Assimilating a Time-Domain Representation of a Wave Energy Converter Into a Spectral Wave Model
Why this work is in the frame
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Bibliographic record
Abstract
To accommodate future power demands, wave energy converters (WECs) will be deployed in arrays, but largely unanswered questions of the annual energy production and environmental impact of such installations present regulatory dilemmas. In recent years, Sandia National Laboratories (SNL) has developed a modified version of the Simulating Waves Nearshore (SWAN) wave model to simulate WEC energy extraction in a propagating wave field. The SNL source code modifications to SWAN have facilitated a way to characterize the frequency dependent power absorption of a device in a spectral model using standard WEC parameterizations. The work presented in this paper seeks to build on source code modifications previously made by SNL. A new WEC meta-model, alters the incident wave spectrum based on power extracted from the sea and dissipated by hydrodynamic losses experienced at the WEC. These losses are calculated in an external six degree of freedom (DOF) time domain WEC simulation. The two WEC models were compared in terms of significant wave height reduction in the WEC’s lee and annual power production. The new model reduced the estimated distance required for the waves to recover 95% of the incident wave height by 50% for the same sea state. A 4.5% difference in annual power production was observed for a WEC operating in the lee of another device when deployed off the west coast of Canada.
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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 it