Velocity Structure of Density Currents Propagating over Rough Beds
Bibliographic record
Abstract
In most practical cases, density-driven currents flow over surfaces that are not smooth; however, the effects of bottom roughness on these currents have not been fully understood yet. Hence, this study aims to examine the velocity structure of density currents while propagating over rough beds. To this end, alterations in the vertical velocity profiles within the body of these currents were investigated in the presence of different bottom roughness configurations. Initially, laboratory experiments were carried out for density currents flowing over a smooth surface to provide a baseline for comparison. Thereafter, seven bottom roughness configurations were tested, encompassing both dense and sparse bottom roughness. The bottom roughness consisted of repeated arrays of square cross-section beams covering the full channel width and perpendicular to the flow direction. The primary results indicate that the bottom roughness decelerated the currents and modified the shape of velocity profiles, particularly in the region close to the bed. Additionally, a critical spacing of the roughness elements was detected for which the currents demonstrated the lowest velocities. For the spacings above the critical value, increasing the distance between the roughness elements had little impact on controlling the velocity of these currents. Moreover, using dimensional analysis, equations were developed for estimating the mean velocities of the currents flowing over various configurations of the bottom roughness. The findings of this research could contribute towards better parameterization and improved knowledge of density currents flowing over rough beds. This can lead to a better prediction of the evolution of these currents in many practical cases as well as improved planning and design measures for the control of such currents.
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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 | 0.000 | 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".