Rock Mechanics
Ali Kazempour Osalou; Sayfoddin Moosazadeh; Ali Nouri Qarahasanlou; Mohammad-Reza Baghban Golpasand
Abstract
Nowadays, tunnel excavation plays a major role in the development of countries. Due to the complex and challenging ground conditions, a comprehensive study and analysis must be done before, during, and after the excavation of tunnels. Hence, the importance of study and evaluation of ground settlement ...
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Nowadays, tunnel excavation plays a major role in the development of countries. Due to the complex and challenging ground conditions, a comprehensive study and analysis must be done before, during, and after the excavation of tunnels. Hence, the importance of study and evaluation of ground settlement is dramatically increased since many tunnel projects are performed in urban areas, where there are plenty of constructions, buildings, and facilities. For this reason, the control and prediction of ground settlement is one of the complicated topics in the field of risk engineering. Therefore, in this paper, the proportional hazard model (PHM) is used to analyze and study the ground settlement induced by Tabriz Metro Line 2 (TML2) tunneling. The PHM method is a semi-parametric regression method that can enter environmental conditions or factors affecting settlement probability. These influential factors are used as risk factors in the analysis. After establishing a database for a case study and using a proportional hazard model for surface settlement analysis, and then by evaluating the effect of environmental conditions on the ground surface settlement, it has been found that the risk factors of grouting pressure behind the segment, the ratio of tunnel depth to groundwater level, and drained cohesion strength at a significant level of 5% have a direct effect on the probability of settlement. The results also showed that the effect of grout injection pressure on ground subsidence is more than other parameters, and with increasing injection pressure, the probability of exceeding safe subsidence values decreases. In addition, it has been found that increasing the risk factor for the ratio of tunnel depth to groundwater level reduces the probability of exceeding the safe ground settlement. Finally, increasing the number of risk factors for drained cohesion strength increases the probability of exceeding safe settlement.
M. Kamran
Abstract
Drillability is one of the significant issues in rock engineering. The drilling rate index (DRI) is an important tool in analyzing the drillability of rocks. Several efforts have been made by the researchers to correlate and evaluate DRI of rocks. The ensemble learning methods including the decision ...
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Drillability is one of the significant issues in rock engineering. The drilling rate index (DRI) is an important tool in analyzing the drillability of rocks. Several efforts have been made by the researchers to correlate and evaluate DRI of rocks. The ensemble learning methods including the decision tree (DT), adaptive boosting (AdaBoost), and random forest (RF) are employed in this research work in order to predict DRI of rocks. A drillability database with four parameters is compiled in this work. A relationship between the input parameters and DRI is established using the simple regression analysis. In order to train the model, different mechanical properties of rocks incorporating the uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), brittleness test (S20), and sievers’ J-miniature drill value (Sj) are taken as the input variables. The original DRI database is randomly divided into the training and test sets with an 80/20 sampling method. Various algorithms are developed, and consequently, several approaches are followed in order to predict DRI of the rock samples. The model performance has revealed that RF predicts DRI with a high accuracy rate. Besides, the Monte Carlo simulations exhibit that this approach is more reliable in predicting the probability distribution of DRI. Therefore, the proposed model can be practiced for the stability risk management and the investigative design of DRI.
