Proceedings of the

The 33rd European Safety and Reliability Conference (ESREL 2023)
3 – 8 September 2023, Southampton, UK

Enhanced Bayesian Network for Reliability Assessment: Application to Salt Domes as Disposal Sites for Radioactive Waste Problem

Andrea Perin1,a, Jonas Suilmann2,c, Thomas Graf2,d and Matteo Broggi1,b

1Institute for Risk and Reliability, Leibniz University Hannover, Hannover, Germany.

2Institute of Fluid Mechanics and Environmental Physics in Civil Engineering, Leibniz University Hannover, Hannover, Germany.


Risk assessment of radioactive waste disposal requires a comprehensive evaluation of the potential hazards and uncertainties associated with the disposal, e.g. hydro-geological conditions, over a time span of thousands of years. Among the tools available to assess risk in engineering application, Enhanced Bayesian Networks (EBNs) 1 are capable to provide a deep understanding of multidisciplinary models affected by uncertainties. Contrary to traditional BN, EBNs can be exploited for addressing the long-term safety analysis of radioactive waste disposal 2, allowing the additional incorporation of information with a non-discrete nature. The usage of EBNs can improve the accuracy of the risk measurements, maintaining the traditional BNs advantages such as compact-representation, human-readability, scalability and multidisciplinary-usability, in various applications.

In this work, the safety of salt domes 3 as deep geological radioactive waste disposal over long terms is analyzed. The main idea is to use EBN as a probabilistic framework for evaluating the possible contamination of the biosphere in different scenarios.

Literature, reports and expert knowledge will be used to determine the EBN's nodes 4. Nodes combinations produce the set of inputs and uncertainties for a finite element (FE) model able to deal with density-driven (thermohaline) flow, heat transport, transport of dissolved salt and a radionuclide in discretely-fractured porous media.


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