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Record W2062796339 · doi:10.1115/gt2011-45133

Emissions Assessment of Alternative Aviation Fuel at Simulated Altitudes

2011· article· en· W2062796339 on OpenAlex

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicAdvanced Aircraft Design and Technologies
Canadian institutionsCommunications Security EstablishmentEnvironment and Climate Change CanadaNational Research Council Canada
Fundersnot available
KeywordsJet fuelAviationEnvironmental scienceDiesel fuelAviation fuelBaseline (sea)Renewable energyAutomotive engineeringEngineeringWaste managementAerospace engineering

Abstract

fetched live from OpenAlex

To address the global fuel challenges of energy security, economic sustainability and climate change the stakeholders of aviation industry are actively pursuing the development and qualification of alternative ‘drop-in’ fuels. New standards will be required to regulate the use of these new fuels, which requires not only fuel specification and rig/engine and flight testing but also an emission life cycle impact assessment of these fuels. This paper reports on emission data measured at various simulated altitudes and engine speeds from a jet engine operated on conventional and alternative aviation fuels. The work was conducted as part of on-going efforts by departments within the Government of Canada to systematically assess regulated as well as non-regulated emissions from the use of alternative aviation fuels. The measurements were performed on an instrumented 1000 N-thrust turbojet engine using a baseline conventional Jet A-1 fuel and a semi-synthetic (50/50) blend with Camelina based Hydroprocessed Renewable Jet (JP8-HRJ8) fuel. Emission results reported here include carbon dioxide, carbon monoxide, nitrogen oxides and particulate matter measured at several simulated altitudes and power settings. In order to ensure that the assessments have a common baseline, relevant engine performance and operability data were also recorded.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score0.996

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.034
GPT teacher head0.290
Teacher spread0.256 · 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

Quick stats

Citations14
Published2011
Admission routes2
Has abstractyes

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