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Record W2025036941 · doi:10.3141/2289-06

Dual-Mode and New Diesel Locomotive Developments

2012· article· en· W2025036941 on OpenAlexaff
J. Vitins

Bibliographic record

VenueTransportation Research Record Journal of the Transportation Research Board · 2012
Typearticle
Languageen
FieldEngineering
TopicRailway Systems and Energy Efficiency
Canadian institutionsBombardier (Canada)
Fundersnot available
KeywordsAutomotive engineeringEngineeringDiesel fuelTruckTraction motorCatenaryAuxiliary power unitDiesel enginePowertrainElectrical engineeringVoltageTorque

Abstract

fetched live from OpenAlex

The integration of electric and diesel traction into a single rail vehicle is technically challenging because of weight and space restrictions, particularly for AC catenary power. Through the combination of recent developments in power converter technology, diesel engine design, and mechanical lightweight structures, dual-mode locomotives are now feasible for railroad applications. Apart from the different modes of traction, such locomotives must also fulfill the latest vehicle standards in regard to safety, environmental impact, and interoperability. A key component is the DC link of the traction converter, which interfaces to electric and diesel power supply systems. In addition, batteries, supercaps, or both can be interfaced to this DC link. All electric power flow is bidirectional and thus permits many possibilities for energy savings and reductions in exhaust emissions. The performance of a dual-mode locomotive is greatly enhanced by the latest high-speed diesel engines developed for off-road and industrial applications. Not only do the engines provide high diesel power at low weight, but they also meet the new Tier 3 and upcoming Tier 4 exhaust emission standards. For maximum vehicle performance in both modes, the car body and truck must be lightweight. A monocoque car body and fabricated truck are the obvious solutions, as used on the dual-powered ALP-45DP and the European TRAXX AC3, which is an electric locomotive with a diesel engine for operation on nonelectrified sidings and terminals. The above technologies also lend themselves to new diesel–electric locomotives, by yielding a high vehicle performance at low axle loads, as required for passenger services at 125 mph.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.155
Threshold uncertainty score0.685

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.082
GPT teacher head0.351
Teacher spread0.269 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations4
Published2012
Admission routes1
Has abstractyes

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