Please use this identifier to cite or link to this item:
Appears in Collections:Biological and Environmental Sciences Journal Articles
Peer Review Status: Refereed
Title: Development of a neural network approach to characterise 226Ra contamination at legacy sites using gamma-ray spectra taken from boreholes
Author(s): Varley, Adam
Tyler, Andrew
Smith, Leslie
Dale, Paul
Contact Email:
Keywords: Borehole gammaspectroscopy
Radium contamination
Monte Carlo
Neural networks
Issue Date: Feb-2015
Date Deposited: 2-Jun-2015
Citation: Varley A, Tyler A, Smith L & Dale P (2015) Development of a neural network approach to characterise 226Ra contamination at legacy sites using gamma-ray spectra taken from boreholes. Journal of Environmental Radioactivity, 140, pp. 130-140.
Abstract: There are a large number of sites across the UK and the rest of the world that are known to be contaminated with226Ra owing to historical industrial and military activities. At some sites, where there is a realistic risk of contact with the general public there is a demand for proficient risk assessments to be undertaken. One of the governing factors that influence such assessments is the geometric nature of contamination particularly if hazardous high activity point sources are present. Often this type of radioactive particle is encountered at depths beyond the capabilities of surface gamma-ray techniques and so intrusive borehole methods provide a more suitable approach. However, reliable spectral processing methods to investigate the properties of the waste for this type of measurement have yet to be developed since a number of issues must first be confronted including: representative calibration spectra, variations in background activity and counting uncertainty. Here a novel method is proposed to tackle this issue based upon the interrogation of characteristic Monte Carlo calibration spectra using a combination of Principal Component Analysis and Artificial Neural Networks. The technique demonstrated that it could reliably distinguish spectra that contained contributions from point sources from those of background or dissociated contamination (homogenously distributed). The potential of the method was demonstrated by interpretation of borehole spectra collected at the Dalgety Bay headland, Fife, Scotland. Predictions concurred with intrusive surveys despite the realisation of relatively large uncertainties on activity and depth estimates. To reduce this uncertainty, a larger background sample and better spatial coverage of cores were required, alongside a higher volume better resolution detector.
DOI Link: 10.1016/j.jenvrad.2014.11.011
Rights: This article is open-access. Open access publishing allows free access to and distribution of published articles where the author retains copyright of their work by employing a Creative Commons attribution licence. Proper attribution of authorship and correct citation details should be given.
Licence URL(s):

Files in This Item:
File Description SizeFormat 
1-s2.0-S0265931X14003452-main.pdfFulltext - Published Version2.37 MBAdobe PDFView/Open

This item is protected by original copyright

A file in this item is licensed under a Creative Commons License Creative Commons

Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

The metadata of the records in the Repository are available under the CC0 public domain dedication: No Rights Reserved

If you believe that any material held in STORRE infringes copyright, please contact providing details and we will remove the Work from public display in STORRE and investigate your claim.