Predicting Open TBM performance in hard rock has been a long-standing challenge in tunnelling engineering. The CSM and NTNU models have been widely used to estimate TBM advance rates and cutter forces based on rock mass proper ties and operational parameters. These models are detailed and widely applied, capable of predicting TBM performance with varying but acceptable accu racy, depending on the amount of input data availa ble. However, they require comprehensive rock property investigations, which can be time-consuming and costly. Data analysis of a global database from 105 tunnelling projects revealed strong correlations between diameter and torque, power, and thrust. Building on these findings, the study combines lin ear regression and random forest models to deliver a fast, cost-effective tool for feasibility studies, performance checks, and optimising TBM design and oper ation. Monte Carlo simulations with 10,000 diameter samples defined the expected operational ranges for power, thrust, and torque. Sensitivity analysis further revealed that a 10% increase in diameter led to a 12.06% rise in power, a 13.80% increase in torque, but a 17.41% decrease in thrust. Conversely, a 10% reduction in diameter resulted in power decreasing by 17.66%, torque by 35.53%, and thrust by 26.04%, confirming torque as the most sensitive metric.
Sensitivity and Monte Carlo Analysis of Open TBM Diameter: Impacts on Power, Thrust, and Torque / Farzay, Oveis; Cardu, Marilena; Jamali, Seyedkhashayar. - In: GEOTECHNICAL AND GEOLOGICAL ENGINEERING. - ISSN 0960-3182. - ELETTRONICO. - (2025), pp. 1-12. [10.1007/s10706-025-03212-0]
Sensitivity and Monte Carlo Analysis of Open TBM Diameter: Impacts on Power, Thrust, and Torque
Farzay, Oveis;Cardu, Marilena;Jamali, Seyedkhashayar
2025
Abstract
Predicting Open TBM performance in hard rock has been a long-standing challenge in tunnelling engineering. The CSM and NTNU models have been widely used to estimate TBM advance rates and cutter forces based on rock mass proper ties and operational parameters. These models are detailed and widely applied, capable of predicting TBM performance with varying but acceptable accu racy, depending on the amount of input data availa ble. However, they require comprehensive rock property investigations, which can be time-consuming and costly. Data analysis of a global database from 105 tunnelling projects revealed strong correlations between diameter and torque, power, and thrust. Building on these findings, the study combines lin ear regression and random forest models to deliver a fast, cost-effective tool for feasibility studies, performance checks, and optimising TBM design and oper ation. Monte Carlo simulations with 10,000 diameter samples defined the expected operational ranges for power, thrust, and torque. Sensitivity analysis further revealed that a 10% increase in diameter led to a 12.06% rise in power, a 13.80% increase in torque, but a 17.41% decrease in thrust. Conversely, a 10% reduction in diameter resulted in power decreasing by 17.66%, torque by 35.53%, and thrust by 26.04%, confirming torque as the most sensitive metric.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/3001219