Stability of saturated granular columns: Role of stress-dilatancy and capillarity
Bibliographic record
Abstract
The granular column collapse experiment is an important benchmark case for the physical and numerical study of transitional mass flows. Unlike columns of dry granular materials, the presence of a relatively incompressible fluid, such as water, in the voids of saturated columns complicates the shear behavior of the column by becoming a function of the coupled shear and volumetric behavior of the grain–fluid system. Dilative or contractive behavior at the pore level will cause a decrease or increase, respectively, in the pore fluid pressure. These changes in effective stress, in turn, will define stability or instability and length of runout. Here we use the new opportunity provided by transparent soil to observe air entry within saturated columns to explore the hypothesis that the entry pressure provides the maximum contribution of capillary pressure at incipient failure, thereby providing a quantitative control on the stability of dilative granular columns. Furthermore, the mobility of densely packed saturated columns subject to collapse was significantly influenced by air entry. An analytical model, based on this assumption of limiting capillary pressure, is able to describe the stability of the experimental columns as well as the larger dataset from the literature, reframing the previous empirical stability threshold using limit equilibrium and soil material parameters. Our results demonstrate the importance of stress-dilatancy and air-entry phenomena on the rapid shear behavior of saturated granular materials.
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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".