Tunnel boring machines (TBMs) have become essential in modern tunnelling projects due to their efficiency, safety, and ability to manage complex geological conditions. Accurate prediction of TBM performance is critical for project planning, risk management, and cost estimation. This study focuses on the performance assessment of a hard rock double-shield TBM used in the exploratory tunnel of the Brenner Base Tunnel (BBT) underground system, specifically within the Central Gneiss unit. Several prediction models from the literature, including those based on rock mass classification systems such as RMR and GSI, were applied and compared with actual TBM performance data collected over approximately 3200-m stretch. The relationships between TBM operational parameters, such as penetration rate, instantaneous cutting rate, specific energy, boreability index, power consumption, specific penetration, and geomechanical properties were statistically analysed. Two new predictive models based on RMR and GSI were also proposed and evaluated. The results demonstrate good correlations between rock mass quality indices and TBM performance indicators, highlighting the importance of detailed geomechanical characterisation for reliable performance forecasting.
TBM performance assessment for the BBT exploratory tunnel in the Central Gneiss unit / Aydin, Deniz; Tinti, Francesco; Boldini, Daniela. - In: UNDERGROUND SPACE. - ISSN 2467-9674. - 28:(2026), pp. 332-349. [10.1016/j.undsp.2026.02.006]
TBM performance assessment for the BBT exploratory tunnel in the Central Gneiss unit
Daniela Boldini
2026
Abstract
Tunnel boring machines (TBMs) have become essential in modern tunnelling projects due to their efficiency, safety, and ability to manage complex geological conditions. Accurate prediction of TBM performance is critical for project planning, risk management, and cost estimation. This study focuses on the performance assessment of a hard rock double-shield TBM used in the exploratory tunnel of the Brenner Base Tunnel (BBT) underground system, specifically within the Central Gneiss unit. Several prediction models from the literature, including those based on rock mass classification systems such as RMR and GSI, were applied and compared with actual TBM performance data collected over approximately 3200-m stretch. The relationships between TBM operational parameters, such as penetration rate, instantaneous cutting rate, specific energy, boreability index, power consumption, specific penetration, and geomechanical properties were statistically analysed. Two new predictive models based on RMR and GSI were also proposed and evaluated. The results demonstrate good correlations between rock mass quality indices and TBM performance indicators, highlighting the importance of detailed geomechanical characterisation for reliable performance forecasting.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


