Quantitative Analysis of Excavation‐Damaged Zones for Effective TBM Tunnel Support Design

The mechanical characteristics of the excavation‐damaged zone (EDZ) are essential in tunnel engineering for scientific design, safe construction, stability evaluation, and support optimization. Due to the lack of quantitative research on the mechanical characteristics of the EDZ and their impact on engineering support design, this paper proposes a quantitative investigation of the EDZ and a method for tunnel support optimization based on field monitoring studies. Then, the Gaoligong Mountains tunnel was analyzed using this method to quantify the mechanical characteristics of the EDZ during the tunnel boring machine (TBM) excavation and its impact on engineering support design. Firstly, the quantitative investigation of EDZ and engineering support optimization method was proposed based on the zonal crack density statistics in the EDZ, the evaluation of the zonal equivalent mechanical parameters using the Hoek–Brown criterion, stability analysis of surrounding rock considering EDZ zonal deterioration, and the engineering support design method. Secondly, the evaluation of the EDZ depth, rock mass wave velocity, and crack propagation in the surrounding rock mass during TBM excavation was analyzed based on field monitoring tests (the ultrasonic test, acoustic CT test, and digital borehole camera test) result of the Gaoligong Mountain tunnel. Thirdly, using the above method, the zonal equivalent mechanical parameters of the rock mass in the EDZ were calculated, and stability analysis of the surrounding rock considering EDZ zonal deterioration was carried out. Finally, the anchor design parameters (the length, pitch, and row spacing of the anchor) of the surrounding rock for the Gaoligong Mountain tunnel were analyzed and optimized. A second stability analysis of the surrounding rock was also carried out to validate the new approach using the conventional rock mass mechanical parameter equivalent. The depth of the plastic zone (7.4 m) in the proposed method was more in agreement with the field monitoring data (6∼8 m) as compared to the traditional method (9.2 m). Hence, this method could provide a stronger foundation for assessing and optimizing the tunnel design scheme and supporting measures.