A new algorithm for estimating radioxenon concentrations
Introduction
Noble gas systems have been used since the late 1990s to detect and quantify four radioactive isotopes of xenon (131mXe, 133mXe, 133Xe, and 135Xe) that are produced in a nuclear explosion (Axelsson and Ringbom, 2003; Bowyer et al., 1998; Fontaine et al., 2004). The International Noble Gas Experiment (INGE) was launched in 1999 to promote the development of autonomous systems for the measurement of xenon radioisotopes in the atmosphere (Auer et al., 2004; Bowyer et al., 1998, 2002; Saey and De Geer, 2005; Wernsperger and Schlosser, 2004). These noble gas systems process air to remove the non-xenon components and concentrate the xenon gas. The concentration step is necessary because xenon occurs at about 0.087 ppm in the atmosphere (Glueckauf, 1951).
Beta-gamma coincidence detectors are utilized by most current radioxenon systems (Dubasov et al., 2005; Ringbom et al., 2003, 2017) and new radioxenon systems under development (Chernov et al., 2021; Hayes et al., 2018; Le Petit et al., 2015; TBE, 2020). The radioxenon isotopes are measured by detecting their decay products which include beta particles, conversion electrons, gamma-rays and X-rays. The net-counts method subtracts the background and interference terms from the raw sample counts in regions of interest (ROI) to develop an estimate of the net counts associated with the xenon isotopes. An overview of the development of the net-count algorithms is provided by Cooper et al. (2019) while Sivels et al. (2017) provides an overview of the associated hardware developments.
The net counts method uses information from a detector background measurement to determine the local long-lived environmental radioactive background and then remove it from future samples. The detector then cycles through three steps. First, the carry-over activity from previous measurements is counted with a gas-background file. The activity counting is performed with an evacuated detector. Then, the activity in a processed xenon sample is counted. The third step is to count the activity from a quality control (QC) source. The long-lived QC source, which often contains encapsulated 137Cs and sometimes isotopes of europium, can be used to check the relative energy calibration of the detectors. The QC source is mechanically moved into position for counting and then moved behind shielding material. Occasionally, but rarely, the QC source is not positioned properly behind the shielding and can affect the other samples.
A number of alternative algorithms have been proposed with the hope of improving on the net-counts method. Several methods are compared by Deshmukh et al. (2017), including a simultaneous decomposition method (SDAT) proposed by Biegalski et al. (2013), which introduced the idea of simultaneously estimating the activity of the four isotopes of interest using a non-negative least squares algorithm. Accurately accounting for background counts is a difficult step in the analysis for both the net-counts method and the alternative methods. Ringbom and Axelsson (2020) recently proposed a Bayesian approach to handling background in the net-counts method. Lastly, Cooper et al. (2022) has proposed a matrix-analysis method to better account for interference terms between the xenon isotopes.
This paper introduces a new simultaneous fitting analysis method called Xcounts. It uses the concept of regions of interest and blends ideas from several approaches. Xcounts does a simultaneous estimation of the counts for all measurement constituents including radon, QC signature, and background. Each measured count in the union of ROIs ends up assigned to background, radon, or one of the other isotopes of interest. All regions are used to estimate the counts from every isotope and the resulting concentration estimates are never negative.
Section snippets
Methods
This section presents a short overview of the response of a beta-gamma detector to different isotopes. Then, the new model for calculating activity concentrations for xenon isotopes is described. Finally, an approach to developing calibration data is described and a preliminary selection of regions of interest is presented.
Model performance
Model performance is demonstrated by evaluating detection limits and estimation uncertainty. Then, degradation of the detection limits in the presence of high concentrations of one isotope, or radon, is evaluated. Finally, a comparison is made with a typical net-counts algorithm for a set of samples with several multiple isotope detections.
Discussion
A new algorithm has been introduced for estimating the activity concentrations for the four xenon isotopes 131mXe, 133mXe, 133Xe, and 135Xe from beta-gamma coincidence data. The algorithm simultaneously estimates the counts for each of the four isotopes rather than using sequential steps with the net counts from previous analysis steps. Background counts are also estimated, based on the average counts from previous gas-background samples, rather than subtracting the background counts from a
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
This research was funded by the National Nuclear Security Administration, Defense Nuclear Nonproliferation Research and Development (NNSA DNN R&D). The authors acknowledge important interdisciplinary collaboration with scientists and engineers from Los Alamos National Laboratory (LANL), Lawrence Livermore National Laboratory (LLNL), Mission Support and Test Services LLC (MSTS), Pacific Northwest National Laboratory (PNNL), and Sandia National Laboratories (SNL). PNNL is operated by Battelle for
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