Abstract
Nuclear Waste Services (NWS) goal is to ensure radioactive waste produced in the UK is managed safely and securely. This includes being responsible for the siting and construction of the UK’s Geological Disposal Facility (GDF) infrastructure for higher-activity radioactive waste. This waste includes large quantities of fissile nuclides, therefore a safe GDF design must account for the risk of a subsurface criticality event (i.e. a chain fission reaction). Fissile nuclides will be dispersed in a GDF over post-closure timescales governed by uncertain processes such as corrosion, radioactive decay, diffusion and reactive transport. To account for the uncertainty in the future evolution of a GDF, safety assessments apply probabilistic modelling and compute thousands of radionuclide migration scenarios. Previous assessments using existing models have used expert human judgement to manually estimate the worst-case scenario of radionuclide migration and then used a criticality code to calculate the effective neutron multiplication factor (i.e. reactivity). However, this manual approach may fail to select the most reactive scenario. Therefore, a new codebase has been developed by Jacobs for NWS in order to automate the safety assessment process, considering all scenarios and identifying trends in reactivity. The new codebase, GoldSim Monte Carlo Interfacing Tool (GMIT), comprises a set of Python modules and scripts which utilise parallel processing to allow the user to couple thousands of scenarios from a reactive transport model of a GDF with a choice of criticality code (MONK or MCNP). The tool is developed with user customisability in mind, and includes optimisation features to minimise space requirements of the GDF design while remaining safely below a prescribed reactivity threshold. This talk will discuss the main features of GMIT and will present some preliminary results that have been obtained through its use in support of the UK GDF criticality safety programme.
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