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Record W2748486425 · doi:10.1115/gt2017-64905

Assessment of Biofuels/Jet A-1 Blends to Meet Cold Start and Altitude Relight Requirements

2017· article· en· W2748486425 on OpenAlexafffund
Joël Jean, Alain Fossi, Alain deChamplain, Bernard Paquet

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsUniversité Laval
FundersFonds Québécois de la Recherche sur la Nature et les TechnologiesPratt and Whitney Canada
KeywordsCombustorIgnition systemEnvironmental scienceNuclear engineeringCombustionJet (fluid)Altitude (triangle)Jet fuelMaterials scienceAerospace engineeringEngineeringChemistry

Abstract

fetched live from OpenAlex

The certification of new fuels for aircraft applications requires preliminary extensive investigations for the most critical combustion phases. Especially, cold start and altitude relight of an aircraft gas turbine and thus its operating envelope could potentially be affected by the use of new fuels. To assess such effects, a test rig is designed using two different air-assist pressure atomizers. The ignition envelopes for seven different blends with a minimum of 50% Jet A-1 are compared to that of pure Jet A-1. Variation in combustor aerodynamics is accounted for by considering various pressure drops across the combustion chamber, and the ignition envelope is retrieved by finding the minimum and maximum fuel-air ratios leading to a successful ignition event. Effects of fuel physical properties, pressure and temperature which are critical factors for a successful ignition event are also investigated. To simulate cold start and altitude relight, a heat exchanger is used to cool air and fuel, while a bleed valve mounted between the combustor and a steam ejector is used to regulate the operating pressure. Globally, cold start for temperatures ranging from 10°C to −40°C, and the altitude relight for operating altitudes ranging from 4 572 m to 10 668 m, show that the lean limit for the seven blends of fuels are in some cases as good as, and for the other cases better than the pure Jet A-1. Some discrepancies are noted for altitude relight at 9 161 m and 10 688 m, for some biofuels with a minimum of 50% Jet A-1, suggesting a need of real engine testing before final approval. Apart from these isolate cases, almost all the biofuel blends with a minimum of 50% Jet A-1 are truly “drop-in” fuels and should qualify for aviation use since they do not present any negative impact on the typical engine components used in the test program. Furthermore, ASTM D1655 requirements are also achieved for all test conditions. Biofuel blends with less than 50% Jet A-1 are found to always be better than the biofuel blends with minimum of 50% Jet A-1 and, it is recommended to modify ASTM D1655 to include them as acceptable “drop-in” 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 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 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 score0.316
Threshold uncertainty score0.501

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)0.0000.000

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 head0.028
GPT teacher head0.323
Teacher spread0.295 · 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 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

Citations7
Published2017
Admission routes2
Has abstractyes

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