Streamlining the time trial apparel of cyclists: The Nike swift spin project
Bibliographic record
Abstract
This paper documents the development of aerodynamic apparel for the Tour de France individual time trial (TT), the Olympic TT, and track cycling races. A wind tunnel and metric balance were used to measure the drag force (Fd) and wind tunnel air velocity on cylinders, limb models, and live cyclists clad in samples or suits sewn with one or more of 200 stretch fabrics. A concurrent measurement of model dimensions and frontal areas provided the non‐dimensional drag coefficient (Cd) and Reynolds Numbers (Re) that characterized the ability of the various fabrics and suits to reduce frictional drag and induce a drag crisis (DC) or premature flow transition. DC defines a critical air velocity over the body segments at which the airflow transitions from laminar to turbulent, yielding a smaller wake behind the body segment and a corresponding decrease in Fd. A number of fabrics triggered DC on cylinders and limb segments, reducing cylinder and limb Cd by over 40 per cent. Several methods of lowering the Fd of cycling apparel proved effective, including custom fitting, aligning seams with the airflow, and matching fabric textures to body segments. Repeated drag measurements of the same cycling suit provided a mean drag of approximately 3200 g with a standard error of ± 29g. The final 2005 individual TT suit design, worn by a pedaling cyclist, had a measured drag at 53kph, which was 125 g less than typical 2001 TT cycling suits worn by competitors (Fd reduction 5 3.9 per cent). A mathematical model predicts that a drag difference of this magnitude would provide a time saving of approximately 44 s in a 55‐km Tour de France TT. In 2002–2005 and 2007, the production version of the ‘Swift Spin’ TT suit was worn by the winner of the Tour de France; by the women's hour record holder and by road; TT and track cyclists who set four world records, six Olympic records, and won seven medals in individual cycling races at the 2004 Athens Olympics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".