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Record W4386004915 · doi:10.1504/ijhvs.2023.10058546

Lateral stability control of truck and centre-axle-trailer combinations under crosswind disturbances

2023· article· en· W4386004915 on OpenAlex

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

VenueInternational Journal of Heavy Vehicle Systems · 2023
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Fluid Dynamics Research
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsCrosswindTrailerTruckAxleArticulated vehicleEngineeringAutomotive engineeringElectronic stability controlAutomobile handlingStructural engineeringAerospace engineering

Abstract

fetched live from OpenAlex

Crosswind disturbances may cause rollover or lane departure of truck and centre-axle-trailer (TCAT) combinations. To increase the safety of TCATs, a crosswind model is introduced and a 3 degrees of freedom (DOF) yaw-plane model is generated for developing a lateral stability control technique. Numerical simulation is conducted to examine the resulting dynamic responses under varying crosswind disturbances. To verify the 3-DOF model, the simulation results under a single lane-change (SLC) manoeuvre under a crosswind disturbance are compared against those based on the corresponding nonlinear TruckSim model. To effectively reject crosswind disturbances, a braking torque distribution strategy is proposed, by which the direct yaw moment control (DYC) is implemented using a fuzzy-PID algorithm. The simulation shows that the directional performance of TCAT is improved when the DYC activates under crosswind disturbances. The proposed active safety technique can reduce the risk of crosswind-induced instabilities of TCATs.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.327
Threshold uncertainty score0.345

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 head0.014
GPT teacher head0.261
Teacher spread0.247 · 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