Investigations into Ship Induced Hydrodynamics and Scour in Confined Shipping Channels
Bibliographic record
Abstract
Taylor D, Hall K and Macdonald N, J., 2007. Investigations into ship induced hydrodynamics and scour in confined shipping channels. Journal of Coastal Research, SI 50 (Proceedings of the 9th International Coastal Symposium), 491 – 496. Gold Coast, Australia, ISSN 0749.0208 Deep draft ships transiting through confined channels can significantly alter surrounding hydrodynamic conditions. Drawdown is a long-period motion, in the order of 30 to 150s, caused by the ship displacing water from the channel. The long-period character of the drawdown wave causes relatively large near-bed currents which are capable of inducing significant rates of sediment transport. The Burlington Shipping Channel is a confined channel, 88m wide and 800m long, which connects Hamilton Harbour to Lake Ontario. Significant scour levels have been observed near the entrances to the channel and along the nearby sheet-pile channel piers. A series of investigations have been undertaken to determine the extent of scour and the magnitude of the forces causing scour. Investigations discussed in this paper include bathymetric and hydrodynamic data collection and numerical modelling using the ship wake and drawdown model SGH (Ship-Generated Hydrodynamics). Hydrodynamic data was collected for seven ship movements to investigate hydrodynamic forces contributing to the scour. The applicability of simulating drawdown using a two-dimensional depth-averaged ship drawdown model such as SGH has been investigated. The model achieved a good level of calibration, particularly in the mid-sections of the channel and near the western entrance. The investigations have confirmed the validity of using sophisticated ship models such as SGH to investigate complex hydrodynamic and scour processes associated with deep draft ships transiting through confined channels. These models are capable of realistically simulating the spatial variation in sediment transport potential in confined channels and could be used to assist in the design of appropriate channel protection.
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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 | 0.001 |
| 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) | 0.000 | 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".