Evaluating stability of rigid-column-supported and geosynthetic-reinforced embankments
Bibliographic record
Abstract
Field observations and centrifuge tests indicate that progressive column bending failure accompanies most instabilities of rigid-column-supported and geosynthetic-reinforced (RCGR) embankments. However, recognized guidelines specifically for evaluating the overall stability of such systems featuring bending failure remain limited. A general methodology to calculate the factor of safety (FS) for RCGR embankments using the limit equilibrium method is presented in this article. The focus is on deep-seated slope failures, wherein rigid columns progressively fracture due to subsoil overstressing. The concentric arches model, along with tensioned geosynthetic analysis, informs the determination of vertical and horizontal loads on the column heads. The column's resisting moment stems from its flexural and compression resistance. A mobilization factor for the net thrust on each column is defined to capture the progressive failure. The methodology involves an iterative computational procedure to identify the critical slip surface and the FS using the Fellenius' method. The solution was validated using three case studies, including both centrifuge models and field tests, as well as finite-element analysis. The results indicate that the soil mass contributes the most to resisting sliding and overall stability, followed by columns and geosynthetics. In addition, axial force mainly provides the resisting moment of columns.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".