Investigation of performance of rock and artificial rubble mound breakwater armour using physical modelling and OpenFOAM
Bibliographic record
Abstract
Abstract The widely used traditional armour units might be promoted by more detailed analysis for better performance. This research investigates the stability, run-up and overtopping performances of three traditional armours, including rock, antifer and tetrapod layer of a rubble-mound breakwater by regular and irregular waves. The comparison is made by the results obtained from several verified numerical models in OpenFOAM library and OlaFOAM solver and also utilizes the common wave flume test procedure. The calibration process has two main parts, which include mesh solution and model turbulence. In this process, the optimal mesh and the most effective turbulence model were selected. The results indicate that the lowest and highest values of relative run-up and overtopping discharge were observed for rock armour and Antifer armour units, respectively. The amount of the relative run-up for tetrapod was slightly more than the rock armour. Also, it was observed that the measured stability parameter Ns on the armour unit was controlled. The results indicate that Antifer units can lead to a more stable armour layer than other units.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".