Can the effect of sand fabric on plastic hardening be determined using a self-bored pressuremeter?
Bibliographic record
Abstract
At working levels of strain, prior to peak strength, soil fabric has a large effect on the mobilized stress–strain response. Fabric is also known to affect the number of cycles to liquefaction in loose sands. Better quality analyses require that the effect of fabric on plastic hardening be included in any parameter selection, but measurement of this fabric effect is difficult. Fabric is sensitive to soil disturbance and hence is most appropriately measured in situ, but the effect of density and fabric may have similar effects on in situ tests, which complicates the determination of each of these independent state variables. This paper investigates whether the pressuremeter, an in situ test whose loading may be idealized as simple cylindrical cavity expansion, is able to differentiate between the effects of density and fabric. A realistic critical state constitutive soil model, NorSand, is used for the investigation in detailed finite element simulations of pressuremeter tests. Resolution of the competing effects of the state parameter ψ and fabric is challenging and cannot be achieved from pressuremeter data alone.Key words: fabric, pressuremeter, sand, state, numerical modelling, critical state.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".