Numerical Study of Two Vessels Seakeeping in Waves
Bibliographic record
Abstract
This paper presents a numerical study of seakeeping in regular waves for two vessels in close proximity using commercial seakeeping software HydroStar and an in-house code MOTSIM. The objective was to study the possible sheltering effect of the larger vessel (FPSO) on the smaller one (OSV) during personnel transfer between the two vessels, where one vessel was at some angle relative to the other vessel and there was no connection line between them. The study mainly focused on the OSV motion resulting from the interaction of the FPSO when the OSV was at different headings and wave directions. Initially the OSV motions close to the FPSO (and parallel) were compared with those for the OSV alone. For an un-parallel position of the two vessels, an objective function based on the OSV RAOs motion in roll, pitch and heave directions was used to optimize the OSV position. Finally comparisons between HydroStar and MOTSIM results are provided. The main conclusions are: 1) When the FPSO and OSV are located in parallel, the OSV motions in sway, roll and yaw are larger than the single OSV motions in head waves while surge, heave and pitch are almost the same. The OSV motions in most of the six degrees of freedom are smaller than the single OSV motions when the waves are from other directions (always on the port side of the FPSO), which means that there is a sheltering effect. 2) The simulation results from different OSV rotation angles show that the hydrodynamic interaction between the FPSO and OSV e.g. the sheltering effect is related to the OSV angle and the wave heading. The objective function in roll, pitch and heave RAOs indicates that the OSV should maintain a close to parallel position with the FPSO to minimize motion when the waves come from the port side of the FPSO from 180 to 240 degrees. When the wave direction is around 240 degrees the OSV should have relatively small motion in waves for any OSV rotation angle. 3) A comparison of HydroStar and MOTSIM results shows that the MOTSIM results of a single vessel seakeeping simulation is in a good agreement with HydroStar. In two vessels situation more validation work needs to be done.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".