Potentials and limitations of using artificial intelligence to predict grouting parameters – Results of a case study in a tunnel project in Scandinavia
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in: Geomechanics and tunnelling = Geomechanik und Tunnelbau, Jahrgang 15.2022, Nr. 5, 04.10.2022, S. 525-534.
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T1 - Potentials and limitations of using artificial intelligence to predict grouting parameters – Results of a case study in a tunnel project in Scandinavia
AU - Thienert, Christian
AU - Ouschan, Michael
AU - Wenighofer, Robert
AU - Könemann, Frank
AU - Klaproth, Christoph
AU - Gabriel, Patrick
AU - Villeneuve, Marlene C.
AU - Pechhacker, Robert
N1 - Publisher Copyright: © 2022, Ernst und Sohn. All rights reserved.
PY - 2022/10/4
Y1 - 2022/10/4
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85139252216&partnerID=8YFLogxK
U2 - 10.1002/geot.202200050
DO - 10.1002/geot.202200050
M3 - Artikel
VL - 15.2022
SP - 525
EP - 534
JO - Geomechanics and tunnelling = Geomechanik und Tunnelbau
JF - Geomechanics and tunnelling = Geomechanik und Tunnelbau
SN - 1865-7362
IS - 5
ER -
