Interpretation and modelling of deformation characteristics of a stiff North Sea clay
Bibliographic record
Abstract
An investigation into the behaviour of North Sea glaciomarine clays was carried out in which triaxial tests were conducted on both natural and reconstituted samples to assess the effects of structure. Although the tests were conventional CID tests, high quality instrumentation was used. The tests were also technically difficult both because of the very long test durations and because some of the samples were swelled back to very low effective stresses so that the effect of swelling on the influence of structure on the soil behaviour could be assessed. A "Class A" prediction of the behaviour in these tests was carried out using the BRICK model. Although the model is not designed to account for the influence of structure, it was found that its effects could be simulated by allowing the soil to have artificially high overconsolidation ratios (OCRs) so that the high undrained shear strengths resulting from structure could be modelled. Making the simple assumption that the decay of stiffness could be scaled from that of London Clay, reasonable predictions of the behaviour were made. The discrepancies between the predictions and the measured behaviour became significant only at the lowest stresses, where structure dominates the behaviour of the natural soil.Key words: laboratory testing, small strain stiffness, stiff clays, structure of soil, numerical predictions, shear deformation properties.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 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".