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Record W1510265864 · doi:10.4271/2004-01-1575

Tire Cleat Impact and Force Transmission: Modeling Based on FTIRE and Correlation to Experimental Data

2004· article· en· W1510265864 on OpenAlexfundno aff
Hans R. Dorfi

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2004
Typearticle
Languageen
FieldEngineering
TopicVehicle Dynamics and Control Systems
Canadian institutionsnot available
FundersPhysicians' Services Incorporated Foundation
KeywordsCorrelationData modelingTransmission (telecommunications)ImpactComputer scienceMaterials scienceMechanical engineeringEngineeringMathematicsTelecommunications

Abstract

fetched live from OpenAlex

The force transmission from the road surface to the spindle due to road disturbances is a significant factor in ride comfort. In this study the force transmission of tires rolling over cleats is studied using both a new numerical tire model, FTIRE, and measured data. FTIRE is a time-integrated physics based tire model with a flexible belt. The predicted and measured tire force response due to cleat impact is determined at different rolling speeds, cleat shapes, tire constructions and loading parameters. Excellent correlation between model and experimental data is achieved for all test parameters. Several observations regarding the force transmission are made with respect to the aforementioned test parameters. These observations are also related to dynamic tire properties. It is observed that a “quiet speed” exists, at which the tire vertical response is significantly reduced. The reason for this “quiet speed” and its relationship to the test parameters is discussed

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.012
GPT teacher head0.247
Teacher spread0.234 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations13
Published2004
Admission routes1
Has abstractyes

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