A Dynamic Bayesian Network for the Performance Assessment of Nuclear Waste Repositories Undergoing Chemical Degradation due to Climate Change

Concrete is used as a barrier to prevent the release of radioactive contaminants from nuclear waste repositories. Concrete suffers of two main chemical degradation processes that can be expedited by climate change: carbonation-induced corrosion and chloride ingress. In this work, a Dynamic Bayesian Network (DBN) is developed for evaluating the concrete degradation induced by variations in climatic factors that affect corrosion, e.g., temperature, relative humidity and CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>. The DBN is applied with reference to near-surface waste disposal of literature, in support to the assessment of the risk of aquifer contamination due to radioactive contaminants release.