Bibliographic record
Abstract
A wave-balancing approach, where a ship is hydrostatically balanced on a wave with either the crest or the trough at midship, is often used to assess the inherent strength and stability of the vessel in waves. This work examines the differences between the wave types (sinusoidal and trochoidal) as well as the values of wave length, wave height, and position of the crest along the ship, with the goal of looking for the worst-case conditions for both intact stability and longitudinal strength. A notional destroyer is used as a case study to look at the trends in strength and stability in the upright condition and at angles of heel in waves. The notional destroyer is intentionally similar to but not the same as any existing design. The study shows that looking at a wider set of wave conditions and ship states can identify more extreme wave loading and stability degradation, suggesting that this more detailed analysis would be beneficial as a standard practice. 1. Introduction Both stability and longitudinal strength are key factors in a successful ship design. In both cases, it has long been recognized that the hydrostatic and hydrodynamic effects of waves are fundamentally important. Before the advent of computers and modern numerical models and methods, naval architects relied on hydrostatic analysis to determine the stability and strength characteristics of a given vessel. They typically added safety margins to account for other influences including wave dynamics. Some, however, used the method of "balancing a ship on a wave" to partially account for the influence of waves. In this methodology, the vessel was hydrostatically balanced on the crest or in the trough of a wave. The method was used first for finding bending moments, and later some experts used the method for assessing the stability of a ship. Although the method does not account for the dynamics of ship motion or hull loading transients, it is still used as a design tool today and is embedded in standards for strength (Lloyd's Register, NSR 2012) and stability (BV 1030-1 2012). It does give a "snapshot" of the hydrostatic forces and moments for a particular condition.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".