Visualization of dominant stress-transfer mechanisms in experimental debris flows of different particle-size distribution
Bibliographic record
Abstract
Physical modelling of debris flow in a small-scale flume has been carried out to investigate the internal stress-transfer mechanisms within unsteady, saturated, and segregating granular free-surface flows. Measurements of the internal velocity fields within model flows were obtained via planar laser–induced fluorescence and particle image velocimetry. Normalized velocity profiles taken at a section over the flow duration were found to essentially collapse onto a single curve, the shape of which was dependent on the particle-size distribution. While all flows exhibited internal basal slip and shear, for tests on well-graded materials that are most representative of debris flows, the shear rate was found to reduce towards the surface to near-zero, exhibiting near plug-flow. Dimensional analysis shows that particles of different size within these flows experienced different dominant stress-transfer mechanisms — frictional, collisional or viscous. Rapid grain-size segregation therefore is both due to and results in different modes of stress transfer within a single flow. This means that in a segregating and hence, stratified system, different flow regimes will act concurrently at microscale and mesoscale. Results highlight the complexity of debris flows, so that it may be undesirable to ascribe a single microscale constitutive behaviour throughout, and further calls into question the concept of flow regimes for debris flows based on bulk measurements.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Physical modeling of stress transfer in experimental debris flows.
This experimentally studies stress transfer mechanisms in debris flows, not research practice.
Physical modelling of debris-flow stress transfer; geotechnical domain science.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".