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Record W4365151234 · doi:10.4271/2023-01-0919

The Influence of Traffic Wakes on the Aerodynamic Performance of Heavy Duty Vehicles

2023· article· en· W4365151234 on OpenAlex
Brian McAuliffe, Hali Barber, Faegheh Ghorbanishohrat

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSAE International Journal of Advances and Current Practices in Mobility · 2023
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Fluid Dynamics Research
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsWakeAerodynamicsWind tunnelCrosswindTrailerDragDrag coefficientFreestreamMarine engineeringTurbulenceAerospace engineeringMeteorologyEnvironmental scienceEngineeringStructural engineeringPhysicsReynolds number

Abstract

fetched live from OpenAlex

<div class="section abstract"><div class="htmlview paragraph">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.</div><div class="htmlview paragraph">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.</div></div>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.529
Threshold uncertainty score0.204

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.332
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it