Assessment of tidal current energy in the Minas Passage, Bay of Fundy
Bibliographic record
Abstract
The tidal power available for electricity generation from in-stream turbines placed in the Minas Passage of the Bay of Fundy is examined. A previously derived theory is adapted to model the effect of turbine drag on the flow through the Minas Passage and the tidal amplitude in the Minas Basin. The theoretical maximum power production over a tidal cycle is determined by the product of the amplitude of the forcing tide in the Bay of Fundy and the undisturbed volumetric flowrate through the Minas Passage. Although the extraction of the maximum power will reduce the flowrate through the Minas Passage and the tides in the Minas Basin by over 30 per cent, a significant portion of the maximum power can be extracted with little change in tidal amplitude as the initial power generation causes only an increase in the phase lag of the basin tides. Two-dimensional, finite-element, numerical simulations of the Bay of Fundy—Gulf of Maine system agree remarkably well with the theory. The simulations suggest that a maximum of 7 GW of power can be extracted by turbines. They also show that any power extraction in the Minas Passage pushes the Bay of Fundy—Gulf of Maine system closer to resonance with the forcing tides, resulting in increased tidal amplitudes throughout the Gulf of Maine. Although extracting the maximum power produces significant changes, 2.5 GW of power can be extracted with a maximum 5 per cent change in the tidal amplitude at any location. Finally, the simulations suggest that a single turbine fence across the Minas Passage can extract the same power as turbines throughout the passage but that partial turbine fences are less efficient.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".