A real-time analysis for diffusion and sorption parameters in compacted clay materials

Abstract

The long-term safety of deep geological radioactive waste repositories depends critically on radionuclide migration through engineered barrier systems. This study proposes the Stability-Driven Iterative Method (SDIM), an innovative analytical approach for robust and efficient parameter estimation in through-diffusion experiments. SDIM employs real-time, data-driven fitting throughout the experimental timeline to simultaneously determine the effective diffusion coefficient, distribution coefficient, and accessible porosity, thus decoupling diffusion from sorption and exclusion effects. SDIM, implemented via commonly available spreadsheet tools, enables continuous monitoring and optimization of experiment duration based on strict convergence criteria. Case studies of cation and anion diffusion in compacted bentonite show that SDIM significantly reduces experimental uncertainty, shortens run times, and provides more accurate parameter estimation than traditional methods. For anions, SDIM uniquely quantifies accessible porosity, thus revealing significant exclusion effects in certain bentonite types. This advancement not only increases the reliability of safety assessment but also enables more efficient experimental design for radioactive waste management, significantly reducing experimental duration and resource consumption.