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Record W2072533192 · doi:10.2298/tsci110911043e

Exergetic analysis of an aircraft turbojet engine with an afterburner

2013· article· en· W2072533192 on OpenAlexaff
M.A. Ehyaei, A. Anjiridezfuli, Marc A. Rosen

Bibliographic record

VenueThermal Science · 2013
Typearticle
Languageen
FieldEngineering
TopicHeat transfer and supercritical fluids
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsTurbojetExergyNozzleGas compressorEnvironmental scienceBrayton cycleTurbineAutomotive engineeringCombustion chamberMarine engineeringJet engineAerospace engineeringCombustionEngineeringWaste managementChemistry

Abstract

fetched live from OpenAlex

An exergy analysis is reported of a J85-GE-21 turbojet engine and its components for two altitudes: sea level and 11,000 meters. The turbojet engine with afterburning operates on the Brayton cycle and includes six main parts: diffuser, compressor, combustion chamber, turbine, afterburner and nozzle. Aircraft data are utilized in the analysis with simulation data. The highest component exergy efficiency at sea level is observed to be for the compressor, at 96.7%, followed by the nozzle and turbine with exergy efficiencies of 93.7 and 92.3%, respectively. At both considered heights, reducing of engine intake air speed leads to a reduction in the exergy efficiencies of all engine components and overall engine. The exergy efficiency of the turbojet engine is found to decrease by 0.45% for every 1?C increase in inlet air temperature.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.210
Teacher spread0.204 · 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 designSimulation or modeling
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

Citations53
Published2013
Admission routes1
Has abstractyes

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