Prediction of Sloshing Effects Using a Coupled Non-Linear Seakeeping and CFD Code
Bibliographic record
Abstract
In this paper, a numerical approach for predicting sloshing or roll-stabilization effects is proposed. A 3D non-linear time domain seakeeping code, MOTSIM, was coupled with a commercial CFD code (Flow-3D) and used to predict roll stabilizing performance of an unconventional U-tube tank installed in an oceanographic vessel. The codes were fully coupled and thus provided coupled effects of the external flow field and the motion of the fluid with a free surface inside the anti-roll tank on the ship motion in six degrees of freedom. MOTSIM is a well validated code that has been proven to provide accurate motion prediction for various vessels. The CFD code allows for modeling of complex tank geometry as well as detailed investigation of locations in the tank where severe loads might be experienced. Comparisons of the simulation results with experimental data showed good agreement and significant effects of the anti-roll tank on decreasing the ship’s roll motion. This study also demonstrated the coupled code’s potential use for any type of sloshing problems including the design of roll-stabilization tanks and LNG carriers.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".