Reynolds stress and sand transport over a foredune
Bibliographic record
Abstract
ABSTRACT Reynolds shear stress (RS = – u ′ w ′) and sand transport patterns over a vegetated foredune are explored using three‐dimensional velocity data from ultrasonic anemometers (at 0 · 2 and 1 · 2 m) and sand transport intensity from laser particle counters (at 0 · 014 m). A mid‐latitude cyclone on 3–4 May 2010 generated storm‐force winds (exceeding 20 m s –1 ) that shifted from offshore to obliquely alongshore. Quadrant analysis was used to characterize the spatial variation of RS quadrant components (Q1 through Q4) and their relative contributions were parameterized using the flow exuberance relation, EX FL = (Q1 + Q3)/(Q2 + Q4). The magnitudes of RS and sand transport varied somewhat independently over the dune as controlled by topographic forcing effects on flow dynamics. A ‘flow exuberance effect’ was evident such that Q2 (ejection‐like) and Q4 (sweep‐like) quadrants (that contribute positively to RS) dominated on the beach, dune toe, and lower stoss, whereas Q1 and Q3 (that contribute negatively to RS) dominated near the crest. This exuberance effect was not expressed, however, in sand transport patterns. Instead, Q1 and Q4, with above‐average streamwise velocity fluctuations (+ u ′), were most frequently associated with sand transport. Q4 activity corresponded with most sand transport at the beach, toe, and stoss locations (52, 60, 100%). At the crest, 25 to 86% of transport was associated with Q1 while Q4 corresponded with most of the remaining transport (13 to 59%). Thus, the relationship between sand transport and RS is not as straightforward as in traditional equations that relate flux to stress in increasing fashion. Generally, RS was poorly associated with sand transport partly because Q1 and Q4 contributions offset each other in RS calculations. Thus, large amounts of transport can occur with small RS. Turbulent kinetic energy or Reynolds normal stresses ( u ′ 2 , w ′ 2 ) may provide stronger associations with sand transport over dunes, although challenges exist on how to normalize and compare these quantities. Copyright © 2013 John Wiley & Sons, Ltd.
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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 | 0.001 | 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".