Track-test Evaluation of Aerodynamic Drag Reducing Measures for Class 8 Tractor-Trailers
Bibliographic record
Abstract
Air resistance, after gross vehicle weight, is the largest factor responsible for vehicle energy loss and has an important influence on fuel consumption. The magnitude of aerodynamic drag is affected by the vehicle's shape, frontal area, and travel speed. This study aimed to evaluate several aerodynamic drag reduction measures applicable to class 8 tractor-trailer combinations. The tested aerodynamic devices included trailer aft body rear deflectors (boat tails), trailer skirts, gap deflectors, fuel tank fairings and truck rear-axle fenders. It also assessed the aerodynamic influence of opened doors on an empty wood chip van trailer on the fuel consumption of the tractor-trailer combination. The tests were conducted according to SAE J1321 Joint TMC/SAE Fuel Consumption Test Procedure - Type II. Testing took place on a closed test track at a fixed speed of 100 km/h, in order to eliminate the inconveniences of on-highway tests, such as the influences of traffic and the variation in driver response. The high-speed test track was a high-banked parabolic oval with a length of 6.4 km. The tests indicated that the influence on fuel consumption was less than 2% for fuel tank fairings, truck rear-axle fender, tractor-trailer gap deflector, and the opened doors on the empty chip van trailer. The test results showed up to 5% improvement in fuel consumption for the test vehicles equipped with boat tail devices, and up to 7% for the vehicles equipped with trailer skirts. For some of the tested devices, full-scale wind tunnel test results were available and comparisons were made between these results and track test results. Conservative estimations for Canadian transportation conditions show that some aerodynamic devices could bring annual greenhouse gas emissions reductions of four tonnes per vehicle. Combinations of different devices, such as trailer skirts and boat tails, would certainly increase the benefits. With payback periods ranging from 1.4 to 2.7 years, the majority of the tested aerodynamic devices represent viable measures to increase fuel efficiency and to reduce greenhouse gas emissions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 0.001 |
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".