Analytical solutions for the stability of stone column-supported and geosynthetic-reinforced embankment
Bibliographic record
Abstract
This study presents a novel prediction model based on the three-wedge method, utilizing a force-based equilibrium model to evaluate the stability of embankments reinforced by stone columns and geosynthetics. The proposed model utilizes six slip surfaces, enabling it to accommodate diverse geometric configurations, shear strength parameters, reinforcement arrangements (i.e., stone columns and geosynthetic), surcharge, water level, and quasistatic seismic coefficients. A constant factor of safety is initially assumed for each slip surface and reinforcement element, although this assumption can be relaxed by varying the strength parameters. The factor of safety is determined analytically through the solution of a polynomial equation. The proposed analytical solutions, which offer a compact form, provide new insights for the three-wedge method and effectively customize the conditions for geosynthetic-reinforced column-supported embankment applications, characterized by wedge interaction between the embankment, clay, geosynthetics, and columns. Validations of the proposed method are performed using the results obtained from the centrifuge test and numerical modelling, demonstrating the reliability of the analytical solution.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".