Digitalisation for nuclear waste management: predisposal and disposal

Research output: Contribution to journalEditorial (Lead article)Contributedpeer-review

Contributors

  • Olaf Kolditz - , Chair of Applied Environmental Systems Analysis, Helmholtz Centre for Environmental Research (Author)
  • Diederik Jacques - , Belgian Nuclear Research Center (Author)
  • Francis Claret - , Bureau de recherches géologiques et minières (Author)
  • Johan Bertrand - , Agence nationale pour la gestion des déchets radioactifs (Author)
  • Sergey V. Churakov - , Paul Scherrer Institute (Author)
  • Christophe Debayle - , Institut de radioprotection et de sûreté nucléaire (Author)
  • Daniela Diaconu - , Institute for Nuclear Research, Pitesti (Author)
  • Kateryna Fuzik - , SSTC NRS (Author)
  • David Garcia - , Amphos 21 Consulting (Author)
  • Nico Graebling - , Helmholtz Centre for Environmental Research (Author)
  • Bernd Grambow - , Université de Nantes (Author)
  • Erika Holt - , VTT Technical Research Centre of Finland Ltd. (Author)
  • Andrés Idiart - , Amphos 21 Consulting (Author)
  • Petter Leira - , Institute for Energy Technology (Author)
  • Vanessa Montoya - , Belgian Nuclear Research Center (Author)
  • Ernst Niederleithinger - , Federal Institute for Materials Research and Testing Berlin (Author)
  • Markus Olin - , VTT Technical Research Centre of Finland Ltd. (Author)
  • Wilfried Pfingsten - , Paul Scherrer Institute (Author)
  • Nikolaos I. Prasianakis - , Paul Scherrer Institute (Author)
  • Karsten Rink - , Helmholtz Centre for Environmental Research (Author)
  • Javier Samper - , University of A Coruna (Author)
  • István Szöke - , Institute for Energy Technology (Author)
  • Réka Szöke - , Institute for Energy Technology (Author)
  • Louise Theodon - , Agence nationale pour la gestion des déchets radioactifs (Author)
  • Jacques Wendling - , Agence nationale pour la gestion des déchets radioactifs (Author)

Abstract

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.

Details

Original languageEnglish
Article number42
JournalEnvironmental earth sciences
Volume82
Issue number1
Publication statusPublished - Jan 2023
Peer-reviewedYes