Influence of particle-size distribution homogeneity on shearing of soils subjected to internal erosion
Bibliographic record
Abstract
Internal erosion (suffusion) is caused by water seeping through the matrix of coarse soil and progressively transporting out fine particles. The mechanical strength and stress–strain behavior of soils within water-retaining structures may be affected by internal erosion. Some researchers have set out to conduct triaxial erosion tests to study the mechanical consequences of erosion. Prior to conducting a triaxial test they subject a soil sample, which has an initially homogeneous particle-size distribution and density throughout, to erosion by causing water to enter one end of a sample and wash fine particles out the other. The erosion and movement of particles causes heterogeneous particle-size distributions to develop along the sample length. In this paper, a new soil sample formation procedure is presented that results in homogeneous particle-size distributions along the length of an eroded sample. Triaxial tests are conducted on homogeneous samples formed using the new procedure as well as heterogeneous samples created by the more commonly used approach. Results show that samples with homogeneous post-erosion particle-size distributions exhibit slightly higher peak deviator stresses than those that were heterogeneous. The results highlight the importance of ensuring homogeneity of post-erosion particle-size distributions when assessing the mechanical consequences of erosion. Forming samples using the new procedure enables the sample’s response to triaxial loading to be interpreted against a measure of its initially homogenous state.
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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 | 0.001 |
| 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".