# Prediction of Friction Resistance for Slurry Pipe Jacking
## 4 The Verification of the Effectiveness of the Proposed New Approach
### Comparison between the Predicted Friction Resistances and the Field Data
Furthermore, they have different overburden depths of 2.72-8.5 m, overcut of 0-20 mm, and pipe diameters of 0.66-4.06 m. All of these characteristics provide good foundations for identifying the capability of the prediction models. In Table 5, for each of the drives, measured frictional force values are presented and compared to values calculated by the approaches of the existing models. One can see that, for most cases, the prediction results of the models (M 1 and M 2) established based on Hypothesis 1 are generally too small. This is because it is correct only when the overcut is stable and the pipeline slides on its base inside the annular gap remaining open. The same problem is encountered in M3 (established based on Hypothesis 2), which is probably more due to ignoring the occurrence of pipe-soil contact decreasing the magnitude of the effective friction coefficient. Obviously, for slurry pipe jacking, the prediction friction based on these two assumptions may be insufficient and unsafe. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Cases** & **C 1 (H City)** & **C 2 (Shanghai)** & **C 3 (F City)** & **C 4 (Neuilly)** \\ \hline
**Geotechnical Description** & **Organic Silt** & **Silty Clay** & **Fine Sand** & **Sand and Gravels** \\ \hline \(h\) (m) & 8.15 & 8.5 & 2.72 & 5 \\ \(D_{p}\) (m) & 0.96 & 4.06 & 1.2 & 0.66 \\ \(\Delta R\) (m) & 10 & 20 & 10 & 0 \\ \(\gamma\) (kN/m3) & 18 & 19.5 & 20.5 & 21 \\ \(c_{s}\) (kPa) & 10 & 30 & 0 & 0 \\ \(\varphi\) (\({}^{\circ}\)) & 10 & 25 & 30 & 40 \\ \(E_{s}\) (MPa) & 12 & 25 & 30 & 35 \\ \(v_{s}\) & 0.35 & 0.3 & 0.25 & 0.2 \\ \(e\) & 2 & 1.5 & 1 & 0.4 \\ \(c_{m}\) (kPa) & 0.1 & 0.1 & 0.1 & 0.1 \\ \(\beta\) & 0.6 & 0.5 & 0.85 & 0.5 \\ \(W\) (kN/m) & 5.5 & 90.2 & 8.5 & 2.2 \\ \(\mu_{m}\) & 0.01 & 0.01 & 0.01 & 0.01 \\ \(P_{m}\) (kPa) & 89.97 & 110.54 & 62.28 & 45.94 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Parameters that are needed to calculate the prediction equations in each case. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Cases** & **C 1** & & **C 2** & & **C 3** & & **C 4** \\ \hline  & & **Ratio** & & **Ratio** & & **Ratio** & & **Ratio** \\ \hline \(f_{\text{meas. }}\) (kN/m)** & 1.5 & & 36.16 & & 3.78 & & 9.75 & \\ \hline M 1 & 0.48 & 32\% & 20.00 & 55\% & 2.28 & 60\% & 0.80 & 8\% \\ M 2 & 2.68 & 179\% & 76.10 & 210\% & 2.28 & 60\% & 0.80 & 8\% \\ M 3 & 3.0  
The calculated results of M4 are much larger than the measured data, which presumably result from ignoring the 'vault effect' of soil, so that the soil pressure has been overestimated. Apart from M4, the other models established based on Hypothesis 3 (M5-13) have shown some applicability in case 4, in which the overcut of C4 is equal to zero, which is exactly in line with the assumption of the full contact of pipe-soil of Hypothesis 3. Except for C4, the prediction results of other cases are much larger, and the amplitude may be up to 30 times the measured data. Therefore, for slurry pipe jacking, Hypothesis 3 is generally over-conservative. Although it can ensure the structural safety of the design, it may also cause a much higher construction cost. From what we have analyzed above, the existing models have good prediction results only when the field case is consistent with the basic hypothesis of each model. However, it is also these hypotheses that determine their limited applicability. Table 6 presents the friction resistances calculated by the approach of this paper, by using the parameters of Terzaghi silo model chosen from different authors (Table 1). Better agreements with the field data in each of these cases were obtained, which indicate that compared with the existing prediction models, the approach of this paper that considers the effect of lubrication and interaction of pipe-soil-slurry not only has higher accuracy but is also more flexible and has wider applicability. Moreover, the approaches of PJA (M9), ATV A 161 E-90 (M11), ASTM F 1962-11 (M12), and GB 50332-2002 (M13) provide higher prediction accuracy than the other ones (Table 6).