comparison of platform and sea-bed mounted flow measurement instrumentation for SME PLAT-I
Bibliographic record
Abstract
Tidal resource assessment for the characterisation of turbine performance or Annual Energy Prediction currently uses the method of bins as recommended by international standards. An alternative method is proposed in this paper and applied to the Sustainable Marine Energy PLAT-I deployment in Connel Sound, Scotland. This method may be suitable for tidal turbines which operate from the surface. Three instrumentation types are used in this work, a bed-mounted Acoustic Doppler Profiler (ADP), and platform-mounted Acoustic Doppler Velocimeter (ADV) and Electromagnetic Current Meter (ECM). By comparing the resource characteristics from these three sources, a comparison of their velocity magnitudes and turbulence characteristics is made, demonstrating the difference between methodologies. It was found that the ADP evaluated using the method of bins produced a more conservative velocity distribution, in comparison to the ADV and ECM. Consequently, a representative AEP showed a difference of 3.8kWh (50% of ADP total) for the month of data collected. When comparing the Turbulence Intensity between devices, the ADP and ECM had similar metrics whilst the ADV had up to 14% higher values. The significance of these differences requires further work comparing them to the SME PLAT-I turbines power output to ascertain which best represents the onset flow experienced by the turbine and if there is a correlation between power performance and turbulence intensity.
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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".