Nonintrusive depth estimation of buried radioactive wastes using ground penetrating radar and a gamma ray detector

Ukaegbu, I. K., Gamage, K. A.A. and Aspinall, M. D. (2019) Nonintrusive depth estimation of buried radioactive wastes using ground penetrating radar and a gamma ray detector. Remote Sensing, 11(2), 141. (doi: 10.3390/rs11020141)

Abstract

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

• Item Type: Articles
• Additional Information: This research was funded by the Engineering and Physical Sciences Research Council, U.K. (EP/N509231/1) and the Nuclear Decommissioning Authority, U.K. The APC was funded by Lancaster University
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Gamage, Professor Kelum
• Authors: Ukaegbu, I. K., Gamage, K. A.A., and Aspinall, M. D.
• College/School: College of Science and Engineering > School of Engineering > Systems Power and Energy
• Journal Name: Remote Sensing
• Publisher: MDPI
• ISSN: 2072-4292
• ISSN (Online): 2072-4292
• Published Online: 12 January 2019
• Copyright Holders: Copyright © 2019 The Authors
• First Published: First published in Remote Sensing 11(2):141
• Publisher Policy: Reproduced under a Creative Commons License