Estimating Second Order Wave Drift Forces and Moments for Calculating DP Capability Plots
Bibliographic record
Abstract
Abstract The DP capability plot is a useful tool to show the limitations of a dynamic positioning system for ships or offshore structures under loading from wind, waves and ocean currents. At the preliminary design stage, it is desirable to use fast methods for calculating the forces and moments caused by the environment, preferably without the need for CFD simulations or model experiments. Empirical methods are available for predicting aerodynamic forces and moments, and hydrodynamic forces and moments from currents, but little is published for second order wave drift forces. Wave drift forces and moment calculations have been carried out using WAMIT, for a series of ship hulls from OSVs to VLCCs and the effects of wave direction and frequency on the Surge, Sway, and Yaw forces and moment have been studied. The presentation of the results allows the user to interpolate the resulting drift forces and moments as a function of wave direction for a given ship size. In terms of wave drift loads calculation, it is found that the very large vessels are dominant in the low frequency waves, while smaller size ships are in high frequencies. The wave frequency and direction in which maximum drift load occurs depends on the ship size.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".