w.w. Existing box models describing the transport of Cs within seawater boxes of the northeast Atlantic allowed for estimation of ¹³⁴Cs contributions from other sources, i.e. from the Chernobyl fallout and from discharges by the two major European nuclear reprocessing plants; both were negligible around Greenland, while for the Chernobyl fallout a small ¹³⁴Cs background contribution to BS fish was estimated. Model results confirmed the level of ¹³⁴C measured in BS fish and showed its maximum to have occurred in winter 2011/2012 followed by a continuous decrease. It was also determined that ¹³⁴Cs activity, but not that of ¹³⁴Cs, showed a significant negative correlation with sampling depth (150–400 m) of GC fish; this strengthens our Fukushima fallout assumption. As a result, the Fukushima fallout in these sea areas only marginally enhanced (GC: 4%; BS: 0.1%) pre-Fukushima levels of individual dose rates received by human fish consumers; the addition was around 0.001 μSv following the consumption of 10 kg of fish per year, which is not expected to cause concern according to present guidelines for radiation protection

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Efficiency Calculation of Gamma Detectors byMonteCarlo Methods

Sima

2012

Encyclopedia of Analytical Chemistry

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γ‐Ray spectrometry is a powerful nondestructive multielemental analysis technique. Its quantitative application requires efficiency calibration. Among the methods available for the computation of the efficiency calibration curve, Monte Carlo simulation is ever increasing in popularity. The need for Monte Carlo simulation is the consequence of the inability of experimental calibration to cope with the broader scope and measuring configurations (shape, volume, and matrices of the samples), with the enhanced coincidence‐summing nuclide specific effects (favored by the current tendency to use high‐efficiency detectors) and with the desired performance parameters (detection limit and uncertainty) met in present‐day applications of γ‐ray spectrometry. The availability of a variety of Monte Carlo packages that can be applied to efficiency computation, several of them user friendly indeed, enlarged the class of potential users of this method. While experimental calibration remains the preferred method in the case of point sources and specific volume sources, such as solutions, it is the flexibility of Monte Carlo calculation that can provide a comprehensive calibration of γ‐ray detectors for a broad range of applications. In this article, the principles of Monte Carlo method are introduced, the applications to detector simulation are presented, and the solutions of typical problems in the calibration of γ‐spectrometry systems are reviewed.

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Intercomparison of methods for coincidence summing corrections in gamma-ray spectrometry—part II (volume sources)

Cited by 39 publications

References 16 publications

Experimental validation of corrections factors for γ–γ and γ–X coincidence summing of 133Ba, 152Eu, and 125Sb in volume sources

Experimental validation of corrections factors for γ–γ and γ–X coincidence summing of 133Ba, 152Eu, and 125Sb in volume sources

Does the Fukushima NPP disaster affect the caesium activity of North Atlantic Ocean fish?

Efficiency Calculation of Gamma Detectors byMonteCarlo Methods

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