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Record W2285624279 · doi:10.4271/2000-01-3478

Directional Response and Yaw Stability of Articulated Log Hauling Trucks

2000· article· en· W2285624279 on OpenAlexaff
Ebrahim Esmailzadeh, B. Tabarrok

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2000
Typearticle
Languageen
FieldEngineering
TopicVehicle Dynamics and Control Systems
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsTruckAutomotive engineeringStability (learning theory)Articulated vehicleComputer scienceControl theory (sociology)EngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

<div class="htmlview paragraph">The planar mathematical model for various design configurations of articulated log-hauling truck in the form of a tandem axle tractor and two separate semi-trailer units, commonly known as super B train truck, is developed. A thorough kinematics and dynamic analyses of the log-hauling combination trucks, incorporating up to three axles to be steerable for the tractor, are carried out and the governing differential equations for the lateral and yaw planar motions are derived. Using a computer simulation model, the directional performance and the lateral and yaw and stability of this articulated truck is fully investigated through transient and harmonic response analyses. Finally, a parameter sensitivity analysis was carried out for different variables involved in the simulation model, to study the sensitivity of the steady-state response to various parameters.</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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.988
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.204
Teacher spread0.198 · 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 designBench or experimental
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

Citations3
Published2000
Admission routes1
Has abstractyes

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