# Stability Analysis of Jinchuan Hydropower Station Hydraulic Tunnels during Excavation and Unloading
## 4 Numerical Modeling of the Excavation of Adjacent Tunnels
### Comparison between Numerical Modeling and Monitoring Results  
Figure 14 compares the deformation of the surrounding rock of the spillway tunnel obtained by numerical modeling with the results of MS monitoring.  
In the analysis of the MS events in the surrounding rock of the spillway tunnel in Section 3.2, the accumulation zone of the MS events was divided into three zones (stake \(0+340\) m, stakes \(0+400\) m to \(0+450\) m, and stakes \(0+500\) m to \(0+540\) m), i.e., zones I, II, and III, as shown in Figure 14b. In the analysis of the density of energy from MS events, three zones with a high density of energy were also observed, i.e., stakes \(0+300\) m to \(0+340\) m, \(0+420\) m to \(0+450\) m, and \(0+500\) m to \(0+580\) m in the spillway tunnel, as shown in Figure 14c. This paper describes the analysis of the spillway tunnel and diversion tunnel excavation following the actual construction process by using FLAC3D and shows the displacement of the surrounding rock in the tunnel axis section of the spillway tunnel, as shown in Figure 14a. Figure 14a shows that there were three zones with large deformation of the surrounding rock (zones I, II, and III), which corresponded to the three accumulation zones on the density cloud diagrams of MS events and energy from the events. Furthermore, the numerical modeling results corresponded to the risk areas revealed by MS monitoring, and the two methods corroborated each other. Then, the numerical modeling results were compared with the conventional monitoring results to prove the accuracy of the numerical modeling results, thus demonstrating the feasibility of the research method integrating MS monitoring, numerical modeling, and conventional monitoring.  
Figure 15 compares the detected stress value in numerical modeling with the monitoring results of the rock bolt stressometer at stake \(0+457\) in the spillway tunnel. Overall, there are similarities between the traditional monitoring and numerical modeling: (1) The stress changed slowly in the beginning and suddenly in the latter stages. (2) The stress change at the burial depth of 3 m was greater than that at the burial depth of 6 m. According to the time-segment-based analysis, the excavation of the first layer of the spillway tunnel after October 6 gradually approached the structural plane, and the excavation in the control area of the structural planes f31 and f27 caused drastic changes to the rock bolt stressometer located at stake \(0+457\) m in the spillway tunnel. The numerical modeling results show the same characteristics of change. Particularly, the stress value increased abruptly around steps  
Figure 14: Comparison between numerical modeling and MS monitoring results.  
85,000 and 90,000. Based on the step statistics in the numerical calculation process, it can be found that the two abrupt increases corresponded to the excavation of stakes 0 + 464 m to 0 + 530 m and 0 + 414 m to 0 + 424 m, both of which were caused by the excavation in the control area of f31 and f27 (f31 exposure area: stake 0 + 404 m; f27 exposure area: stake 0 + 450 m), which is consistent with the measured results of the rock bolt stressometer. The accuracy of the numerical modeling results was verified by the conventional monitoring results, and the numerical modeling and the MS monitoring supported each other. These results show that the research method integrating MS monitoring, numerical modeling, and conventional monitoring is feasible. Numerical modeling allows advanced calculation according to the construction process to delineate the risk zone in advance and to serve as a guide for construction design; MS monitoring can provide real-time monitoring of the surrounding rock, forecast the abnormal MS parameters during construction promptly for early warnings, and adjust the construction progress in real time; conventional monitoring is used to check the accuracy of the other monitoring and modeling processes.  
Figure 15: Comparison between numerical modeling and conventional monitoring results.