Repair Performance Landslide and Slope Using Bore pile and Ground Anchor on Cipali Toll Road Km 103

One of the causes of on-road collapse slopes is traffic load. Slope failure by road loads usually occurs due to several factors such as soil type, rainfall, land use. This study aims to determine landslide and slope repair performance using bore pile and ground anchor on Cipali Toll Road KM 103. The research method used in this study is the Finite element method. In this research, data collection, modeling parameter determination, slope stability analysis, slope reinforcement analysis, and reinforcement design were carried out with variations in bore pile and ground anchor dimensions. The software program used is a finite element program in the form of PLAXIS to analyze slope stability and estimate the slope failure area. The result of the study is that the R-Value inter is 0.25 with a 1.0341 safety factor. Best repair performance obtained from the addition of reinforcement with ground anchor 2 layer on bore pile 2 with a distance of 2 meters increased the safety factor to 1,913; Borepile capacity calculation with the calculation of normal force and moment iteration, the largest occurs in the DPT (Retaining Wall) stage with a normal load of -37.9 and a moment force of -471.15 which is still able to be borne by bore pile 1. The result of this study is expected to be benchmark and repair material to improve slope stability at km 103 Tol Cipali

Evaluation of Anthropogenic Substrate Variability Based on Non-Destructive Testing of Ground Anchors

The purpose of this paper is to describe the variability of soil rheological properties based on research carried out using load tests of ground anchors under complex geotechnical conditions. The heterogeneity of soil should always be considered when designing geotechnical constructions. In the present case, the earthwork created at the Warsaw Slope revealed an embankment of anthropogenic origin, located in a geologically and geomorphologically complex area of the Vistula valley slope. Excavation protection was anchored mainly in soils of anthropogenic origin. When the acceptance tests of the ground anchor were completed, the subsoil randomness was confirmed using nondirect, geostatistical methods. A standard solid rheological model with nonlinear fitting to the data was used. This model was established to describe the creeping activity of the ground anchor more accurately. The characteristics of man-made embankments were described using the parameters obtained with the rheological model of the subsoil.

Predicting load on ground anchor using a metaheuristic optimized least squares support vector regression model: a Taiwan case study

Failure of ground anchor is a major cause of landslides and severe natural hazards, especially in the highly developed mountainous areas such as New Taipei City. Accurately estimating load on ground anchors is thus essential for evaluating the stability status of slope to prevent landslide from happening. This study first employed correlation analyses to identify possible influential factors of load on ground anchors. Second, various artificial intelligence models were used to map the relationship of the found influencing factors with the current load on ground anchors. The results indicated that the symbiotic organisms search-optimized least squares support vector regression (SOS-LSSVR) model had the optimal accuracy by earning the smallest value of mean absolute percentage error (9.10%) and the most outstanding value of correlation coefficient (R = 0.988). The study applied the established inference model for the real case of estimating load on un-monitoring ground anchors. The analyzed results strongly advised administrators to conduct site surveying and patrolling more frequently to take early proper actions. In summary, the obtained results have demonstrated SOS-LSSVR as an effective alternative for the conventional subjective evaluation methods, which is able to rapidly provide accurate values of load on un-monitoring ground anchors.