Automated Response Matching for Organic Scintillation Detector Arrays

This paper identifies a digitizer technology with unique features that facilitates feedback control for the realization of a software-based technique for automatically calibrating detector responses. Three such auto-calibration techniques have been developed and are described along with an explanation of the main configuration settings and potential pitfalls. Automating this process increases repeatability, simplifies user operation, enables remote and periodic system calibration where consistency across detectors’ responses are critical

Real-time capabilities of a digital analyzer for mixed-field assay using scintillation detectors

Scintillation detectors offer a single-step detection method for fast neutrons and necessitate real-time acquisition, whereas this is redundant in two-stage thermal detection systems using helium-3 and lithium-6, where the fast neutrons need to be thermalized prior to detection. The relative affordability of scintillation detectors and the associated fast digital acquisition systems have enabled entirely new measurement setups that can consist of sizeable detector arrays. These detectors in most cases rely on photomultiplier tubes, which have significant tolerances and result in variations in detector response functions. The detector tolerances and other environmental instabilities must be accounted for in measurements that depend on matched detector performance. This paper presents recent advances made to a high-speed FPGA-based digitizer. The technology described offers a complete solution for fast-neutron scintillation detectors by integrating multichannel high-speed data acquisition technology with dedicated detector high-voltage supplies. This configuration has significant advantages for large detector arrays that require uniform detector responses. We report on bespoke control software and firmware techniques that exploit real-time functionality to reduce setup and acquisition time, increase repeatability, and reduce statistical uncertainties

Radioxenon Time Series and Meteorological Pattern Analysis for CTBT Event Categorisation

Understanding radioxenon time series and being able to distinguish anthropogenic from nuclear explosion signals are fundamental issues for the technical verification of the Comprehensive Nuclear-Test-Ban Treaty. Every radioxenon event categorisation methodology must take into account the background at each monitoring site to uncover anomalies that may be related to nuclear explosions. Feedback induced by local meteorological patterns on the equipment and on the sampling procedures has been included in the analysis to improve a possible event categorisation scheme. The occurrence probability of radioxenon outliers has been estimated with a time series approach characterising and avoiding the influence of local meteorological patterns. A power spectrum estimator for radioxenon and meteorological time series was selected; the randomness of the radioxenon residual time series has been tested for white noise by Kolmogorov-Smirnov and Ljung-Box tests. This methodological approach was applied to radioxenon data collected at two monitoring sites located at St. John's, Canada and Charlottesville, USA, equipped with two different noble gas systems. It shows different feedback with local meteorological patterns and randomness for the radioxenon data recorded at the selected sites of St. John's and Charlottesville as well as a different occurrence probability of the outliers in the normalized radioxenon original and residual time series