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// Closure of Underground Cavities, Long-term Safety Studies

KI-Stoff

AI-supported Material Modelling of Bentonite behaviour

The research project “KI-Stoff” focuses on developing a methodology for the automated selection and adaptation of material models for bentonite using machine learning (ML). Bentonite materials are an integral part of the geotechnical barriers in most repository concepts worldwide and exhibit complex behavioural patterns such as non-linearity, heterogeneity, and coupled interactions. The process of developing material laws is therefore extremely demanding and time-consuming. In addition, the properties of bentonite are subject to natural variations depending on its occurrence, meaning that it has not yet been possible to develop a universally valid constitutive law. The use of ML opens up new possibilities that can contribute to accelerated model selection, parameter identification, and further development of material models.

A major challenge is to select and calibrate a material model suitable for new measurement data of different bentonite types. The aim of this project is therefore to develop an ML methodology that automates this process at various points and thus provides the best possible support for modellers and engineers. At the same time, model comparisons can be systematised on this basis.

The ultimate aim of the research project is to reduce the gap between experiments and simulations for bentonite.

Contact

Research & Development
info@bge-technology.de


Short Infos

Runtime: 2025 - 2028

Client:
Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection (BMUV)

Partner:
Technischen Universität Bergakademie Freiberg (TUBAF), Deutschland
Abteilung Datengetriebene Modellierung mechanischer Systeme (IRMB-DDM-TUBS), Deutschland

Publications

// Newsletter

BGE TECHNOLOGY NEWS 2024 Q4

Author(s): T. von Berlepsch, et al.

Fourth newsletter of BGE TECHNOLOGY GmbH in 2024

  • BGE TECHNOLOGY GmbH supports BGE in Area Screening in the Site Selection Procedure
  • Accident Analyses for the Operating Phase of the KONRAD Mine – Effect of Fire on Structural Stability?
  • Evaluation of the Impact of Metal Corrosion on the Integrity of Waste Containers in Crystalline Rock (R&D Project BEnKo)
  • AI-supported Material Modelling of Bentonite behaviour (R&D Project KI-Stoff)
  • Crushed Salt as Engineered Backfill Material (R&D Project MEASURES)

Language: Englisch

20.12.2024

KI-Stoff, MEASURES

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