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Record W2332691410 · doi:10.1149/1.3429017

Fuel Cells as Tactical Auxiliary Power in Military Vehicles

2010· article· en· W2332691410 on OpenAlexfundno aff
E. Andrukaitis

Bibliographic record

VenueECS Transactions · 2010
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsnot available
FundersNational Research Council CanadaMinistère de la Défense NationaleAstellas Pharma US
KeywordsAuxiliary power unitAutomotive engineeringBattery (electricity)Power (physics)Diesel fuelFuel cellsEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

An integration of a PEM fuel cell for on-board auxiliary power of a military vehicle was demonstrated. If fuel (hydrogen) storage methods are properly implemented, a fuel cell is potentially the lightest and most energy efficient electrical power source in this application as part of a hybrid power system. The need for mobile auxiliary power units (APUs) is widespread in the military where communications and reconnaissance systems are operational while the vehicle engine is not running. Current drawbacks with present battery systems are that they do not run as long as desired. Diesel generators give off undesirable, detectable emissions such as noise, heat, vibrations and particulate matter, making its operation around personnel problematic. A full scale integration of fuel cells into a military vehicle is challenging given the availability of space, but the design goal performances were achieved in this demonstration.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.283
Threshold uncertainty score0.998

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.003
GPT teacher head0.191
Teacher spread0.188 · 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.

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

Citations3
Published2010
Admission routes1
Has abstractyes

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