National Nuclear Laboratory

The geological disposal of higher activity radioactive wastes is internationally accepted as a safe, permanent solution. Work to implement this solution is progressing in many countries, involving national and international programmes that bring together technical, social, scientific and engineering considerations to advance subject matter understanding, enhance experience and broaden knowledge bases. This Special Publication collates research outputs from site investigations, advances in technology, experimental studies and modelling activities relevant to radioactive waste disposal. The sixteen papers report research undertaken on a variety of topics, including knowledge management, engineered barrier design and geological investigation studies, as well as contributions that consider how disposed waste and multiple barriers of geological disposal facilities evolve on prolonged timescales. The papers reflect the breadth and depth of scientific research activities contributing to radioactive waste disposal.

Flow and solute transport in groundwater are primarily controlled by the hydraulic conductivity (K) field. Variations in the K field greatly influence subsurface flow rates and solute migration and dispersion. Due to the importance of aquifer heterogeneity, several approaches have been proposed in the literature for modelling K field spatial distribution based on borehole data. In this work, we evaluate two methods to generate spatial realisations of the K field of a heterogeneous aquifer. Results are analysed in terms of the connectivity of high-K cells, and solute transport results are compared and discussed. The methodology consists of three main steps. First, borehole PSD data are used to characterise hydrofacies and generate 3D stochastic realisations of those hydrofacies using the Markov-Chain/Transition Probability approach (MC/TP). Resultant realisations are used to fill a 3D grid. Then, two methods are used to generate hydraulic conductivity fields by assigning a K value to each cell on those grids: (1) using the geometric mean of each hydrofacies (GMEAN) and (2) using a value sampled from the KDE probability functions of each hydrofacies (KDE). Two different porosity scenarios are considered (high porosity, HP; and low porosity, LP). Finally, solute transport estimates were computed using MODFLOW and MT3DMS.Connectivity analysis of the stochastic realisations shows a higher degree of connectivity of high-K cells on the GMEAN mode than in the KDE. The latter leads to overall higher average K values, but also to slower flow regions with lower K values than the GMEAN.Solute transport runs result in slower travel times and lower peak concentrations on the KDE realisations than in the GMEAN case. Breakthrough curves at different observation points show that, when concentrations fall after peaking (for a time-limited input pulse), both GMEAN and KDE curves tend to converge. The field-scale longitudinal dispersivity implied from the ensemble probability plumes is similar between the two K field realisation approaches modelled, but the vertical dispersivity is higher in the KDE realisations. The high porosity scenario shows higher dispersivities and considerably longer travel times.Results show that, for the same porosity scenario, contaminant plumes behave similarly for the KDE and GMEAN approaches at longer times and distances from the source. This suggests that, on the studied site, the small-scale heterogeneity has a reduced effect on the on the long term, field scale macrodispersivity and solute transport behaviour.

Abstract This study investigates the erosion behavior and modeling of glass particle beds under impinging jet conditions, with a focus on particle size effects and the onset of cohesion. Ultrasonic profiling is implemented to scan and measure static crater profiles. Results indicate that particle size significantly affects crater dimensions, ring peak formation, and overall crater shape. The smallest glass particles ( d 50 = 35 μm) studied deviate from the trends in crater size, yield stress, and analytical modeling established using larger particles, indicating the onset of cohesion effects at this small particle size. The standard erosion parameter worked well for modeling cohesionless particles down to a certain size limit, beyond which cohesive forces become significant. A new parameter, E τ based on particle critical shear stress, is introduced for erosion modeling in this study. The transition to cohesive behavior observed in the smallest glass particles is successfully accounted for using E τ .

Monitoring the internal conditions of spent nuclear fuel (SNF) dry-storage casks is essential for ensuring the long-term safety and integrity of radioactive waste containment. This study addresses the critical challenge of early detection of potential failures within sealed SNF casks by introducing a novel gas sensor based on microelectromechanical systems (MEMS) technology. The sensor is specifically designed to detect nitrogen concentration in helium, an important indicator of canister degradation, particularly cracks and leaks that may compromise the sealed environment. The proposed sensor utilizes an aluminium nitride (AlN) piezoelectric micromachined structure comprising weakly coupled bridge and cantilever resonators to measure changes in gas thermal conductivity. Electrothermal excitation revealed distinct vibration modes, including a fixed first global mode, a highly variable second global mode, and two instances of mode veering at defined voltage thresholds. Nitrogen sensitivity was quantitatively assessed using the dimensionless Frequency Localisation Factor (FLF), capturing the sensor’s responsiveness to gas composition changes. Experimental validation confirmed the sensor’s high sensitivity, strong linearity, and low power consumption, making it well-suited for integration into Internet of Things (IoT) platforms and wireless sensor networks. By combining the precision and scalability of MEMS technology with robust gas detection capabilities, this work provides a practical and effective solution for enhancing safety monitoring in SNF dry-storage systems.

Plasma-assisted electrochemical reduction is most often driven by gas-phase free electrons injected into a solution to promote reactions with solutes. In aqueous systems, this reduction is fundamentally limited by the short penetration depth of solvated electrons (esol⁻), which are rapidly quenched via second-order recombination. Non-aqueous solvents offer slower recombination kinetics, enhancing esol⁻ lifetime and penetration. In this study, we present a catalyst-free plasma electrolysis platform using ethylene glycol (EG) as the solvent, enabling direct electron injection from an atmospheric plasma and demonstrating CO₂-tunable selectivity in the resulting reduction products.Total internal reflection absorption spectroscopy (TIRAS) and pulse radiolysis confirm the presence of esol⁻ in EG, with peak absorbance between 575–600 nm. Unlike in water, esol⁻ decay in EG follows a slower first-order reaction, leading to a penetration depth of ~25 nm. Product analysis reveals a rich spectrum of EG redox products including polyethylene glycols (PEGs), higher-order glycols and polyols, dioxanes, dioxolanes, and complex cyclic and bicyclic compounds. Adding dissolved CO₂ to the EG solution significantly shifts the product distribution, generating unique compounds and enabling tunable product selectivity.These results highlight the role of solvent environment in shaping esol⁻ reactivity and establish non-aqueous plasma electrolysis as a promising platform for selective ethylene glycol and CO₂ conversion and sustainable chemical synthesis. More broadly, these findings offer a new strategy for carbon valorization without metal catalysts and could inform the design of future systems aimed at converting dilute CO₂ streams into valuable oxygenated chemicals under ambient conditions.

Automation of radioactive waste stores could enable medium-long range monitoring in real-time or set intervals, increasing safety by reducing the need for manual inspections by workers. This study evaluates the environmental and economic impact of implementing two monitoring technologies - SiLiF/SciFi and LoRa - over the lifespan of an interim storage facility, from construction to end-of-life dismantling, including detailed analysis of the production, operational and disposal of the monitoring systems. Results show that the climate change impact of the full life cycle is 4741t CO2 eq. for LoRa and 4837t CO2 eq. for SiLiF/SciFi (95 and 97kg CO2 eq. per drum, respectively): the 2% lower impact of the LoRa platform is due to its lower operational energy consumption. Store construction is the biggest contributor to overall environmental impacts, followed by production of the monitoring systems. Reducing the number of monitored drums and the size of the monitor support system could together reduce environmental impacts by 9%. Replacing steel with HDPE for the monitor support system reduces the impact from 17.8 to only 1.9kg CO2 eq. (-89%), plus >95% reduction in all toxicity categories, metal depletion and land use. Evaluation of two scaled-up scenarios based on test configuration mock-ups reveals that monitoring costs an additional €9.5M (LoRa) to €24M (SiLiF/SciFi). Data herein allows real-world configurations to be evaluated based on case-specific sensor performance and operational requirements. Saving one mSv of worker dose is found to incur a carbon 'cost' of 23-37kg CO2 eq. and an economic cost of ~€18.48-48.42. The latter falls well within sectoral guidelines on dose reduction expenditure. Future research should explore the optimisation of monitor numbers, alternative materials and energy sources, long-term system reliability, and the socio-economic implications of saving worker dose vs incurring environmental costs.

Composite ceramic-metallic (cermet) fuels, such as UO2-Mo, have gained attention as advanced alternatives to traditional UO2 fuel, primarily due to their potential to address the issue of poor thermal conductivity in UO2. This poor thermal conductivity can lead to challenges like elevated fuel temperatures, increased fission gas release (FGR), and heightened clad hoop strain. UO2-Mo composite fuel offers a potential solution by incorporating molybdenum to significantly enhance thermal conductivity and mitigate these issues. In this work we develop a new thermal conductivity model for UO2-Mo fuel and implement it in the ENIGMA fuel performance code to investigate the impact of the increased thermal conductivity on fuel behavior under pressurized water reactor (PWR) operating conditions. We simulate a typical PWR fuel rod, except with UO2-Mo fuel, under both steady-state irradiation and transient scenarios. Predictions of fuel temperature, FGR, and clad hoop strain are compared against conventional UO2 fuel, with results indicating significant advantages for UO2-Mo, including reductions in all three metrics. While not investigating the effects of other differences in material properties and phenomenological behavior of UO2-Mo fuel (in part due to the lack of irradiation data), the results provide an initial quantification of the benefits of the increased thermal conductivity on UO2-Mo fuel performance.