## 6 Conclusions  
In this paper, based on an actual project using the pipe curtain method, the main modeling control parameters are determined for numerical analysis; the geometric and mechanical parameters and the analysis cases are clarified; the safety coefficient analysis model of the excavation face under different cases is established by using Flac 3D 6.0 software; the strength reduction method calculation procedure is written; and the safety coefficient is calculated. Different slope inclinations, height spacings, numbers of MJS zones, and strength of MJS zones are analyzed for the stability of the excavation face in soft soil areas with the pipe curtain method.  
(1) For the soft soil area of large-section pipe curtain tunnels, the construction needs to consider not only the stability of the tunnel construction around the tunnel enclosure structure and the surrounding ground deformation in the large-section excavation, but the excavation face's internal soil also needs to take certain reinforcement measures to ensure the stability of the excavation face.  
(2) The analysis results of the parameters under different MJS zone arrangement conditions show that the safety coefficient of the excavation face decreases continuously with the increase in the slope angle of the excavation face, and the safety coefficient of the excavation face decreases continuously with the increase in the spacing of the MJS zone. The safety coefficient of the excavation face also decreases continuously with the increase in the height of the MJS zone arrangement, while the safety coefficient of the excavation face increases continuously with the increase in the strength of the MJS zones themselves and the strength of the soil between the MJS zones. The safety coefficient of the excavation face increases with the increase in the strength of the MJS zones themselves and the strength of the inter-MJS zones; at the same time, the influence laws of the different parameters are slightly different.  
(3) Using XGBoost and LGBM machine learning models, the safety coefficients of the slopes with one and two layers of MJS zone were predicted and analyzed, and the results showed that different machine learning models could predict the safety coefficients of the excavated faces well, and the correlation coefficients were above 0.9. The F-score method was used to calculate the importance of the attributes of different factors and to analyze the weights of the influence of different geometric and mechanical parameters, and the results showed that the strength of the MJS zones themselves and the height of the MJS zone arrangement had the most significant influence on the safety factor.  
W.P.: Methodology, Validation, Writing--Original Draft. Z.W.: Conceptualization, Writing--Review & Editing. Y.D.: Supervision, Project Administration. G.Z.: Formal Analysis. H.Z.: Formal Analysis. T.Z.: Formal Analysis. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was supported by the National Natural Science Foundation of China (Grant No. 52178342); Tianjin Natural Science Foundation (Grant No. 21)CZDJC00590); and Tianjin Transportation Technology Development Project (Grant No. 2022-02) for financial support.  
**Data Availability Statement:** Because of privacy restrictions, the data of this study is unavailable.  
**Conflicts of Interest:** The authors declare no conflict of interest.