Assessment of hydrodynamic impacts throughout the Bay of Fundy and Gulf of Maine due to tidal energy extraction by tidal lagoons
Bibliographic record
Abstract
The Bay of Fundy is home to some of the world's largest tides and has long been identified as one of the world's premier locations for the installation of tidal power generating systems. This paper deals with the assessment of hydrodynamic impacts throughout the Bay of Fundy and Gulf of Maine due to power generation by tidal lagoons located in Minas Basin. The lagoon concept involves temporarily storing seawater behind an impoundment dike and generating power by gradually releasing the seawater through conventional low-head hydroelectric turbines. Tidal lagoons represent a relatively novel approach to tidal power generation, and are intended to achieve high efficiency while avoiding some of the environmental problems associated with tidal barrages. A detailed two-dimensional (depth-averaged) finite-element numerical model, based on the TELEMAC system, has been developed, calibrated against observed water levels and velocities, and applied to simulate tidal hydrodynamics throughout the Bay of Fundy and Gulf of Maine, both for existing conditions without a lagoon and for two scenarios with tidal lagoons operating in Minas Basin. A 12 km 2 offshore lagoon with 14 turbines generating ∼124 MW on average and a 24 km 2 coastal lagoon with 24 turbines generating ∼220 MW on average have been investigated. This paper provides a summary of the work that has been performed to date and presents results describing the local and far-field changes in water levels and tidal currents due to tidal lagoons operating in the upper Bay of Fundy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".