Modeling of a Wind-Turbine-Powered Ground Vehicle
Bibliographic record
Abstract
View Video Presentation: https://doi.org/10.2514/6.2023-2094.vid A number of vehicles have been demonstrated in past years that are purely wind-powered and capable of propelling themselves upwind into an oncoming wind. A wind turbine mounted on the vehicle drives the wheels of the vehicle through a geartrain. To help understand the vehicle operation, this paper presents a dynamics model of such a vehicle, using a blade-element momentum theory model of the turbine. As a case study, we use the Blackbird vehicle which set an upwind speed record in 2012. The model is able to accurately predict the vehicle performance in upwind mode when compared to available experimental data. Once validated, the model is used to determine how the Blackbird could be refined to improve its performance. In particular, we find that a variable-ratio transmission could substantially improve the vehicle’s acceleration; and that using lower gear ratios would slightly improve its terminal velocity. A sensitivity analysis performed on the losses (rolling resistance, air drag and transmission efficiency) found that improvement in the transmission efficiency would lead to the greatest increase in terminal velocity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".