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The influence of rock and rock mass properties towards prediction of TBM penetration rates
The performance of a Tunnel Boring Machine (TBM) is greatly influenced by the rock and rock mass conditions it encounters. Recently, various methods have been developed to incorporate fractured rock mass and strength into Penetration Prediction Model (PPM)s for TBMs. However, it should be noted that many of these models are based on the rock mass classification system used in documenting the particular tunnel, with limited significance. This study aims to address sensitive and specific rock parameters and rock mass classification systems. The first question focuses on identifying a considerably relevant rock mass classification model for predicting TBM Penetration Rate (PR)s and the indentation process of a disc cutter. By exploring the different classification models, the study aims to determine which rock mass classification model provides the highest relevance and accuracy in understanding TBM rock mass interactions. The second research question delves into characterising rock strength parameters to avoid biased inputs in PPMs. The study seeks to establish acceptable ranges for defining rock strength parameters and explore engineering judgements regarding discarding samples that may introduce biases. The goal is to achieve an unbiased characterisation of rock strength, ensuring accurate input for PPMs. The primary objective of this research is to enhance the understanding of input parameters and their interaction with TBMs and rock masses. By avoiding the ”Garbage In, Garbage Out” scenario, the study aims to improve the reliability and accuracy of TBM performance predictions. To achieve this, the research involves analysing the Gehring and Colorado School of Mines (CSM) PPMs, which form the basis for understanding the interaction between rock masses and TBMs. The study proposes an innovative approach to characterising rock properties, aiming for standardised procedures to determine geomechanical parameters. The procedure utilises a specific correlation between the force applied by the cutter and the penetration rate of the Tunnel Boring Machine, known as Thrust Penetration Gradients. A matrix notation is introduced to characterise specific Thrust Penetration Gradients uniquely, aligned with sensitive geological parameters. Using matrix notation ensures transparency and comprehensible characterisation of TBM performance. To achieve these objectives, the research involves analysing geological and geotechnical conditions, conducting rock mechanical tests, determining machine specific parameters, and developing a more sophisticated method for determining Uniaxial Compressive Strength (UCS). Furthermore, the study addresses mining specific phenomena, such as rock mass failure and anisotropic rock behaviour, and assesses their influence on TBM penetration and performance. Ultimately, the research endeavours to contribute to TBM engineering by improving the understanding of input parameters, refining predictive models, and providing practical guidelines for more accurate TBM performance assessments.
The influence of rock and rock mass properties towards prediction of TBM penetration rates
The performance of a Tunnel Boring Machine (TBM) is greatly influenced by the rock and rock mass conditions it encounters. Recently, various methods have been developed to incorporate fractured rock mass and strength into Penetration Prediction Model (PPM)s for TBMs. However, it should be noted that many of these models are based on the rock mass classification system used in documenting the particular tunnel, with limited significance. This study aims to address sensitive and specific rock parameters and rock mass classification systems. The first question focuses on identifying a considerably relevant rock mass classification model for predicting TBM Penetration Rate (PR)s and the indentation process of a disc cutter. By exploring the different classification models, the study aims to determine which rock mass classification model provides the highest relevance and accuracy in understanding TBM rock mass interactions. The second research question delves into characterising rock strength parameters to avoid biased inputs in PPMs. The study seeks to establish acceptable ranges for defining rock strength parameters and explore engineering judgements regarding discarding samples that may introduce biases. The goal is to achieve an unbiased characterisation of rock strength, ensuring accurate input for PPMs. The primary objective of this research is to enhance the understanding of input parameters and their interaction with TBMs and rock masses. By avoiding the ”Garbage In, Garbage Out” scenario, the study aims to improve the reliability and accuracy of TBM performance predictions. To achieve this, the research involves analysing the Gehring and Colorado School of Mines (CSM) PPMs, which form the basis for understanding the interaction between rock masses and TBMs. The study proposes an innovative approach to characterising rock properties, aiming for standardised procedures to determine geomechanical parameters. The procedure utilises a specific correlation between the force applied by the cutter and the penetration rate of the Tunnel Boring Machine, known as Thrust Penetration Gradients. A matrix notation is introduced to characterise specific Thrust Penetration Gradients uniquely, aligned with sensitive geological parameters. Using matrix notation ensures transparency and comprehensible characterisation of TBM performance. To achieve these objectives, the research involves analysing geological and geotechnical conditions, conducting rock mechanical tests, determining machine specific parameters, and developing a more sophisticated method for determining Uniaxial Compressive Strength (UCS). Furthermore, the study addresses mining specific phenomena, such as rock mass failure and anisotropic rock behaviour, and assesses their influence on TBM penetration and performance. Ultimately, the research endeavours to contribute to TBM engineering by improving the understanding of input parameters, refining predictive models, and providing practical guidelines for more accurate TBM performance assessments.
The influence of rock and rock mass properties towards prediction of TBM penetration rates
Der Einfluss von Gesteins und Gebirgseigenschaften auf die Vorhersage von Penetrationsraten von Tunnelbohrmaschinen
Wannenmacher, Helmut (author) / Amann, Florian (tutor) / Fuentes Gutierrez, Raul (tutor) / Marcher, Thomas (tutor) / Perras, Matthew (tutor)
2023-01-01
1 Online-Ressource : Illustrationen pages
Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2023; Aachen : RWTH Aachen University 1 Online-Ressource : Illustrationen (2023). = Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2023
Miscellaneous
Electronic Resource
English
The influence of rock and rock mass properties towards prediction of TBM penetration rates
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