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Record W2152835168 · doi:10.1109/vppc.2005.1554560

The Effects of Front and Rear Tires Characteristics on the Snaking Behavior of Articulated Steer Vehicles

2005· article· en· W2152835168 on OpenAlex
Nasser L. Azad, John McPhee, Amir Khajepour

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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMechanical Engineering and Vibrations Research
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSlip angleStiffnessTire balanceAutomotive engineeringFront (military)Structural engineeringEngineeringSlip (aerodynamics)Mechanical engineeringAerospace engineeringSteering wheel

Abstract

fetched live from OpenAlex

A virtual prototype of a real vehicle is used to study the effects of front and rear tires characteristics on the snaking mode of articulated steer vehicles. By using this prototype, the tire slip angles, forces and moments and articulation angle are simulated and reviewed. Then, the effects of some changes in the front and rear tires characteristics, more specifically, the cornering stiffness on the snaking mode are studied. Based on these studies, a decrease in the cornering stiffness of the rear tires can be used to reduce the snaking oscillations. The reduction in the cornering stiffness of the rear tires can be achieved by making some changes in the tire properties, such as use of the narrower tires.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.537
Threshold uncertainty score0.119

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.009
GPT teacher head0.225
Teacher spread0.216 · 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