A Reliable Absolute and Relative Bayesian Method for Nuclear Decommissioning: Low-Level Radioactivity Detection With Gamma-Ray Spectrometry

In this article, we aim at measuring a low-activity uranium contamination deposited on concrete surfaces of a nuclear facility and presenting varying enrichment levels. Considering this application field, CEA LIST, has developed an original approach, combining gamma-ray spectrometry based on high-purity germanium (HPGe) measurements and specific Bayesian algorithms. This methodology gives access to an indirect surface activity estimation, assuming that the ratio between the number of alpha particles to be quantified and the number of detected gamma rays is known. The Bayesian approach characteristic property is able to inject a representation of the physical context in the form of a probabilistic a priori. It enables to improve the tradeoff between the true detection rate (TDR) and the false alarm rate (FAR) at low count rates and takes benefit of a richer time-energy information structure than the algorithms used in the conventional detection procedures. The performance evaluation and characterization of Bayesian statistical tests are performed using classical receiver-operating characteristic (ROC) curves by comparison to frequentist hypothesis tests. Results indicate that the Bayesian approach has a superior detection performance for low-activity uranium contamination compared to the frequentist approach. The estimated gain is contained between 30% and 50%, considering a variable or stable radiological background. The Bayesian approach offers the best tradeoff between the TDR, FAR, and the response time and is compatible with the user's requirements.