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Record W2565811154 · doi:10.1515/tjj-2015-0052

Numerical Study of the Propulsive Performance of the Hollow Rotating Detonation Engine with a Laval Nozzle

2015· article· en· W2565811154 on OpenAlexaboutno aff
Songbai Yao, Xinmeng Tang, Jianping Wang

Bibliographic record

VenueInternational Journal of Turbo and Jet Engines · 2015
Typearticle
Languageen
FieldEngineering
TopicCombustion and Detonation Processes
Canadian institutionsnot available
Fundersnot available
KeywordsNozzleDetonationThrustRocket engine nozzleSpecific impulseMechanicsPropulsive efficiencyImpulse (physics)Mass flow rateAerospace engineeringMaterials scienceMechanical engineeringPhysicsEngineeringChemistryClassical mechanicsExplosive material

Abstract

fetched live from OpenAlex

Abstract The aim of the present paper is to investigate the propulsive performance of the hollow rotating detonation engine (RDE) with a Laval nozzle. Three-dimensional simulations are carried out with a one-step Arrhenius chemistry model. The Laval nozzle is found to improve the propulsive performance of hollow RDE in all respects. The thrust and fuel-based specific impulse are increased up to 12.60 kN and 7484.40 s, respectively, from 6.46 kN and 6720.48 s. Meanwhile, the total mass flow rate increases from 3.63 kg/s to 6.68 kg/s. Overall, the Laval nozzle significantly improves the propulsive performance of the hollow RDE and makes it a promising model among detonation engines.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.251
Threshold uncertainty score0.156

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 head0.010
GPT teacher head0.224
Teacher spread0.214 · 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 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

Citations16
Published2015
Admission routes1
Has abstractyes

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