Wind Tunnel Test of Drafting at Endurance Run Velocity
Bibliographic record
Abstract
The aim of this study is to investigate and quantify the aerodynamics advantage, the physiological and performance advantage produced by pacemaker drafting in the case of long endurance running. The experimental tests have been carried out in a wind tunnel, at submaximal effort two runners done a treadmill run test of five minutes at 4.72 m/s with the same air velocity. By comparison of physiological parameters with and without drafting, the decreasing due to the pacemaker effect was obtained. A CFD simulation is used to analyze aerodynamic effects in terms of drag and drag coefficient with and without drafting at a wind speed of 4.72 m/s. Results indicates that compared to the baseline (running alone), the drafting position show a decrease in drag (-9.73%) and drag coefficient (-9.73%). This reduction in aerodynamic drag also leads to the reduction of the following physiological parameters, as detected by the experimental tests: oxygen consumption (-5.46%), metabolic power (-5.48%), energy cost (-7.31%), produced carbon dioxide (-7.40%), minute ventilation (-5.44%), HR (-0.60%), blood lactate concentration (-16.66%), RPE (-13.89%). Results demonstrate that drafting has a significant effect on aerodynamics parameters, but also on physiological and performance variables in highly and medium trained athletes.
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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".