Characterizing the wave loading on closely arranged pile breakwaters under regular and irregular waves
Bibliographic record
Abstract
Pile breakwaters have been widely applied to protect harbors and coastal regions from extreme waves. To ensure the survivability of pile breakwaters in harsh sea conditions, an accurate estimate of the maximum wave loading is essential for structural design. In this paper, a series of experiments considering the effects of wave steepness, relative wave height, relative pile diameter, and relative pile distance are conducted to measure the loading of regular and irregular waves on pile breakwaters. Moreover, a high-fidelity numerical solver is comprehensively validated against the experimental data and then utilized to reveal the process of wave–pile interactions. Two distinct flow patterns relying on the relationship between the pile diameter D and the wavelength L are identified, which lead to different wave loading characteristics. By evaluating the performance of different approaches in analyzing the maximum wave force, the “wave force approach” is adopted by introducing a pile group coefficient Kgroup to account for the magnification of wave force compared with a single pile. Finally, a predictive model for Kgroup of pile breakwaters is developed based on the experimental data, which is proved to be applicable for regular and irregular unidirectional waves orthogonal to the piles.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".