## 4 A New Grouting Evaluation Method
### Validation of Permeability Coefficient Weights for Formulae
#### 4.3.1 Comparative Analysis of Water Inflow at Different Sections of Qiyue Mountain Tunnel  
(1) Verification for slurry injection excavation water inflow  
The excavated section is not continuous, so a point line approach is used for clarity of presentation. According to the calculations, it can be seen that the average and minimum values of the permeability coefficient can be calculated in a way that is very close to the measured influx of water. However, we can know from Figure 13 that the very small value of the calculation of the water surge is generally less than the measured value, which is not enough safety reserve. Meanwhile, the water influx is calculated using a great value when the error is the largest, the size of the error is inversely proportional to the uniformity of the permeability coefficient taken. It is true that the use of very small values of the permeability coefficient can be a good way of reducing economic costs, but it is risky and should be used with caution. (2) Verification of water inflow at workface without slurry  
As most of the site construction is slurry excavation for water-rich strata, there is a lack of actual measurement data without slurry excavation. However, with the research and application of simulation technology, this problem can be better dealt with. Here we use FLAC3D to simulate 15 sections of the Qiyue Mountain tunnel, taking the model size of 100 m \(\times\) 40 m \(\times\) 100 m, showing as Figure 14. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Parameters** & **q** & **p** & **a1** & **a2** \\ \hline Calculation results & 84.495 & 108.968 & 0.613 & 0.790 \\ \hline \hline \end{tabular}
\end{table} 
Table 18: Parameter calculation results. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Indexes** & **B1** & **B2** & **B3** & **B4** & **B5** \\ \hline Subjective weights & 0.241401 & 0.074277 & 0.092068 & 0.026305 & 0.565948 \\ Objective weights & 0.063259 & 0.215245 & 0.257914 & 0.220558 & 0.243024 \\ Combined weights & 0.141063 & 0.153677 & 0.185481 & 0.135718 & 0.384061 \\ \hline \hline \end{tabular}
\end{table} 
Table 19: Weight values of different indexes. Figure 12: Verification flow chart. Figure 13: Comparison of theoretical and measured values. (**a**) Comparison of theoretical and measured water inflow under different permeability coefficients; (**b**) Ratio of different theoretical water inflow to measured values. Where 3 stand for ZDDK365+333 to +313, 4 stand for ZDDK365+323 to +313, 5 stand for PDK365+313 to +308 (L), 6 stand for PDK365+316 to +308 (L), 7 stand for PDK365+319 to +308 (L), 8 stand for PDK365+322\(\rightarrow\)+308 (L), 9 stand for PDK365+325 to +308 (L), 10 stand for YPDK365+315.5 to +312.5 (L), 11 stand for YPDK365+317.5 to +312.5 (L), 12 stand for ZDDK365+307.5 to +292.5 (L), 13 stand for ZDDK365+310.5 to +292.5 (L), 14 stand for ZDDK365+290 to +275, and 15 stand for ZDDK365+293 to +275. Considering the study focus on the seepage field, the model parameters were adopted from the site Class IV envelope parameters, see Table 20.  
The permeability coefficient can be calculate with mean value, while the parameters for the different sections are shown in Table 21. For the permeability coefficients outside the range of overtopping in front of the workplace, the values obtained from the n overtopping are considered to a log-normal distribution and expanded by one order of magnitude, which discretized as shown in Figure 15b with a permeability boundary. Meanwhile, the permeability coefficient obtained from the overtopping of the exploration horizon is equivalent to the overall permeability coefficient for that horizon. For the rock masses outside this range, the five sets of permeability coefficients B1, B2, B3, B4 and B5 obtained from the over-survey were randomly discretized using FLAC3D's DFN plug-in.