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Record W4323257226 · doi:10.2507/ijsimm22-1-co5

A Performance Study on Structural Parameters of Centre-Axle-Trailer Combinations

2023· article· en· W4323257226 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 Simulation Modelling · 2023
Typearticle
Languageen
FieldEngineering
TopicVehicle Dynamics and Control Systems
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsAxleTrailerStructural engineeringAutomotive engineeringEngineering

Abstract

fetched live from OpenAlex

Compared with rigid-trucks, centre-axle-trailer (CAT) combinations significantly improve fuel economy and reduce greenhouse-gas emissions.However, with respect to rigid-trucks, CAT combinations exhibit lower lateral stability at high speeds, and display poorer path-following offtracking (PFOT) at low speeds.This study intends to address these problems.To this end, eigenvalue analysis and simulation were conducted to evaluate the directional performance of CAT combinations considering the variations of typical structure parameters.To coordinate the trace-off between the lateral stability in terms of rearward amplification (RWA) and PFOT of CAT combinations, a CAT design with a variable-length drawbar was proposed.The drawbar length may be altered under different operating conditions, e.g., low-speed curved-path negotiations and high-speed evasive manoeuvres.The proposed variable-length drawbar is feasible in design and cost-effective in implementation.The insightful results derived from this study provide useful guidelines for the design CAT combinations to improved directional performance.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.316

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 head0.028
GPT teacher head0.268
Teacher spread0.240 · 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