Effects of fines content and stress history on surface erosion of cohesive soils
Bibliographic record
Abstract
Surface erosion involves the removal of soil from ground surfaces, riverbeds, or seabeds by flows or currents. While internal erosion has been widely researched, surface erosion—especially in cohesive soil—remains less explored from a geotechnical perspective. This study examines effects of fines content and stress history on the erodibility of cohesive soils. Using five materials with varying fines contents, key erosion parameters, including erosion coefficient ( K d ) and critical shear stress ( τ c ), were measured in a purpose-built apparatus. The results were correlated with the shear strength under zero normal stress ( τ d s ) obtained from a modified direct shear test. It was found that while τ c showed a strong correlation with τ d s in soils with varying fines contents, this correlation weakened under stress history effects. In contrast, the correlation between K d and τ d s remained more consistent for varying fines contents and stress history conditions. Notably, higher fines content did not always enhance erosion resistance, and excessive fines could reduce the erosion resistance. Increasing OCR improved the erosion resistance, with the most notable changes occurring at OCR ≤ 4. Moreover, the stress history effects on soil erodibility were visualized by linking the erosion coefficient to the void index.
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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 | 0.000 |
| 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".