Development of compartment models with Markov-chain processes for radionuclide transport in repository region

Abstract

This paper presents a new radionuclide transport model for performance assessment and design of a geologic repository for high-level radioactive waste. The model uses compartmentalization of a model space and a Markov-chain process to describe the transport. The model space is divided into an array of compartments, among which a transition probability matrix describes radionuclide transport. While similar to the finite-difference method, it has several advantages such as flexibility to include various types of transport processes and reactions due to probabilistic interpretation, and higher-order accuracy resulting from direct formulation in a discrete-time frame. We demonstrated application of this model with a hypothetical repository in porous rock formation. First we calculated a three-dimensional steady-state heterogeneous groundwater flow field numerically by the finite-element method. The transition probability matrix was constructed based on the flow field and hydraulic dispersion coefficient. The present approach has been found to be effective in modeling radionuclide transport at a repository scale while taking into account the effects of change in hydraulic properties on the repository performance. Numerical exploration results indicate that engineered barrier configuration and material degradation have substantial effects on radionuclide release from the repository.