Tsunami-Induced Bore Propagating over a Canal—Part 1: Laboratory Experiments and Numerical Validation
Bibliographic record
Abstract
This companion paper investigates the hydrodynamics of turbulent bores that propagate on a horizontal plane and have a striking resemblance to dam break waves and tsunami-like hydraulic bores. The focus of this paper is on the propagation of a turbulent bore over a mitigation canal using both laboratory experiments and numerical simulations. In the first part of this paper, the effects of canal depth on the time histories of wave height and velocity were experimentally investigated, and the experimental results were used for the validation of the numerical model. The rapid release of water from an impoundment reservoir at depths of do = 0.30 m and 0.40 m generated bores analogous to tsunami-induced inundations. The time histories of the wave heights and velocities were measured at 0.2 m upstream and at 0.2 m and 0.58 m downstream of the canal to study the energy dissipation effect of the mitigation canal. The recorded time series of the water surface levels and velocities were compared with simulation outputs, and good agreement was found between the experimental and numerical water surface profiles, with a Root Mean Square Error (RMSE) of less than 6.7% and a relative error of less than 8.4%. Three turbulence models, including the standard k-ε, Realizable k-ε, and RNG k-ε, were tested, and it was found that all these models performed well, with the standard k-ε model providing the highest accuracy. The velocity contour plots of the mitigation canal with different depths showed jet streams of different sizes in the shallow, medium-depth, and deep canals. The energy dissipation and air bubble entrainment of the bore as it plunged downward into the canal increased as the canal depth increased, and the jet stream of the maximum bore velocity decreased as the canal depth increased. It was found that the eye of the vortex created by the bore in the canal moved in the downstream direction and plunged downward in the middle of the canal, where it then began to separate into two smaller vortices.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".