Best practice guidelines for tank testing of wave energy converters
Bibliographic record
Abstract
Experimental tank testing is a key aspect of wave energy conversion research. The performance of designs can be assessed in an accessible and controlled environment and at a fraction of the cost of sea trials. Wave energy converter (WEC) tank testing is complex and has its own specificities compared with model testing of ships and offshore structures. This largely reflects the fact that the main quantity of interest is wave energy: how much is available and how much is harvested by the model. This paper provides an extensive overview of the various aspects of WEC tank testing. These are divided into three categories: physical model, measurements, and wave generation. For each of them, current best practice guidelines are given.
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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 | 0.056 | 0.131 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.013 | 0.005 |
| Research integrity | 0.013 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 0.018 |
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".