Powering and Seakeeping Characteristics of a Displacement Vessel Hullform With Waterline Parabolization
Bibliographic record
Abstract
Waterline parabolization is a design procedure used for displacement vessels to decrease the wave resistance of the hullform through the addition of amidships bulbs. The bow and shoulder wave system of a parent hullform are interfered with by the wave system produced by the amidships bulb. Despite an overall increase in vessel beam, amidships bulbs can produce enough wave cancellations to decrease the total resistance. The designer must pay close attention to the amidships bulbs longitudinal positioning and fairing. Two design approaches can be taken: one the amidships bulbs are “retro-fit” to the existing parent hullform increasing the vessels displacement, and second the displacement is held constant producing an entirely new “optimized” design with shallower entrance and exit angles. Optimal shapes for the amidships bulbs were developed numerically using a potential flow code based on Dawson’s method coupled with a quasi-Newton nonlinear programming algorithm, Calisal et al. (2009a). Tow-tank tests at Istanbul Technical University (ITU) confirmed that amidships bulbs could reduce the effective power by 15%. Given a significant improvement in powering, this paper compares the seakeeping performance of the parent, optimized, and retro-fit hullforms at different sea state conditions and quantifies fuel consumption and acceleration levels. SHIPMO PC, a ship motion program based on strip theory is used to compare the three different hullforms. Three speeds are considered: the design speed of 12.5 knots, a reduced speed of 11 knots associated with the expected loss of speed from added resistance, and 6 knots to represent significant speed reduction. Roll, pitch and heave motions along with added resistance are estimated. Accelerations at the bridge are used to evaluate effects on the crew. For various sea states the most significant motion is roll in beam seas and is incurred at low speeds. The only significant difference in response between all models was for the retro-fit design; the increased displacement from adding the amidships bulbs and holding the draught constant increased the added resistance. Powering and acceleration levels for all models in head seas will be verified in tow-tank tests at ITU.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".