A Novel Method for Remote Depth Estimation of Buried Radioactive Contamination.
A Novel Method for Remote Depth Estimation of Buried Radioactive Contamination.
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DOI：
10.3390/s18020507
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发表时间：
2018-02-08
期刊：
影响因子：
--
通讯作者：
Gamage KAA
中科院分区：
文献类型：
--
作者：
Ukaegbu IK;Gamage KAA
现有的埋藏放射性废物的远程放射性污染深度估计方法要么限制在2厘米以下，要么基于需要预先知道污染的最大可穿透深度的经验模型。这些严重限制了它们在一些现实生活中的地下污染场景中的用处。因此，这项工作提出了一种新的远程深度估计方法，该方法基于近似的三维线性衰减模型，该模型利用了使用辐射探测器从污染被掩埋的材料表面获得的多次测量的好处。仿真结果表明，所提出的方法能够检测到埋在沙子和混凝土中40cm深的铯-137和钴-60污染。此外，实验结果表明，该方法能够探测到埋在沙子中12厘米深的铯-137污染。实验中记录的最大深度较低是由于探测器的限制和所使用的铯-137源的低活度。然而，这两个结果都表明，与现有方法相比，所提出的方法具有优越的性能。
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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影响因子：
1.8
作者：
Adams, Jamie C.;Joyce, Malcolm J.;Mellor, Matthew
通讯作者：
Mellor, Matthew
影响因子：
1.6
作者：
Shippen, Alan;Joyce, Malcolm J.
通讯作者：
Joyce, Malcolm J.
DOI：
10.3390/s17040790
发表时间：
2017-04-07
期刊：
Sensors (Basel, Switzerland)
影响因子：
--
作者：
Ukaegbu IK;Gamage KA
通讯作者：
Gamage KA
影响因子：
1.6
作者：
Adams, Jamie C.;Joyce, Malcolm J.;Mellor, Matthew
通讯作者：
Mellor, Matthew
影响因子：
1.2
作者：
Maeda, Koji;Sasaki, Shinji;Murata, Hirotoshi
通讯作者：
Murata, Hirotoshi