Centrifuge modeling of backfill consolidation in soil-bentonite cutoff walls
Bibliographic record
Abstract
Soil-bentonite (SB) is commonly adopted for the backfill of vertical cutoff walls to contain contaminated groundwater. The permeability of SB backfill is dependent on its effective stress state, which is affected by the backfill consolidation process. This paper presents a geotechnical centrifuge model test to simulate the primary consolidation of typical SB cutoff walls with the advantages of reduced scale in time and size. The moisture content and earth pressure of the wall were monitored at varied depths. Test results showed that the rapid consolidation stage developed swiftly and various consolidation indicators exhibited significant development. Within the buried depth over the half (approximately two-thirds), the distribution of vertical effective stress was similar to the Bucknell field testing results, namely that it increased nonlinearly and then tended to stabilize. Also, the cumulative effect of lateral frictional resistance increased with depth and reached its peak value. In the deeper buried areas, lateral frictional resistance decreased sharply before increasing again with increasing depth, while vertical effective stress followed a pattern of significant increase followed by a decrease, which was found to be in good agreement with the predicted model compared in the literature. Analysis of consolidation behaviour and mechanisms could be fully validated from directly monitored indicators, including excess pore pressure dissipation, consolidation settlement, moisture content distribution patterns, and permeability coefficient inside the wall. This centrifuge test may be useful for achieving a comprehensive evaluation of the consolidation behaviour and mechanism of SB cutoff walls.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".