Depth profiling 137Cs and 60Co non-intrusively for a suite of industrial shielding materials and at depths beyond 50mm

Adams, Jamie C.; Joyce, Malcolm J.; Mellor, Matthew

doi:10.1016/j.apradiso.2011.11.033

Cited by 8 publications

(11 citation statements)

References 5 publications

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“…In fact, the activity intensity of the Cs-137 used in this work was about 10 times weaker than that of the Cs-137 used in those studies. Hence, the maximum detectable depth of 21 cm for both weakly active 0.94-µCi Cs-137 and 0.69-µCi Co-60 sources buried in sand was indeed a significant improvement in comparison to existing methods [9][10][11][12][13][14][15][16]. Third, the proposed technique provided a much faster and more accurate estimation of depths up to the maximum detectable depth (i.e., 21 cm), which was achieved within 60 s, even for sources with a weak activity.…”

Section: Discussionmentioning

confidence: 83%

“…Traditional destructive methods, such as logging and core sampling, have been used for depth estimation; however, they are expensive and time-consuming [7,8]. Thus, various non-destructive techniques have been developed for remote-depth profiling including the relative attenuation method [9,10], principal component analysis (PCA) [11][12][13], and the approximate three-dimensional linear-attenuation method [14][15][16]. The relative attenuation method takes the relative difference in the attenuations of two primary peaks (i.e., the 32-keV X-ray and 662-keV gamma-ray peaks of Cs-137) in a measured spectrum to find the depth profile.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Bayesian Approach for Remote Depth Estimation of Buried Low-Level Radioactive Waste with a NaI(Tl) Detector

Kim

Lim

Park

et al. 2019

Sensors

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This study reports on the implementation of Bayesian inference to improve the estimation of remote-depth profiling for low-level radioactive contaminants with a low-resolution NaI(Tl) detector. In particular, we demonstrate that this approach offers results that are more reliable because it provides a mean value with a 95% credible interval by determining the probability distributions of the burial depth and activity of a radioisotope in a single measurement. To evaluate the proposed method, the simulation was compared with experimental measurements. The simulation showed that the proposed method was able to detect the depth of a Cs-137 point source buried below 60 cm in sand, with a 95% credible interval. The experiment also showed that the maximum detectable depths for weakly active 0.94-μCi Cs-137 and 0.69-μCi Co-60 sources buried in sand was 21 cm, providing an improved performance compared to existing methods. In addition, the maximum detectable depths hardly degraded, even with a reduced acquisition time of less than 60 s or with gain-shift effects; therefore, the proposed method is appropriate for the accurate and rapid non-intrusive localization of buried low-level radioactive contaminants during in situ measurement.

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Section: Discussionmentioning

confidence: 83%

Section: Introductionmentioning

confidence: 99%

A Bayesian Approach for Remote Depth Estimation of Buried Low-Level Radioactive Waste with a NaI(Tl) Detector

Kim

Lim

Park

et al. 2019

Sensors

View full text Add to dashboard Cite

show abstract

“…However, traditional methods of depth estimation such as core sampling and logging are slow and have limited spatial sampling extent because of their intrusive nature. Furthermore, the nonintrusive methods reported in [5,[7][8][9][10][11][12][13][14] are either based on regressional models whose parameters typically have no physical significance or are limited to specific radioactive sources. Also, other nonintrusive methods reported in [15,16] use specialised shielding and collimator arrangements while those that employ machine learning [17][18][19] require significant amount of data to train the algorithms.…”

Section: Introductionmentioning

confidence: 99%

Nonintrusive Depth Estimation of Buried Radioactive Wastes Using Ground Penetrating Radar and a Gamma Ray Detector

2019

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This study reports on the combination of data from a ground penetrating radar (GPR) and a gamma ray detector for nonintrusive depth estimation of buried radioactive sources. The use of the GPR was to enable the estimation of the material density required for the calculation of the depth of the source from the radiation data. Four different models for bulk density estimation were analysed using three materials, namely: sand, gravel and soil. The results showed that the GPR was able to estimate the bulk density of the three materials with an average error of 4.5%. The density estimates were then used together with gamma ray measurements to successfully estimate the depth of a 658 kBq ceasium-137 radioactive source buried in each of the three materials investigated. However, a linear correction factor needs to be applied to the depth estimates due to the deviation of the estimated depth from the measured depth as the depth increases. This new application of GPR will further extend the possible fields of application of this ubiquitous geophysical tool.

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“…Consequently, various remote depth profiling methods have been investigated and reported in literature. These include: the relative attenuation method [ 13 , 14 , 15 ] and principal component analysis (PCA) method [ 16 , 17 , 18 ]. The relative attenuation method exploits the relative difference in the attenuation of two prominent peaks (typically the X-ray and gamma photo peaks) in the measured energy spectrum of the buried radionuclide.…”

Section: Introductionmentioning

confidence: 99%

A Novel Method for Remote Depth Estimation of Buried Radioactive Contamination

Ukaegbu

Gamage

2018

Sensors

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Existing remote radioactive contamination depth estimation methods for buried radioactive wastes are either limited to less than 2 cm or are based on empirical models that require foreknowledge of the maximum penetrable depth of the contamination. These severely limits their usefulness in some real life subsurface contamination scenarios. Therefore, this work presents a novel remote depth estimation method that is based on an approximate three-dimensional linear attenuation model that exploits the benefits of using multiple measurements obtained from the surface of the material in which the contamination is buried using a radiation detector. Simulation results showed that the proposed method is able to detect the depth of caesium-137 and cobalt-60 contamination buried up to 40 cm in both sand and concrete. Furthermore, results from experiments show that the method is able to detect the depth of caesium-137 contamination buried up to 12 cm in sand. The lower maximum depth recorded in the experiment is due to limitations in the detector and the low activity of the caesium-137 source used. Nevertheless, both results demonstrate the superior capability of the proposed method compared to existing methods.

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Depth profiling 137Cs and 60Co non-intrusively for a suite of industrial shielding materials and at depths beyond 50mm

Cited by 8 publications

References 5 publications

A Bayesian Approach for Remote Depth Estimation of Buried Low-Level Radioactive Waste with a NaI(Tl) Detector

A Bayesian Approach for Remote Depth Estimation of Buried Low-Level Radioactive Waste with a NaI(Tl) Detector

Nonintrusive Depth Estimation of Buried Radioactive Wastes Using Ground Penetrating Radar and a Gamma Ray Detector

A Novel Method for Remote Depth Estimation of Buried Radioactive Contamination

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