Transient torque and power number of a fluid agitator for direct wind thermal energy conversion
Bibliographic record
Abstract
The present research explores a novel method for direct conversion of wind power to heat through fluid agitation for decentralized heating in remote or off-grid areas. An experimental setup was designed to study the torque and power characteristics of the fluid agitator. Two different impellers were tested under various dynamic conditions, including acceleration, deceleration, and sinusoidal speed variations. The results demonstrate that the agitator’s power number under transient conditions differs significantly from its steady-state values. This finding is crucial for properly matching the agitator to a wind turbine, ensuring efficient energy transfer. Moreover, it was found that the transient power number is more sensitive to acceleration rates than to deceleration. When operated under a sinusoidal speed profile, both the frequency and amplitude of the speed variation strongly influence system performance. Temperature measurements of the working fluid confirmed that applying a sinusoidal speed profile leads to higher heat generation compared to constant-speed operation. These findings provide valuable insights for designing practical wind-powered thermal systems.
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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) | 0.001 | 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".