Effects of rear spoilers on ground vehicle aerodynamic drag
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose – The purpose of this paper is to examine the aerodynamic effects of rear spoiler geometry on a sports car. Today, due to economical, safety and even environmental concerns, vehicle aerodynamics play a much more significant role in design considerations and rear spoilers play a major role in this area. Design/methodology/approach – A 2-D vehicle geometry of a race car is created and solved using the computational fluid dynamics (CFD) solver FLUENT version 6.3. The aerodynamic effects are analyzed under various vehicle speeds with and without a rear spoiler. The main results are compared to a wind tunnel experiment conducted with 1/18 replica of a Nascar. Findings – By the CFD analysis, the drag coefficient without the spoiler is calculated to be 0.31. When the spoiler is added to the geometry, the drag coefficient increases to 0.36. The computational results with the spoiler are compared with the experimental data, and a good agreement is obtained within a 5.8 percent error band. The uncertainty associated with the experimental results of the drag coefficient is calculated to be 6.1 percent for the wind tunnel testing. The sources of discrepancies between the experimental and numerical results are identified and potential improvements on the model and experiments are provided in the paper. Furthermore, in the CFD model, it is found that the addition of the spoiler caused a decrease in the lift coefficient from 0.26 to 0.05. Originality/value – This paper examines the effects of rear spoiler geometry on vehicle aerodynamic drag by comparing the CFD analysis with wind tunnel experimentation and conducting an uncertainty analysis to assess the reliability of the obtained results.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it