Evaluation of the Aerodynamics of Drag Reduction Technologies for Light-duty Vehicles: a Comprehensive Wind Tunnel Study
Why this work is in the frame
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Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">In a campaign to quantify the aerodynamic drag changes associated with drag reduction technologies recently introduced for light-duty vehicles, a 3-year, 24-vehicle study was commissioned by Transport Canada. The intent was to evaluate the level of drag reduction associated with each technology as a function of vehicle size class.</div><div class="htmlview paragraph">Drag reduction technologies were evaluated through direct measurements of their aerodynamic performance on full-scale vehicles in the National Research Council Canada (NRC) 9 m Wind Tunnel, which is equipped with a the Ground Effect Simulation System (GESS) composed of a moving belt, wheel rollers and a boundary layer suction system.</div><div class="htmlview paragraph">A total of 24 vehicles equipped with drag reduction technologies were evaluated over three wind tunnel entries, beginning in early 2014 to summer 2015. Testing included 12 sedans, 8 sport utility vehicles, 2 minivans and 2 pick-up trucks.</div><div class="htmlview paragraph">Two categories of drag reduction technologies were evaluated: i) those currently offered by the original equipment manufacturers (i.e. active grille shutters, partial underbody covers, bumper and wheel air dams); and, ii) emerging technologies that have market introduction potential, i.e., active ride height control, actively deployable bumper air dams and full under-body covers.</div><div class="htmlview paragraph">The main findings of the experiments are presented in this paper by categories of vehicles and drag reduction technologies. A discussion on the use of wind averaged drag to evaluate the full impact of the technologies on fuel consumption is also presented.</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 | 0.002 | 0.000 |
| 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 | 0.001 | 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