Strength and Stress Estimation in Soil Bentonite Slurry Trench Cutoff Walls Using Cone Penetration Test Data
Bibliographic record
Abstract
The Cone Penetration Test (CPT) is widely used for classifying soils and assigning soil properties to the subsurface because it is robust and can be used to quickly collect continuous data with depth. During and subsequent to the construction of a very deep soil-bentonite (SB) slurry trench cut-off wall in Mayfield NSW, Australia, the CPT was used to check the continuity and quality of the SB backfill material. The numerous CPT profiles conducted in the Mayfield wall provided a unique research opportunity for examining how shear strength and effective stress vary with depth. A method is proposed to estimate the undrained shear strength of the Mayfield Wall from the CPT combined with some vane shear data. The results support previous studies that show that the shear strength and the effective stress distributions in SB slurry trench cutoff walls are less than would be expected from a geostatic stress distribution. While there is some increase in shear strength with depth, these data show that the increase is modest and consistent with the less than geostatic stresses. In addition, the authors recommend a general procedure for shear strength and horizontal stress estimation using CPT data in any SB slurry trench application.
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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 | 0.001 |
| 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".