Hydrodynamic Analysis and Optimization of a Hinged Type Wave Energy Converter
Bibliographic record
Abstract
SeaWEED (Sea Wave Energy Extraction Device) is a multi-body floating wave energy converter (WEC) with hinged joints developed by Grey Island Energy Inc. (GIE) in Canada. Initial conceptual studies have been carried out to evaluate the performance of the first generation device by testing a 1:16 scale model in a wave basin. The experimental results were compared with the numerical solutions. Based on the experimental studies, improvements were made and a second generation model with a new geometry of the hull and a new connection structure was developed. This paper is mainly focused on the numerical analysis and optimization of the second generation SeaWEED model. In the numerical studies, the hydraulic power take-off (PTO) system was simulated by a linear spring damper system coupled with the motion of the hinged bodies. The vertical hinge motion was computed at a series of wave periods using WAMIT. Optimization was focused on the PTO damping and the geometrical parameters in terms of the draft and the length of the truss structure between hinged bodies by using the response surface method. An optimal combination of length, draft and PTO damping was recommended for an intended operation location.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".