CFD simulations of wind flow across scarped foredunes: Implications for sediment pathways and beach–dune recovery after storms
Bibliographic record
Abstract
Abstract Beach–dune systems are dynamic geomorphic environments subject to erosion during storms and reconstruction during swell‐dominated inter‐storm periods. Wave‐cut scarps are frequently carved into the beach–dune profile, occasionally eroding the stoss slope of the foredune. Although the rapid phases of erosion have been researched and modelled extensively, relatively little is known about beach–dune recovery, especially scarp healing by aeolian processes. Computational fluid dynamic (CFD) modelling was deployed in this study to yield insights into different flow patterns across beach–dune profiles with three model foredunes (unscarped, 1 m scarp, 2 m scarp) for varying wind approach angles (α = 0–45°). The results show that the presence of a scarp substantially modifies the flow dynamics on the backbeach in front of the foredune. Vertical profiles of turbulence kinetic energy indicate that the influence of this flow‐modified zone extends out to about −7hfrom the scarp base (wherehis the scarp height). The reduction in onshore wind speed that is characteristic of this flow‐modified zone favours sand deposition on the backbeach and sand ramp development at the base of the scarp. Shore‐normal wind approach angles yield discontinuous roller‐like vortices with reversing (offshore) flow components at the sand surface, accompanied by the evolution of echo dunes. Oblique wind approach angles yield corkscrew (helicoidal) vortices that lead to the formation of continuous sand ramps alongshore. A conceptual model of scarp healing based on ideas previously discussed in the literature and enhanced by the CFD simulation results highlights the importance of sand ramps for reconnecting the transport system on the beach to the foredune stoss slope, thereby facilitating foredune growth and maintenance.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".