Experimental and Numerical Investigation of Beach Slope Effects on the Hydrodynamic Loading of Tsunami-like Surges on a Vertical Wall
Bibliographic record
Abstract
Over the past decades, hydraulic surge generated by dam-break waves has been used to simulate the effects of tsunamis on coastal infrastructure. This study investigates the slope effects on hydrodynamic loading of dam-break waves on structure when propagating over four different inclined beds (0-, 5-, 10-, 15-degree) by experiment and numerical simulation using OpenFOAM and DualSPHysics. Except for small discrepancies in the pressure time-history, numerical results obtained with both OpenFOAM and DualSPHysics agreed closely with the experimental dynamic pressures. The results revealed that the hydrodynamic pressure decreased after an initial impact peak from the lowest transducers in the 5-, 10-, and 15-degree cases when compared with the horizontal case. However, the dynamic pressure of transducers at same corresponding level increased with an increase in the slope. The integrated experimental hydrodynamic forces were similar to the numerical results for the 0- and 5-degree cases, while they were higher for the 10- and 15-degree cases due to insufficient pressure data. By investigating the relation between the force decrease and slopes, a non-dimensional reduction factor was proposed from the linear fitness for slope effects estimation. This experimental and numerical study can provide novel insight on the hydrodynamic force calculation of tsunami-like surges on coastal infrastructures when considering beach slope.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".