The Effects of Detailed Tire Geometry on Automobile Aerodynamics - a CFD Correlation Study in Static Conditions
Bibliographic record
Abstract
A correlation study was performed between static wind tunnel testing and computational fluid dynamics (CFD) for a small hatchback vehicle, with the intent of evaluating a variety of different wheel and tire designs for aerodynamic forces. This was the first step of a broader study to develop a tool for assessing wheel and tire designs with real world (rolling road) conditions. It was discovered that better correlation could be achieved when actual tire scan data was used versus traditional smooth (CAD) tire geometry. This paper details the process involved in achieving the best correlation of the CFD prediction with experimental results, and describes the steps taken to include the most accurate geometry possible, including photogrammetry scans of an actual tire that was tested, and the level of meshing detail utilized to capture the fluid effects of the tire detail. The effects of this scanned tire geometry were significant, and improved the results for drag, lift, and the cooling drag for the vehicle relative to experimental full scale testing.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".