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Record W4409017790 · doi:10.4271/2025-01-8784

Design and Evaluation of a Conceptual Zero-Emission Truck Model Considering Aerodynamic Efficiency

2025· article· en· W4409017790 on OpenAlexaff
Faegheh Ghorbanishohrat, Brian McAuliffe, Harrison O'Reilly

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2025
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Fluid Dynamics Research
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsAerodynamicsTruckZero emissionZero (linguistics)Aerospace engineeringConceptual designComputer scienceAutomotive engineeringEnvironmental scienceEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

<div class="section abstract"><div class="htmlview paragraph">Emerging zero-emission-powertrain concepts are providing opportunities to re-shape heavy trucks for improved aerodynamic performance. To investigate the potential for energy savings through aerodynamic improvements, with a goal to inform operators and regulators of such benefits, a multi-phase project was initiated to design and evaluate aerodynamic improvements for Class 8 tractor-trailer combinations. While the focus was battery-electric and hydrogen-fuel-cell powered trucks, improvements for internal-combustion powered trucks were also examined. Previously-reported activities included a scaled-model wind-tunnel test that demonstrated the potential for up to 9% drag reduction from simple shape adaptations, with a follow-up CFD study providing guidance towards further optimization.</div><div class="htmlview paragraph">This paper presents wind-tunnel-test results using a high-fidelity 30%-scale model of a new aerodynamic tractor concept, with comparison to a conventional North American Class 8 tractor with a modern aerodynamic package and identical wheelbase. The study included testing of the new tractor concept along with individual parts such as air dams, under-body panels, grill/cooling-flow configurations, mirrors, wheel fairings, cab extenders, etc. The battery-electric variant of the new tractor provided a 16% drag reduction compared to the conventional truck model when using the same trailer configuration. When paired with a low-drag-trailer concept, the new tractor-trailer combination demonstrated up to 41% drag reduction compared to the conventional tractor with a standard box-van trailer. This configuration is shown to be nearly insensitive to crosswinds with a wind-averaged drag coefficient of 0.34. Examining additional cooling-flow configurations necessary for hydrogen-fuel-cell trucks showed up to 3% increase in drag associated with the extra cooling drag. Additionally, the new tractor-shaping concept applied to a conventional internal-combustion-powertrain arrangement generated 8% drag reduction compared to the conventional tractor.</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.

How this classification was reachedexpand

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.887
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.024
GPT teacher head0.284
Teacher spread0.260 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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