Prediction of Stabilizing Moments and Effects of U-Tube Anti-Roll Tank Geometry Using CFD
Bibliographic record
Abstract
U-tube type stabilizers have been used in ships and offshore vessels to reduce roll motion. The motion of the fluid in the tank creates moments that counteracts the roll moment of the ship. With space and weight constraints, a well designed U-tube tank is crucial for providing effective stabilization. Geometric parameters play important roles in defining the stabilizing performance of such tanks. The effects of these parameters are sometimes interrelated. Computational Fluid Dynamics (CFD) is a useful tool that can be used to predict stabilizing moments and phase lags of U-tube tanks in a short period of time. In order to use the CFD code reliably, validation is required. In this paper, a CFD code’s ability to predict stabilizing moments created by fluid in various U-tube tank geometries was validated. The effects of tank parameters on the stabilizing moments were investigated and compared with published experiment data. The results were found to be in good agreement with the model test data. The code can be used to give a preliminary evaluation of tank performance for design purposes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".