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Record W2999910890 · doi:10.1115/1.4045918

Shimmy Characteristic Analysis for Steering System of Heavy Mining Dump Trucks

2020· article· en· W2999910890 on OpenAlex
Lulu Gao, Fei Ma, Chun Jin, Yanjun Huang, Zhipeng Feng

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

VenueJournal of vibration and acoustics · 2020
Typearticle
Languageen
FieldEngineering
TopicVehicle Dynamics and Control Systems
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSpeed wobbleTruckControl theory (sociology)Suspension (topology)VibrationRange (aeronautics)Hopf bifurcationVolume (thermodynamics)Automotive engineeringEngineeringNonlinear systemBifurcationMarine engineeringComputer scienceMathematicsPhysicsAerospace engineering

Abstract

fetched live from OpenAlex

Abstract Tire wear cost accounts for a large proportion of the total cost of heavy mining dump trucks (HMDTs), and the shimmy of the steering system aggravates the tire wear severely. This study proposes a model-based approach to avoid the shimmy of the steering system for such trucks without replacement or destruction of steering structure. First, a five degrees-of-freedom (DOF) shimmy dynamic model of the steering system is established considering the tire lateral dynamics and the nonlinearity of the hydro-pneumatic suspension (HPS). Second, the unstable parameter range of the dynamic model is obtained based on the Lyapunov’s first approximation theorem and Hopf bifurcation theory. The stability analysis results show that the steering system of heavy mining dump trucks is a self-excited vibration system because of the Hopf bifurcation in the unstable parameter range, and this unstable parameter range is greatly affected by the load and the initial pneumatic volume of hydro-pneumatic suspension. In addition, the accuracy of the dynamic is verified by a field test. Therefore, how the load and initial pneumatic volume affect the shimming is analyzed numerically. In other words, how to match the load and initial pneumatic volume is uncovered to avoid the shimmy. For instance, it shows that the shimmy at full load can be avoided at the speed of 30 km/h by charging the initial pneumatic volume of hydro-pneumatic suspension to 14.5 l.

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: none
Teacher disagreement score0.578
Threshold uncertainty score0.276

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 head0.010
GPT teacher head0.196
Teacher spread0.186 · 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