Limit equilibrium analysis of large-scale reinforced and unreinforced embankments loaded by a strip footing
Bibliographic record
Abstract
The paper describes limit equilibrium analyses of two large-scale geosynthetic reinforced soil embankments and one unreinforced soil embankment that were taken to collapse under a strip footing placed close to the crest. One reinforced embankment was constructed with a relatively extensible and weak polypropylene geogrid and the second with a relatively strong and stiff high-density polyethylene geogrid. The geometry of the embankments and the loading arrangement were the same for all three structures. The focus of the paper is on a comparison of the predicted collapse load for the three structures and the actual observed values. A three-dimensional analytical approach is used to account for possible side-wall friction effects due to the test facility in which the large-scale experimental models were built. The paper also reports details on the interpretation of in-isolation constant load tests and strain measurements used to infer tensile loads in the reinforcement at failure. An important conclusion is that a general two-part wedge analysis approach can be used to predict the collapse footing load for both unreinforced and reinforced sand embankments in this investigation provided careful attention is paid to the selection of soil shear strength and reinforcement tensile capacity.Key words: geosynthetics, reinforced embankments, strip footing, large scale, limit equilibrium analyses.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".