Improving Bayesian radiological profiling of waste drums using Dirichlet priors, Gaussian process priors, and hierarchical modeling.

We present three methodological improvements of our recently proposed approach for Bayesian inference of the radionuclide inventory in radioactive waste drums, from radiological measurements. First we resort to the Dirichlet distribution for the prior distribution of the isotopic vector. The Dirichlet distribution possesses the attractive property that the elements of its vector samples sum up to 1.

2D inversion of in situ gamma-ray spectrometric measurements of Cs for site characterization.

Environmental contamination by radioactive materials can be characterized by in situ gamma surface measurements. During such measurements, the field of view of a gamma detector can be tens of meters wide, resulting in a count rate that integrates the signal over a large measurement support volume/area. The contribution of a specific point to the signal depends on various parameters, such as the height of the detector above the ground surface, the gamma energy and the detector properties, etc.

Bayesian inference of 1D activity profiles from segmented gamma scanning of a heterogeneous radioactive waste drum.

We present a Bayesian approach to probabilistically infer vertical activity profiles within a radioactive waste drum from segmented gamma scanning (SGS) measurements. Our approach resorts to Markov chain Monte Carlo (MCMC) sampling using the state-of-the-art Hamiltonian Monte Carlo (HMC) technique and accounts for two important sources of uncertainty: the measurement uncertainty and the uncertainty in the source distribution within the drum. In addition, our efficiency model simulates the contributions of all considered segments to each count measurement.

Metrology for decommissioning nuclear facilities: Partial outcomes of joint research project within the European Metrology Research Program.

Decommissioning of nuclear facilities incurs high costs regarding the accurate characterisation and correct disposal of the decommissioned materials. Therefore, there is a need for the implementation of new and traceable measurement technologies to select the appropriate release or disposal route of radioactive wastes. This paper addresses some of the innovative outcomes of the project "Metrology for Decommissioning Nuclear Facilities" related to mapping of contamination inside nuclear facilities, waste clearance measurement, Raman distributed temperature sensing for long term repository integrity monitoring and validation of radiochemical procedures.

Thorium-229 quantified in historical Thorium-228 capsules.

Thorium-229 is a valuable, but scarce, radionuclide for nuclear clock applications or targeted alpha therapy. While it is mostly produced by the decay of U, Th can also be produced by neutron irradiation of Ra. At SCK•CEN, capsules containing mainly Th (by-product of Ra irradiation) were characterized to quantify the present amounts of Th, Th, Ac, Ra with high resolution gamma spectroscopy, after a decay period of 40 years in which Th has decayed.

Determination of 137Cs contamination depth distribution in building structures using geostatistical modeling of ISOCS measurements.

Decommissioning of nuclear building structures usually leads to large amounts of low level radioactive waste. Using a reliable method to determine the contamination depth is indispensable prior to the start of decontamination works and also for minimizing the radioactive waste volume and the total workload. The method described in this paper is based on geostatistical modeling of in situ gamma-ray spectroscopy measurements using the multiple photo peak method.