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Record W2884528516 · doi:10.1080/00423114.2018.1494842

A study of polygonal wheel wear through a field test programme

2018· article· en· W2884528516 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

VenueVehicle System Dynamics · 2018
Typearticle
Languageen
FieldEngineering
TopicRailway Engineering and Dynamics
Canadian institutionsConcordia University
FundersFundamental Research Funds for the Central Universities
KeywordsAxleAccelerationEngineeringStructural engineeringAutomotive engineeringMagnitude (astronomy)Physics

Abstract

fetched live from OpenAlex

High magnitude impact loads caused by polygonal wear of the wheels have been associated with in-service failures of structural components of high-speed railways, although the mechanisms leading to wheels’ polygonalisation is not yet fully understood. In this study, a long-term field test programme is undertaken and the data are analysed to gain better understanding of the growth in polygonal wear, and its characteristics and correlation with the axle box acceleration. The field measurements on a high-speed railway involved monitoring of wheels profiles between successive re-profiling of the wheels so as to identify the rate of growth of wear in addition to the axle box acceleration. The data suggested rapid growth in wheel wear, which could be characterised by polygonal wear of nearly 18th and 19th harmonic order. It is further shown that the magnitude of axle box acceleration increased considerably with increasing wear magnitude of the wheel.

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 score0.593
Threshold uncertainty score0.913

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 head0.009
GPT teacher head0.213
Teacher spread0.203 · 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