Version 1
: Received: 19 December 2023 / Approved: 19 December 2023 / Online: 20 December 2023 (04:32:57 CET)
How to cite:
Garzón-Roca, J.; Torrijo, F.J.; Rodríguez-Peces, M.J.; Ramos, A. Discontinuities Characterization and Estimation of the Geological Strength Index by AI Tools on Flysch Materials. Preprints2023, 2023121455. https://doi.org/10.20944/preprints202312.1455.v1
Garzón-Roca, J.; Torrijo, F.J.; Rodríguez-Peces, M.J.; Ramos, A. Discontinuities Characterization and Estimation of the Geological Strength Index by AI Tools on Flysch Materials. Preprints 2023, 2023121455. https://doi.org/10.20944/preprints202312.1455.v1
Garzón-Roca, J.; Torrijo, F.J.; Rodríguez-Peces, M.J.; Ramos, A. Discontinuities Characterization and Estimation of the Geological Strength Index by AI Tools on Flysch Materials. Preprints2023, 2023121455. https://doi.org/10.20944/preprints202312.1455.v1
APA Style
Garzón-Roca, J., Torrijo, F.J., Rodríguez-Peces, M.J., & Ramos, A. (2023). Discontinuities Characterization and Estimation of the Geological Strength Index by AI Tools on Flysch Materials. Preprints. https://doi.org/10.20944/preprints202312.1455.v1
Chicago/Turabian Style
Garzón-Roca, J., Martín J. Rodríguez-Peces and Adrià Ramos. 2023 "Discontinuities Characterization and Estimation of the Geological Strength Index by AI Tools on Flysch Materials" Preprints. https://doi.org/10.20944/preprints202312.1455.v1
Abstract
This work studies the discontinuities features of sedimentary flysch materials in a 100 km2 area belonging to the Basque Arc. Such materials are common in this Spanish Alpine region located in the north of the Iberian Peninsula. A total of 33 outcrops are investigated by an intensive geotechnical investigation including geomechanical stations, boreholes and mechanical laboratory tests. Two flysch units are characterized: the Upper Aguinaga Formation or siliciclastic flysch, and the Lower Itziar Formation or calcareous flysch. Differences between both flysch formation are found. Joints in the siliciclastic flysch formation present an undulated roughness, with a spacing narrower and a persistence lower than in the calcareous flysch formation, which exhibits higher friction angles, although roughness is essentially planar. In addition, the potential of using Artificial Intelligence (AI) techniques, particularly Artificial Neural Networks and Support Vector Machine, to estimate the Geological Strength Index (GSI) from the Rock Quality Design (RQD) and some discontinuities features (spacing, persistence, aperture and roughness) is investigated. AI techniques are found to be satisfactory, being the Support Vector Machine with a linear kernel the technique which achieves the best performance.
Keywords
Flysch materials; Geomechanical characterization; Discontinuities; Geological Strength Index; AI tools; Artificial Neural Network; Support Vector Machine
Subject
Engineering, Civil Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
