Automation in tunneling

Key challenges in a nutshell

Real-time steering of TBM based on monitored data and artificial intelligence AI
Development of Tunnel Information Model
Account for geotechnical uncertainties

Short description of the technology

Real-time steering of TBM requires to be able to update predictive models during the construction phase using monitoring data (see 1.1 above) to assist engineers to make informed decisions and optimization. In addition to the data monitoring, it requires an equivalent Building Information Model (BIM), also known as Tunnel Information Model (TIM[1]) integrating the geological data, the built environment and predicted ground models with potentially surface data (e.g. subsidence or vibrations). Ideally, the automation should account for inherent geotechnical uncertainties and to enable real-time automation surrogate models might be used together with Machine Learning techniques to bypass the long computation costs of the modelled process.

[1] https://www.tunnel-online.info/en/artikel/tunnel_Real-Time_Simulations_for_Process_Steering_Support_3622255.html

State of the Art: technology in existing gravitational wave detectors / TRL

Intended use in the frame of the Einstein Telescope

Improvements needed: Technological challenge for the Einstein Telescope

Economic perspectives of participation beyond the ET applications

We are open to any companies’ proposals.

Related projects and labs

Ongoing and future procurements

Business Development contacts

Peter Gier
AGIT DE – p.gier@agit.de

Matthias Grosch
NMWP.NRW DE – matthias.grosch@nmwp.de

Michel Stassart
Skywin BE – michel.stassart@skywin.be

Annick Pierrard
ULiège BE – a.pierrard@uliege.be

Maxime Corvilain
POM Limburg BE – maxime.corvilain@pomlimburg.be

René Kessen
LIOF NL – rene.kessen@liof.nl

Technology contact

Florian Amann
RWTH Aachen DE – amann@lih.rwth-aachen.de