Power performance of vertical axis wind turbine in Martian atmosphere
Bibliographic record
Abstract
This research investigates both physics of fluids in Martian atmosphere over the vertical axis wind turbine (VAWT) and also examines the power performance of the turbine under different geometrical features. Computational fluid dynamics simulations of VAWTs are inherently challenging, as the blades in the downstream region are impacted by the wakes generated by the upstream blades. Furthermore, the distinct flow behavior caused by the low atmospheric density on Mars adds another layer of complexity, making this research both unique and technically demanding. The reduced atmospheric density on Mars leads to Reynolds numbers that differ substantially from those under terrestrial conditions, influencing boundary layer development and separation, and thereby altering the associated vorticity dynamics. Incorporating winglets into the blade design resulted in a maximum power coefficient (CP) of 0.2, demonstrating their effectiveness in significantly reducing tip vortex formation along the blade span. This CP value is consistent with the results reported by Kumar et al., who employed the double-multiple stream-tube method—which inherently neglects tip vortex effects—thereby supporting the validity of the current simulation approach. Results indicate that winglets are more effective than endplates, enabling greater power extraction from the turbine. Furthermore, the impact of dome placement—both with and without winglets—is investigated, and the results demonstrate that the maximum power performance of the VAWT increases significantly due to the accelerated flow over the dome.
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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 | 0.000 |
| 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) | 0.002 | 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".