Effects of current suction ratio and recent suction history on small-strain behaviour of an unsaturated soil
Bibliographic record
Abstract
Although the small-strain shear modulus of saturated soils is known to be significantly affected by stress history, consisting of the overconsolidation ratio (OCR) and recent stress history, the effects of suction history on the small-strain shear modulus of unsaturated soils have rarely been reported. In this study, the effects of suction history, which refers to current suction ratio (CSR) and recent suction history, on both the very-small-strain shear modulus (G 0 ) and shear modulus reduction curve of an unsaturated soil, are investigated by carrying out constant net mean stress compression triaxial tests with bender elements and local strain measurements. In addition, the effect of suction magnitude on G 0 and the shear modulus reduction curve is also investigated. At a given suction, G 0 , elastic threshold strain (ε e ), and the rate of shear modulus reduction all increase with CSR. On the other hand, the effect of recent suction history on G 0 is not significant. The effect of direction of recent suction path (θ) on the shear modulus reduction curve is not distinct. However, the magnitude of recent suction path (l) affects the shear modulus reduction curve significantly when θ = –90°.
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 | 0.001 |
| 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 | 0.000 | 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".