DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Jinhwan | ko |
dc.contributor.author | Lim, Kyung Taek | ko |
dc.contributor.author | Park, Kyungjin | ko |
dc.contributor.author | Cho, Gyuseong | ko |
dc.date.accessioned | 2020-01-30T07:20:16Z | - |
dc.date.available | 2020-01-30T07:20:16Z | - |
dc.date.created | 2019-12-31 | - |
dc.date.created | 2019-12-31 | - |
dc.date.created | 2019-12-31 | - |
dc.date.issued | 2019-12 | - |
dc.identifier.citation | SENSORS, v.19, no.24 | - |
dc.identifier.issn | 1424-8220 | - |
dc.identifier.uri | http://hdl.handle.net/10203/271922 | - |
dc.description.abstract | 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. | - |
dc.language | English | - |
dc.publisher | MDPI | - |
dc.title | A Bayesian Approach for Remote Depth Estimation of Buried Low-Level Radioactive Waste with a NaI(Tl) Detector | - |
dc.type | Article | - |
dc.identifier.wosid | 000517961400029 | - |
dc.identifier.scopusid | 2-s2.0-85076357247 | - |
dc.type.rims | ART | - |
dc.citation.volume | 19 | - |
dc.citation.issue | 24 | - |
dc.citation.publicationname | SENSORS | - |
dc.identifier.doi | 10.3390/s19245365 | - |
dc.contributor.localauthor | Cho, Gyuseong | - |
dc.description.isOpenAccess | Y | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | remote-depth profiling | - |
dc.subject.keywordAuthor | gamma spectral analysis | - |
dc.subject.keywordAuthor | Bayesian inference | - |
dc.subject.keywordAuthor | uncertainty estimation | - |
dc.subject.keywordAuthor | radioactive nuclear waste | - |
dc.subject.keywordAuthor | radiological characterization | - |
dc.subject.keywordAuthor | nuclear decommissioning | - |
dc.subject.keywordAuthor | radiation detection | - |
dc.subject.keywordAuthor | low-resolution detector | - |
dc.subject.keywordPlus | CS-137 | - |
dc.subject.keywordPlus | CO-60 | - |
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