Safety Prediction Model for Reinforced Highway Slope using a Machine Learning Method

Abstract

Recycled plastic pin (RPP) has been proved to be an effective and inexpensive solution for shallow slope stabilization. Current practice suggests conducting numerical modeling to find out the desired factor of safety (FS) using RPP in the design of landslide repair. While the slope stability is heavily dependent on soil strength parameters and slope geometry, RPP length and spacing can also play a significant role in reaching the target factor of safety for the highway slope. During this study, a safety prediction model was developed using both statistical and machine learning (ML) approaches to use RPP in slope stabilization. Initially, parametric study was conducted using five different soil strengths, six slope heights, three slope ratios, three RPP lengths, and five RPP spacing configurations. Using the strength reduction techniques of Finite Element Modeling Software PLAXIS 2D, FS was determined for more than 1,000 combinations. Afterwards, a statistical approach was undertaken to determine a safety prediction model containing all possible parameters. Finally, an ML approach was conducted for safety model. The ML approach was found to be more accurate than the classical statistical approach with 85% accuracy of predicting the FS for an RPP reinforced highway slope. The developed model was validated against the values obtained from the numerical modeling, which indicated that the SF obtained from the developed model was in good agreement with those from finite element method (FEM) analysis.

Numerical Study of Recycled-Plastic-Pin- and Geosynthetic-Platform-Supported Embankment over Soft Soil

“…The analysis was conducted using a plane strain model. Standard fixities were used as boundary conditions at the base and the sides of the model ( 19 , 20 ). The standard fixities imply that the movement of the bottom of the model is restricted in all directions and the movement of the vertical sides is restricted in the horizontal directions.…”

Application of Electrical Resistivity Tomography in Geotechnical and Geoenvironmental Engineering Aspect

“…After the summer of 2013, there was a desiccation crack on the slope which created a path for possible intrusion of rainwater (Figure 12a). The presence of a high-moisture zone was observed within 2.1 m (7 feet) of the slope, which indicated a perched water zone because of the crack in the slope [40,41]. In September 2014, the slope failed (Figure 12b) due to the fully softened condition of the soil near the crack.…”

“…Geotechnics 2024, 4, FOR PEER REVIEW 11 the slope [40,41]. In September 2014, the slope failed (Figure 12b) due to the fully softened condition of the soil near the crack.…”