Near-to-Far Wake Characteristics of Road Vehicles Part 3: Influence of Multi-Vehicle Interactions
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">Conventional assessments of the aerodynamic performance of ground vehicles have, to date, been considered in the context of a vehicle that encounters a uniform wind field in the absence of surrounding traffic. Recent vehicle-platooning studies have revealed measurable fuel savings when following other vehicles at inter-vehicle distances experienced in every-day traffic. These energy savings have been attributed in large part to the air-wakes of the leading vehicles. This set of three papers documents a study to examine the moderate-to-far regions of ground-vehicle wakes (one to ten vehicle lengths), in the context of their potential influence on other vehicles.</div><div class="htmlview paragraph">Part Three of this three-part paper documents the wake characteristics for multi-vehicle scenarios of two or three vehicles, in single-lane or two-lane arrangements. A set of high-fidelity numerical simulations, based on a Lattice-Boltzmann approach, and a series of scaled-model wind-tunnel measurements are presented to examine some multi-vehicle scenarios with four types of vehicle shapes: a sedan, an SUV, a medium-duty vehicle, and a heavy-duty vehicle. The wake-merging process of a two-lane longitudinally-staggered sedan-and-SUV configuration is examined in detail with and without cross winds. Experimental-results are presented only for the SUV, medium- and heavy-duty vehicle shapes due to challenges described in Part One with respect to the sedan-model and the stationary-floor arrangement.</div><div class="htmlview paragraph">Complex wake patterns emerge under multi-lane scenarios, particularly under cross-wind conditions, but the results suggest a level of predictability in the aggregate wake properties. Only for the cases with close lateral proximity (side-by-side configurations) do the wake patterns change substantially such that the characteristics of the individual wakes are not perceptible. Additionally, the merged wakes in cross winds are shown to potentially influence vehicles up to three or four lane widths away. The results suggest that superposition of moderate-to-far-wake profiles may be possible to generate on-road wind conditions associated with a range of traffic scenarios.</div></div>
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".