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Record W1973562926 · doi:10.1299/jmtl.3.206

Ride Comfort Improvements in a High-Speed Train with Active Secondary Suspension

2010· article· en· W1973562926 on OpenAlexaff
Anneli Orvnäs, Sebastian Stichel, Rickard Persson

Bibliographic record

VenueJournal of Mechanical Systems for Transportation and Logistics · 2010
Typearticle
Languageen
FieldEngineering
TopicRailway Engineering and Dynamics
Canadian institutionsBombardier (Canada)
Fundersnot available
KeywordsAutomotive engineeringSuspension (topology)Active suspensionTrack (disk drive)EngineeringSimulationMechanical engineeringElectrical engineeringActuator

Abstract

fetched live from OpenAlex

A combination of increased vehicle speeds and non-improved railway tracks may have a negative impact on passenger comfort. Active technology can replace the conventional passive solution of the secondary suspension of a rail vehicle in order to maintain good passenger comfort even when vehicle speed is increased and track conditions are inferior. This paper focuses on the benefits of using a so-called Hold-Off-Device (HOD) function in the lateral secondary suspension. On-track tests have been performed with the active secondary suspension concept implemented in a two-car Regina train during the summers of 2007 and 2008. The evaluated measurement results have been very satisfactory and the device will be implemented in long-term tests in service operation. These tests were carried out in the beginning of 2009.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.008
GPT teacher head0.211
Teacher spread0.202 · 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 designBench or experimental
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

Citations31
Published2010
Admission routes1
Has abstractyes

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