- Sustainable energy from the depths: Optimization strategies for hydrothermal tunnel water systems. Dans: Geomechanics and Tunnelling, v. 17, n. 5 (octobre 2024). (2024):
- Towards reinforcement learning - driven TBM cutter changing policies. Dans: Automation in Construction, v. 165 (septembre 2024). (2024):
- The rock mechanical relevance of anisotropy in tunnel design. Dans: Geomechanics and Tunnelling, v. 17, n. 1 (décembre 2023). (2023):
- Shallow Tunnels, Subway constructions. Dans: Geomechanics and Tunnelling, v. 16, n. 6 (novembre 2023). (2023):
- Practical recommendations for machine learning in underground rock engineering – On algorithm development, data balancing, and input variable selection. Dans: Geomechanics and Tunnelling, v. 15, n. 5 (octobre 2022). (2022):
- Potential applications of machine learning for BIM in tunnelling. Dans: Geomechanics and Tunnelling, v. 15, n. 2 (avril 2022). (2022):
- Improving face decisions in tunnelling by machine learning‐based MWD analysis. Dans: Geomechanics and Tunnelling, v. 15, n. 2 (avril 2022). (2022):
- Towards the integration of smart techniques for tunnel seismic applications. Dans: Geomechanics and Tunnelling, v. 14, n. 5 (octobre 2021). (2021):
- Reinforcement learning based process optimization and strategy development in conventional tunneling. Dans: Automation in Construction, v. 127 (juillet 2021). (2021):
- Learning decision boundaries for cone penetration test classification. Dans: Computer-Aided Civil and Infrastructure Engineering, v. 36, n. 4 (février 2021). (2021):
- On the pointlessness of machine learning based time delayed prediction of TBM operational data. Dans: Automation in Construction, v. 121 (janvier 2021). (2021):
- Austrian Tunnel Competence Center – ATC 2. Dans: Geomechanics and Tunnelling, v. 12, n. 6 (décembre 2019). (2019):
- MSAC: Towards data driven system behavior classification for TBM tunneling. Dans: Tunnelling and Underground Space Technology, v. 103 (septembre 2020). (2020):
- Machine Learning in tunnelling – Capabilities and challenges. Dans: Geomechanics and Tunnelling, v. 13, n. 2 (avril 2020). (2020):
- Application of artificial neural networks for Underground construction – Chances and challenges – Insights from the BBT exploratory tunnel Ahrental Pfons. Dans: Geomechanics and Tunnelling, v. 12, n. 5 (octobre 2019). (2019):
- Valhalla - Innovative pumped hydro storage facilities in Chile: Challenges from a rock mechanical point of view. Dans: Geomechanics and Tunnelling, v. 8, n. 5 ( 2015). (2015):
- Validation of a novel constitutive model for shotcrete using data from an executed tunnel / Validierung eines neuen Stoffgesetzes für Spritzbeton mittels Ergebnissen eines ausgeführten Tunnelprojekts. Dans: Geomechanics and Tunnelling, v. 7, n. 4 ( 2014). (2014):
- 3-dimensional numerical calculations for tunnels with high overburden / Dreidimensionale numerische Berechnungen für tiefliegende Tunnelbauvorhaben. Dans: Geomechanics and Tunnelling, v. 6, n. 4 ( 2013). (2013):
- Tunnel Heading Stability in Drained Ground. Dans: Felsbau, v. 20, n. 6 ( 2002). (2002):
- Comparison of Excavation Methods: A.DE.CO-RS versus NATM. Dans: Felsbau, v. 22, n. 4 ( 2004). (2004):
- On the Ground Response Curve. Dans: Felsbau, v. 20, n. 6 ( 2002). (2002):