Influence of anisotropic consolidation on the instability of loose granular soils under undrained and drained loading
Bibliographic record
Abstract
Previous studies, mostly experimental, have reported conflicting observations on the effect of the initial anisotropic consolidation stress ratio (η0) on the stress ratio at the onset of instability (η f) for drained and undrained loadings that involve static liquefaction. They indicate that as η0 increases, η f could decrease, increase, or remain invariant, albeit without providing potential mechanistic factors. In this study, the anisotropic critical state theory (ACST) is used to investigate potential factors, including compressibility, state, and fabric anisotropy, that can explain the influence of η0 on η f under undrained and drained loading. The assessments consider numerical simulations with the ACST-based SANISAND-F model, insights from SANISAND-F-based instability criteria, the instability surface concept, and available experimental observations. Our findings show that compressibility and fabric anisotropy (and its evolution) are key factors in explaining the influence of η0 on η f. In particular, the results show that if fabric evolution is not substantial, an increase in η0 decreases η f for materials with significant compressibility, whereas the effect of η0 in low compressibility materials is minimal. On the other hand, for materials that promote fabric evolution, the results suggest that the effect of fabric changes counteract compressibility effects, potentially increasing η f. Finally, the study also highlights the need for further research to better understand potential coupled effects of compressibility and fabric evolution on materials prone to significant loading-induced fabric changes.
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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 | 0.001 |
| Scholarly communication | 0.001 | 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".