Micromechanical assessment of an internal stability criterion
Bibliographic record
Abstract
Abstract The internal stability of a soil is a measure of its susceptibility to suffusion and suffosion, two forms of internal erosion. The internal stability of granular filters must be carefully considered when designing new embankment dams and assessing the risk associated with existing embankment dams. Current guidelines for assessing the internal stability of such filters were empirically derived from macroscale observations and consider the shape of the particle-size distribution curve. These guidelines lack a fundamental, scientific micromechanical basis. The initiation and propagation of internal erosion is clearly a particle-scale phenomenon, and this paper applies particulate mechanics to provide a micromechanical justification for one currently used stability criterion. The study used discrete element simulations of idealised virtual soil samples that had various degrees of internal stability when assessed using the criterion proposed by Kézdi [10]. The internal topologies of stable and unstable samples were analysed by considering the distributions of inter-particle contact forces, the number of particle–particle contacts and the average particle stresses. Clear correlations are observed between the filter stability criterion and the average number of contacts per particle and the probability that a given particle participates in stress transmission. The phenomenon of a critical fines content, at which the existing guidelines are no longer considered to be valid, is also considered.
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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 | 0.003 |
| 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 | 0.001 |
| 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".