Critical air entry value-controlled vacuum consolidation of clayey sludge with horizontal drains
Bibliographic record
Abstract
The prefabricated horizontal drain (PHD) is increasingly being used for the treatment of high water content slurries with vacuum preloading, thanks to its higher efficiency as compared to the conventional prefabricated vertical drain. However, certain issues concerning the air–liquid interface of PHD systems, e.g., improved geotextile tubes or slurry pits, require further investigation. In fact, air entry-induced vacuum failure can occur when the surface suction exceeds the critical air entry value (CAEV, corresponding to the intersection point of the compression curve and the void ratio–AEV curve). Existing models, which assume that the excess pore-water pressure remains zero at the drainage boundary, may significantly underestimate the soil consolidation. In this study, a CAEV-controlled large-strain consolidation model is proposed to simulate the dewatering process of vacuum-preloaded clayey sludge, incorporating the geometrical and mechanical nonlinearities and self-weight of soil. Numerical solutions are obtained using the alternative direction implicit algorithm and are validated through laboratory and field model tests. Further analysis indicates that the discrepancy between the proposed model and the traditional model increases with the increasing horizontal spacing of PHDs, decreasing thickness of the geotextile tube or soil layer, and increasing CAEV.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".