Modeling Moored Ship Response to a Passing Ship
Bibliographic record
Abstract
As a ship passes through a confined waterway long period drawdown and associated diffracted waves are produced that will cause nearby moored ships to experience a transient forcing, imposing moments and tensions on the mooring lines. These passing vessel effects can be significant and are highly complex, depending on the characteristics of the mooring arrangement, moored vessels, the waterway geometry, and the passing ship. Assessing the forces induced and the associated structure loads requires understanding of both the drawdown wave and the dynamic behavior of the moored vessel's response. This paper discusses these issues and presents recent studies involving modeling of passing tanker waves and induced forces on moored vessels within berths dredged along the side of a confined navigation channel. Numerical simulations of the passing tanker at varying speeds and the dynamic mooring response of various sized Liquefied Natural Gas (LNG) carriers at berth were examined. These numerical model simulations were complimented by physical model testing and field measurements of several passing tanker waves in the waterway immediately downstream of the terminal site. These measurements will be compared to the numerical modeling results and the influence of the passing ship on the moored vessel and mooring response will be discussed.
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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 | 0.000 |
| 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 | 0.001 | 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".