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Record W1993851138 · doi:10.1115/gt2011-45132

Altitude Performance of a Turbojet With Alternate Fuels

2011· article· en· W1993851138 on OpenAlexafffundabout
Craig R. Davison, Wajid A. Chishty

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRocket and propulsion systems research
Canadian institutionsNational Research Council Canada
FundersNational Research Council Canada
KeywordsJet fuelKeroseneTurbojetEnvironmental scienceAviation fuelWork (physics)Diesel fuelAutomotive engineeringAerospace engineeringEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

To enhance energy security and reduce the environmental impact of aviation, alternate fuels derived from various non-petroleum based sources are being developed. Currently alternate fuels are produced to match the properties of existing jet fuels allowing the new fuels to be used in current fleets concurrently with traditional jet fuel. The alternate fuels must, therefore, perform as well as the traditional fuels through the entire operating envelope. This paper provides the results of performance testing in an altitude chamber up to 11,300 m (35,000 feet) with a simulated forward speed up to Mach 0.75. The test engine was an instrumented 1.15 kN thrust turbojet burning conventional Jet A-1 as a baseline; a semi-synthetic blend of camelina based hydro processed renewable jet and JP8; a blend of 50% Fischer-Tropsch synthetic paraffinic kerosene and 50% JP8; and a 100% Fischer-Tropsch synthetic paraffinic kerosene. Both steady state and transient performance are presented. The theoretical effect of the alternate fuels for a simple idealized Brayton cycle is also presented. The work was conducted as part of on-going efforts by departments within the Government of Canada to systematically assess alternative aviation fuels.

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 score0.006

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 head0.033
GPT teacher head0.226
Teacher spread0.192 · 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

Citations8
Published2011
Admission routes3
Has abstractyes

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