Computational investigation of baffle configuration on impedance of channelized debris flow
Bibliographic record
Abstract
Channelized debris flows surge downslope in mountainous regions and have large impact forces. Arrays of debris flow baffles are frequently positioned in front of rigid barriers to engage torrents and attenuate flow energy. They are regularly designed on empirical and prescriptive basis because their interaction mechanism is not well understood. Numerical back-analysis of flume experiments using the discrete element method (DEM) is conducted to provide insight on flow interaction with an array of baffles. Varying configurations of baffle height, a second staggered row, and spacing between successive rows are examined. Upstream and downstream kinematics are monitored to capture and compare the Froude number, kinetic energy, and discharge resulting from each baffle configuration. Results from this study reveal that the height of baffles can be categorized relative to the initial approach flow depth (h), namely tall baffles (1.5h) and short baffles (0.75h). Tall baffles are characterized by the development of upstream subcritical flow conditions, whereas short baffles exhibit supercritical upstream conditions. Furthermore, tall baffles facilitate the suppression of overflow, and short baffles lead to excessive overflow that is supercritical in nature. Less flow attenuation occurs as the distance increases both upstream and downstream from each array of baffles. A second staggered row of short staggered baffles is ineffective in reducing debris kinetic energy, whereas tall baffles should be positioned as close as possible.
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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 | 0.000 | 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 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".