Compression and consolidation characteristics of structured natural clay
Bibliographic record
Abstract
The compression and consolidation behavior of some structured natural clays are discussed. It is shown that for some structured natural clays, the relation between void ratio (e) and mean effective stress (p′) is more linear in a ln(e + ec) ln(p′) plot (where ec is a soil parameter) than in an e ln(p′) plot. It is proposed that for structured natural clay with a sensitivity value greater than 4, a linear ln(e + ec) ln(p′) relation can be used in settlement and consolidation calculation. The effect of introducing a linear ln(e + ec) ln(p′) relation on the calculated loadsettlement curve and consolidation behavior of structured clays is discussed. The linear ln(e + ec) ln(p′) relation was incorporated into the modified Camclay model by modifying the hardening law of the model. It is shown that using the linear ln(e + ec) ln(p′) relation simulated the consolidation behavior of the structured natural clays better than using the linear e ln(p′) relation.Key words: structured natural clay, compression, consolidation, constitutive model, numerical analysis.
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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 | 0.000 |
| 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".