Combined effects of reinforcement and prefabricated vertical drains on embankment performance
Bibliographic record
Abstract
The behaviour of geosynthetic-reinforced embankments constructed over soft cohesive soils installed with prefabricated vertical drains (PVDs) is investigated by numerically examining an embankment constructed over different foundation soils. The partial consolidation during embankment construction, the consequent shear strength gain of the foundation soil, and the effect of the use of reinforcement on the mobilization of shear strength are examined. It is shown that the combined use of reinforcement and PVDs can significantly increase embankment stability and potentially allow the rapid construction of higher embankments than could be achieved with either method of soil improvement alone. Construction rate and spacing of PVDs can significantly affect the degree of consolidation at the end of construction and the stability of the embankment. For the situation examined, the effect of well resistance of typical vertical drains is insignificant. A relatively simple method for calculating the degree of consolidation and the strength gain of the foundation soil during construction is evaluated based on finite element results and is shown to be reasonably conservative. A design procedure is proposed to combine the design of reinforcement and PVDs.Key words: soft clay, prefabricated vertical drain, reinforcement, embankment stability, consolidation, strength gain.
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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 | 0.000 | 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) | 0.001 | 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".