Improving Activity Estimation in Passive Gamma Scanning for Radioactive Waste Drums

• Main Authors: Vax E., Marcus E., Mazor T., Kadmon Y., Osovizky A.
• Format: Article
• Language: English
• Published: EDP Sciences 2020-01-01
• Series: EPJ Web of Conferences
• Subjects: radioactive waste drum; alternating projections; projection algorithms; maximum likelihood estimation; passive scanning
• Online Access: https://www.epj-conferences.org/articles/epjconf/pdf/2020/01/epjconf_animma2019_06010.pdf

A method to improve radioactive waste drum activity estimation in Segmented Gamma Scanning (SGS) systems was developed for homogenous content. We describe a method to quantify the activity of spatially distributed gamma-emitting isotopes (‘hot spots’) in homogenous content waste drums without the use of a collimator. Instead of averaging all the detector's readings we treat it as many different spatial samples as if we have multiple detectors surrounding the waste drum ("virtual detectors"). From these readings, we form a general linear model. Next, we derive the Maximum Likelihood Estimator (MLE) for the multiple sources position and activity. We solve this hyper-dimensional search problem using an Alternating Projections (AP) technique which transforms the problem into a simpler one-dimensional maximization problem. We tested this method using a mathematical simulation with a various number of sources, at random activities and positions for several energy bands. The preliminary results are consistent and show large improvement of the accuracy with comparison to industrial SGS systems and the same accuracy as new methods which exploits the spatial samples. Furthermore, since this method eliminates the need for heavy led collimator, none of the sources is blocked for the whole measurement period, which provides increased count rates and decreases the total measurement time.