Alongshore velocities and turbulence in the swash and surf zone forced by oblique, monochromatic waves on smooth and rough impermeable beaches
Bibliographic record
Abstract
Wave breaking on beaches drives complex nearshore flow patterns and turbulence. A series of controlled laboratory experiments were conducted to better understand swash and surf zone hydrodynamics on smooth and rough planar impermeable beaches under obliquely incident waves. The experiments were performed in a 26.0 m long, 20.6 m wide, and 1.0 m deep wave basin using a fixed concrete beach with a 1:10 slope. The beach surface was roughened through sandblasting following smooth surface experiments to allow a direct comparison between smooth and rough bed conditions. Regular waves with heights of 0.10 m, 0.125 m, and 0.15 m and a period of 2.0 s were generated with the wave paddle positioned at angles of 0°, 10°, and 20° with respect to the beach. An array of sensors recorded high-frequency data on water surface elevations and velocities at multiple cross-shore positions. Differences in the cross-shore velocities were most evident near the breaker zone, with peak onshore velocities approaching 0.8 m/s. Bed roughness was found to delay wave breaking and modulate velocity profiles compared to smooth bed conditions. Alongshore velocities remained predominantly positive, indicating consistent wave-driven mean flow along the beach, generally increasing with wave paddle angle, and measurements over the smooth bed contained larger nearbed gradients and alongshore flows during flow reversal. Mean nearbed turbulent kinetic energy ( k ) in the surf zone was on the order of 10 -3 m 2 /s 2 . Roughness resulted in an increase of nearbed of approximately 12% at the sensor closest to wave breaking. Analysis of nearbed Reynolds stresses close to the wave breaking location showed roughly a factor of 2 increase for beach normal waves compared to obliquely incident waves. This may suggest influence of reflections off of the beach increased by the intermediate-to-steep slope in this study.
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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 | 0.000 |
| 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".