Potentials and limitations of using artificial intelligence to predict grouting parameters – Results of a case study in a tunnel project in Scandinavia
Research output: Contribution to journal › Article › Research
External Organisational units
- STRABAG AG
- Studiengesellschaft für Tunnel und Verkehrsanlagen e. V.
- eguana GmbH
- geoteam Ingenieurgesellschaft mbH
- Züblin Spezialtiefbau Ges.m.b.H.
Great importance is attached to ‘pressure-volume records’ for the execution, documentation and billing of rock grouting. In this context, special digital data management systems are now available which can provide data in a structured and consistent format that is also suitable for artificial intelligence (AI) approaches. Using datasets from a tunnel project in Scandinavia, this paper shows that artificial neural networks can be used to reliably predict the evolution of pressure-volume records or the volume of grout injected at the end in the interests of construction site efficiency. Taking into account the technical feasibility of using AI to support tunnel grouting, we then show which contractual modifications would be required in order to make effective use of corresponding developments.
|Number of pages||10|
|Journal||Geomechanics and tunnelling = Geomechanik und Tunnelbau|
|Publication status||Published - 4 Oct 2022|