Noncircular Deterministic and Stochastic Slope Stability Analyses and Design of Simple Geosynthetic-Reinforced Soil Slopes
Bibliographic record
Abstract
The purpose of this study is to examine the behavior of simple soil slopes reinforced with geosynthetics using deterministic and stochastic as well as circular and noncircular limit equilibrium method (LEM) of slope stability analyses. Two particular types of stochastic analyses, namely single random variable analyses and spatial variability analyses based on the random limit equilibrium method (RLEM), are performed in order to render probability of failure (Pf). Bishop’s method is used as the circular LEM approach, and the GLE/Morgenstern-Price method together with a global metaheuristic optimization method (Cuckoo search) and a local optimization technique (surface altering optimization) are then used as the noncircular RLEM. Three different failure mechanisms (external, internal, and transitional) are defined in this study. The threshold values of the reinforcement length and tensile strength are presented for both the external and internal failure mechanisms. Contour plots are drawn with noncircular slip surface assumption for different deterministic FS values corresponding to the external, transitional, and internal failure mechanisms as introduced by previous researchers. This investigation evaluates, for the first time, the stochastic FS values for the geosynthetic-reinforced slopes with the noncircular slip surface assumption using LEM, with and without spatial variability. Finally, relevant stochastic design charts for a wide range of the deterministic (mean) FS and internal friction angles are presented for the external and internal failure mechanisms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".