Radiological characterization for decommissioning of nuclear sites and facilities is a key issue for the global success of such industrial projects, which imposes an efficient control of radiological hazards, cost estimation, planning and waste management.
A large range of evaluation objectives co-exist during a decommissioning and dismantling (D&D) project: doubt removal, identification of hot spots, spatial extent of contaminated materials, dose rate estimation for workers, monitoring of the decontamination work and final survey. At each stage of a decommissioning program or project, adequate radiological characterization is of crucial importance.
D&D projects are largely impacted by the contamination state of the facility or the site. However, until recently, little care was dedicated to this initial characterization. Deterministic numerical models might be used to describe the contamination distribution in simple cases. They deal with activation, migration, dispersion, etc. But most of the time, they fail to represent accurately the reality due to its complexity. Model parameters and hypotheses become too numerous to be handled correctly. The geostatistical framework provides probabilistic and reliable methods for sampling optimization, activity estimation, uncertainty quantification and risk analysis, leading to a sound classification of radiological waste. Numerous industrial feedbacks have demonstrated the financial benefit of applying this methodology before any remediation.
Using recent examples, this article aims at presenting the geostatistical approach and its added value in operational decommissioning and dismantling projects.