Preliminary Investigation of Power Output of Two Typical Two-Turbine Tidal Current Systems
Bibliographic record
Abstract
The hydrodynamic interaction between a stand-alone tidal current turbine and the incoming flow through it affects the power output of the turbine. Similarly, the hydrodynamic interaction between two tidal current turbines is expected to affect the power output of the two turbines. In this situation, we called the two turbines a two-turbine system. Turbine designers, especially those former naval architects, who worked on a two-propeller system before, strongly hold that the two-turbine system is one of the more cost-efficient formats of extracting energy from tidal current. Consequently, the relationship between hydrodynamic interaction and the power output of the two-turbine system is receiving broad attention, although it has not been systematically studied. In this paper, the parameters of the design of a two-turbine system are identified and nondimensionalized and two typical system layouts are given: canard layout and tandem layout two-turbine systems. By using the recently developed numerical method for simulating unsteady flow and tidal current turbine, i.e., DVM-UBC, a new numerical model for predicting the power output of a two-turbine system is developed. The power outputs of two-turbine systems of these two typical layouts are analyzed. It is noted that the total power output of a two turbine system with optimal configuration can be 25% higher than that of two stand-alone turbines. Also, we find that the power output of a canard layout two-turbine system is higher than that of a tandem layout two-turbine system.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".