Accurate Prediction and Modeling of Overbreak Phenomenon in Tunnel Excavation Using Rock Engineering System Method
Publication: International Journal of Geomechanics
Volume 24, Issue 6
Abstract
According to various human needs, such as mineral supply, transportation, and underground storage, tunnel excavation has become commonplace today. However, one of the undesirable phenomena encountered during tunnel excavating, particularly when employing drilling and blasting techniques, is the overbreak phenomenon (OBP). This phenomenon not only compromises the safety of the work environment but also leads to increased operating costs. Therefore, accurately predicting the occurrence of OBP in tunnel excavation is of utmost importance. Due to the numerous uncertainties and complexities associated with rock formations, traditional methods have limited accuracy in predicting OBP. Consequently, this research used the rock engineering system (RES) method to comprehensively understand the physical and mechanical characteristics of the rock mass at any given point. By employing the RES method, accurate modeling of the OBP can be achieved in a time- and cost-efficient manner without requiring extensive and complicated coding. To construct the model using the RES method, 217 data points from three case studies were utilized: the Tarzeh underground coal mine in Iran, the Azad tunnel on the Tehran-North road in Alborz, Iran, and an Indian mine. The parameters considered in this study that affect the OBP (%) included perimeter hole powder factor (PPF, kg/m3), spacing-to-burden ratio of contour holes (S/B, kg), tunnel section area (A, m2), specific drilling (SD, m/m3), and rock mass rating (RMR, %). To compare and evaluate the RES method, various regression methods were also employed. Statistical criteria revealed that the RES method (RMSE = 0.0046, MSE = 0.068, R2 = 0.945) demonstrated high accuracy compared to other regression methods. Consequently, it can be concluded that the RES is a highly valuable and essential tool for rock engineers.
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Data Availability Statement
All data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request.
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© 2024 American Society of Civil Engineers.
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Received: Aug 11, 2023
Accepted: Jan 4, 2024
Published online: Mar 27, 2024
Published in print: Jun 1, 2024
Discussion open until: Aug 27, 2024
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