Modeling of Entrainment in Debris Flow Analysis for Dry Granular Material
Bibliographic record
Abstract
Debris flows that entrain sediment by undermining channel beds or scouring channel banks can become exceptionally mobile and destructive. Therefore, the calculation of entrainment plays an important role in debris flow runout analysis. An entrainment model is proposed that takes into account surface erosional effects by considering progressive scouring and shear failure on the channel surface. By considering simple geometry and particle configurations, the equations for the progressive scouring are developed. In deriving the equations for the progressive-scouring mode of erosion, two types of motions are considered: rolling motion and sliding motion. Newton’s law of motion is applied to calculate the acceleration, velocity, and displacement of the particles. A probability-density function (PDF) is used in the calculation of the entrainment rate for different configurations of particle contact. Measurements from flume experiments were used for model verification. It was found that the entrainment rate can be calculated using a normal-distribution PDF. The proposed entrainment model has been shown to be effective in calculating debris flow entrainment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".