Digitalisation for nuclear waste management: Predisposal and disposal
Year of publication
2023
Authors
Kolditz, Olaf; Jacques, Diederik; Claret, Francis; Bertrand, Johan; Churakov, Sergey V.; Debayle, Christophe; Diaconu, Daniela; Fuzik, Kateryna; Garcia, David; Graebling, Nico; Grambow, Bernd; Holt, Erika; Idiart, Andrés; Leira, Petter; Montoya, Vanessa; Niederleithinger, Ernst; Olin, Markus; Pfingsten, Wilfried; Prasianakis, Nikolaos I.; Rink, Karsten; Samper, Javier; Szöke, István; Szöke, Réka; Theodon, Louise; Wendling, Jacques
Show moreAbstract
<p>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.</p>
Show moreOrganizations and authors
Publication type
Publication format
Article
Parent publication type
Journal
Article type
Original article
Audience
ScientificPeer-reviewed
Peer-ReviewedMINEDU's publication type classification code
A1 Journal article (refereed), original researchPublication channel information
Journal
Volume
82
Issue
1
Article number
42
ISSN
Publication forum
Publication forum level
1
Open access
Open access in the publisher’s service
Yes
Open access of publication channel
Partially open publication channel
License of the publisher’s version
CC BY
Self-archived
No
Other information
Fields of science
Environmental engineering
Keywords
[object Object],[object Object]
Language
English
International co-publication
Yes
Co-publication with a company
Yes
DOI
10.1007/s12665-022-10675-4
The publication is included in the Ministry of Education and Culture’s Publication data collection
Yes