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Data science (digitalisation and artificial intelligence) became more than an important facilitator for many domains in fundamental and applied sciences as well as industry and is disrupting the way of research already to a large extent. Originally, data sciences were viewed to be well-suited, especially, for data-intensive applications such as image processing, pattern recognition, etc. In the recent past, particularly, data-driven and physics-inspired machine learning methods have been developed to an extent that they accelerate numerical simulations and became directly usable for applications related to the nuclear waste management cycle. In addition to process-based approaches for creating surrogate models, other disciplines such as virtual reality methods and high-performance computing are leveraging the potential of data sciences more and more. The present challenge is utilising the best models, input data and monitoring information to integrate multi-chemical-physical, coupled processes, multi-scale and probabilistic simulations in Digital Twins (DTw) able to mirror or predict the performance of its corresponding physical twins. Therefore, the main target of the Topical Collection is exploring how the development of DTw can benefit the development of safe, efficient solutions for the pre-disposal and disposal of radioactive waste. A particular challenge for DTw in radioactive waste management is the combination of concepts from geological modelling and underground construction which will be addressed by linking structural and multi-physics/chemistry process models to building or tunnel information models. As for technical systems, engineered structures a variety of DTw approaches already exist, the development of DTw concepts for geological systems poses a particular challenge when taking the complexities (structures and processes) and uncertainties at extremely varying time and spatial scales of subsurface environments into account.
Before the final disposal of radioactive wastes, various processes can be implemented to optimise the waste form. This can include different chemical and physical treatments, such as thermal treatment for waste reduction, waste conditioning for homogenisation and waste immobilisation for stabilisation prior to packaging and interim storage. Ensuring the durability and safety of the waste matrices and packages through performance and condition assessment is important for waste owners, waste management organisations, regulators and wider stakeholder communities. Technical achievements and lessons learned from the THERAMIN and PREDIS projects focused on low- and intermediate-level waste handling is shared here. The recently completed project on Thermal Treatment for Radioactive Waste Minimization and Hazard Reduction (THERAMIN) made advances in demonstrating the feasibility of different thermal treatment techniques to reduce volume and immobilise different streams of radioactive waste (LILW) prior to disposal. The Pre-Disposal Management of Radioactive Waste (PREDIS) project addresses innovations in the treatment of metallic materials, liquid organic waste and solid organic waste, which can result from nuclear power plant operation, decommissioning and other industrial processes. The project also addresses digitalisation solutions for improved safety and efficiency in handling and assessing cemented-waste packages in extended interim surface storage.