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Record W1992262557 · doi:10.1115/detc2007-35823

Effects of the Load Distribution Patterns on the Longitudinal Freight Train Dynamics

2007· article· en· W1992262557 on OpenAlex
Masoud Ansari, Davood Younesian, Ebrahim Esmailzadeh

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

VenueVolume 3: 19th International Conference on Design Theory and Methodology; 1st International Conference on Micro- and Nanosystems; and 9th International Conference on Advanced Vehicle Tire Technologies, Parts A and B · 2007
Typearticle
Languageen
FieldEngineering
TopicRailway Engineering and Dynamics
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsTrainParametric statisticsPosition (finance)Nonlinear systemFreight trainsRail freight transportSimulationComputer scienceEngineeringStructural engineeringAutomotive engineeringMathematics

Abstract

fetched live from OpenAlex

A comprehensive parametric study is carried out on the longitudinal dynamics of a freight train having different loading patterns. A nonlinear time domain model, with one locomotive and nine wagons, is considered. In another simulation the train model has two locomotives and eight wagons, and in both models, every two cars are connected to each other through an automatic coupler. The effects of different load distribution patterns on the coupler forces for the cases of ascending, descending, constant, ascending-descending and descending-ascending are investigated through a parametric sensitivity study. In order to investigate how an empty wagon and its position in a train-consist model may affect the overall longitudinal dynamic behavior of freight trains a second computer simulation model has been developed. Moreover, the best possible position for the second locomotive with the objective of reaching to the lower longitudinal forces, in the case that an additional locomotive is included will be discussed. Finally, an investigation is carried out to determine the kind of couplers with their relevant specifications that must be installed in different positions of a train-consist in order to improve the longitudinal train dynamic behavior.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.738
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.063
GPT teacher head0.293
Teacher spread0.229 · 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