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Record W2557575805 · doi:10.2174/1874155x01610010183

Identification of the Mechanical Properties of Tires for Wheelchair Simulation

2016· article· en· W2557575805 on OpenAlex
A. Doria, Luca Taraborrelli, Tarek Jomaa, Tom Peijs, Mario Potter, Sunjoo Advani, Larry Russell Crichlow

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

VenueThe Open Mechanical Engineering Journal · 2016
Typearticle
Languageen
FieldEngineering
TopicVehicle Dynamics and Control Systems
Canadian institutionsToronto Rehabilitation Institute
Fundersnot available
KeywordsWheelchairEngineeringExperimental dataAutomotive engineeringSimulationMechanical engineeringComputer scienceMathematics

Abstract

fetched live from OpenAlex

The development of high performance wheelchairs and wheelchair simulators requires dynamic models taking into account the properties of tires. In this paper the properties of two wheelchair tires are measured by means of a rotating disc testing machine and are compared with the properties of bicycle tires, which have similar dimensions and structure. Tests are carried out considering variations in speed, inflation pressure and load. The possibility of fitting experimental results with the Magic Formula, the Dugoff formula and a linear model is discussed. A dynamic model of a wheelchair is developed, which includes a linear tire model derived from experimental results. Steady turning and slalom manoeuvres are simulated. Numerical results show the effect of tire properties on the handling characteristics of the wheelchair.

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)0.001
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: none
Teacher disagreement score0.741
Threshold uncertainty score0.190

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.016
GPT teacher head0.220
Teacher spread0.204 · 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