2D Numerical Viscous Predictions of Wave Impact Effects on an Idealized Seawall Rooted in Large Scale Experiments (1:4)
Bibliographic record
Abstract
This study aims to investigate the free-surface flow involved in a wave impact and the vibrational characteristics of an idealized seawall to achieve an improved insight in the design of seawalls and coastal infrastructures subjected to moderate and storm wave conditions. This type of structure can be subjected to frequently occurring as well as high impact wave loadings. In addition to the structural concerns, it is also important to evaluate the importance of the coupling between both fluid and structure motion. In the various steps to design proper wall deflector (wave guide) and to predict pressures and forces following a wave impact, we first present a comparison between numerical results from a CFD model and experimental recordings conducted in a large scale flume in the new Quebec Coastal Physics Laboratory, Canada. A CFD model performance is tested to investigate the more fundamental mechanisms of the underlying processes and to assess real conditions around seawalls to facilitate design process. The preliminary results are based on the assumption of treating the fluid-structure interaction physics as decoupled processes and the wall as a rigid plate. Modal analysis performed on the structure indicates that this approach is adequate, since loadings are of short duration (less than 1 ms) compared to the wall natural frequencies. A maximum local wall pressure of 3.5 MPa has been obtained from an air-pocket impact which generates an instantaneous horizontal force of 4.3×106 N/m.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".