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Record W7068158472

Nonlinear dynamics of railway wheelsets incorporating randomness / by Jing Yu.

2007· dissertation· en· W7068158472 on OpenAlexfundno aff

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2007
Typedissertation
Languageen
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRandomnessChaoticNonlinear systemParametric statisticsLyapunov exponentControl theory (sociology)Mathematical modelBifurcationVehicle dynamics
DOInot available

Abstract

fetched live from OpenAlex

"The thesis is to investigate the dynamic behavior of a single-axle railway wheelset and identify its chaotic behavior by means of time history, phase portrait, Lyapunov exponents, information dimension, bifurcation diagram and control strategy. The thesis has its analytical and computational components. For the analytical component, several mathematical models of a single-axle rail vehicle wheelset are presented in order to compare their features for similarities and differences. These models present different contact theories of creep force, and have different parametric values. In addition, Model III does not consider gravitational stiffnesses and gyroscopic couple. As a result, directly comparing simulation results of these models makes it difficult to interpret results and to draw conclusions. Therefore, these models need to be expanded so that issues can be isolated and investigated accordingly.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.858
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0020.003
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 head0.058
GPT teacher head0.398
Teacher spread0.340 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2007
Admission routes1
Has abstractyes

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