The Influence of Traffic Wakes on the Aerodynamic Performance of Heavy Duty Vehicles
Bibliographic record
Abstract
Road vehicles have been shown to experience measurable changes in aerodynamic performance when travelling in everyday safe-distance driving conditions, with a major contributor being the lower effective wind speed associated with the wakes from forward vehicles. Using a novel traffic-wake-generator system, a comprehensive test program was undertaken to examine the influence of traffic wakes on the aerodynamic performance of heavy-duty vehicles (HDVs). The experiments were conducted in a large wind tunnel with four primary variants of a high-fidelity 30%-scale tractor-trailer model. Three high-roof-tractor models (conventional North-American sleeper-cab and day-cab, and a zero-emissions-cab style) paired with a standard dry-van trailer were tested, along with a low-roof day-cab tractor paired with a flat-bed trailer. Amongst these, trailer variants provided a total of 10 HDV configurations that were tested in uniform turbulent flow over a range of freestream yaw angles between ±15°, and with wake effects over a range of yaw angles between -2° and +11°. Up to 53 specific wake-flow conditions were applied to each HDV configuration. Wind-load and surface-pressure measurements were acquired and provide indicators of the manner in which the aerodynamic performance of the HDV models are influenced by traffic wakes. Drag-coefficient reductions up to 17% for individual drag-coefficient values and up to 9% for wind-averaged values were observed. Wakes from adjacent-lane vehicles were observed to have comparable, or sometimes greater, influence to those from safe-distance same-lane vehicles. The wakes influence primarily the forward-facing surfaces of the HDV, resulting in performance changes associated with tractor modifications being affected more than for trailer modifications. These results represent the first comprehensive study of traffic-wake effects on HDVs at safe inter-vehicle distances in highway-driving conditions, and highlight potential differences in real-world aerodynamic performance relative to the standard wind-averaged uniform-flow metrics used for fuel/energy-use and emissions predictions.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 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".