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Record W2070346605 · doi:10.2514/2.6075

Thermodynamics of Airbreathing Pulse-Detonation Engines

2002· article· en· W2070346605 on OpenAlexaff
J. A. C. KentŽfield

Bibliographic record

VenueJournal of Propulsion and Power · 2002
Typearticle
Languageen
FieldEngineering
TopicCombustion and Detonation Processes
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsDetonationCombustionPropulsionMechanicsThermodynamic cycleShock waveShock tubePhysicsThermodynamicsChemistryExplosive material

Abstract

fetched live from OpenAlex

An analytical investigation was conducted of the idealized performance potential, from a thermodynamic cycle viewpoint, of airbreathing pulse-detonation engines (PDEs) primarily intended for air-vehicle propulsion. The investigation was restricted to the static operation of PDEs. The detonation-wave model used was of the classical Zel'dovich-von Neumann-Doering type, in which an initiating shock wave is followed by a Rayleigh-type combustion process in a duct, the detonation tube, of uniform cross-sectional area. The results of the analysis indicated that the idealized PDE performance was only slightly better than that of a simple, easily analyzed, constant-volume combustion, Lenoir-type surrogate cycle. The PDE also had the potential of being slightly more efficient, under idealized flight conditions, with induction ramming occurring, than the corresponding surrogate cycle. The corresponding surrogate cycle will advance thermodynamically, due to intake ramming, from a relatively inefficient Lenoir cycle to a more efficient Humphrey, or Atkinson, cycle.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.009
GPT teacher head0.207
Teacher spread0.198 · 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

Citations57
Published2002
Admission routes1
Has abstractyes

Explore more

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