Influence of electro-osmosis activation time on vacuum electro-osmosis consolidation of a dredged slurry
Bibliographic record
Abstract
Combining vacuum preloading with electro-osmosis of a dredged slurry is a significantly effective technology for ground improvement. Despite extensive research, the mechanism of vacuum preloading combined with electro-osmosis is still not properly understood, especially regarding the optimum electro-osmosis activation time. In this study, laboratory tests were performed to confirm the influence of electro-osmosis activation time on vacuum electro-osmosis consolidation of a dredged slurry. A total voltage of 12 V was used in five tests with different electro-osmosis activation times. During the combined process of vacuum preloading and electro-osmosis, the vacuum pressure, electric current, and volume of extracted water were monitored. The water content and shear strength were measured after the tests. The results indicated that electro-osmosis was activated when the degree of consolidation for the soil reached 60%. Thus, this approach can significantly promote the effectiveness of soil consolidation. The shear strength distribution along the depth was much more uniform in all tests with electro-osmosis. The shear strength decreased linearly with increasing distance from the anode rows, but sharp increases occurred near the cathode row (or prefabricated vertical drains).
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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 | 0.001 | 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".