Further CFD Studies for Detailed Tires using Aerodynamics Simulation with Rolling Road Conditions
Why this work is in the frame
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Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">In an environment of tougher engineering constraints to deliver tomorrow's aerodynamic vehicles, evaluation of aerodynamics early in the design process using digital prototypes and simulation tools has become more crucial for meeting cost and performance targets. Engineering needs have increased the demands on simulation software to provide robust solutions under a range of operating conditions and with detailed geometry representation. In this paper the application of simulation tools to wheel design in on-road operating conditions is explored.</div> <div class="htmlview paragraph">Typically, wheel and wheel cover design is investigated using physical tests very late in the development process, and requires costly testing of many sets of wheels in an on-road testing environment (either coast-down testing or a moving-ground wind-tunnel). This paper is a follow-up to a study by the same authors, in which the aerodynamic drag performance of wheel designs was evaluated in a static ground wind-tunnel and simulation environment. In the present study, new experimental data using on-road coast-down tests is shown to verify the drag benefits of key wheel and wheel cover designs. The data is compared to a simulation study with commercial CFD software using an on-road configuration with moving ground and rotating tires. The simulation data is well-correlated to the experiment, and through analysis of the flow data, it provides insight into the mechanism of drag reduction. The study is successful in establishing simulation as a reliable means to evaluate wheel designs and the potential for drag savings early in the vehicle development process, with much less cost than physical tests.</div></div>
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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