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Record W2348167537

Improvement of Laval nozzle calculation model and simulative verification in aero-engine performance calculation

2009· article· en· W2348167537 on OpenAlexaboutno aff
Zhou Ren-zhi

Bibliographic record

VenueJournal of Aerospace Power · 2009
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsnot available
Fundersnot available
KeywordsNozzleMach numberRocket engine nozzleThrustMechanicsEngineeringDischarge coefficientRotor (electric)OutflowStagnation pressureMechanical engineeringPhysics
DOInot available

Abstract

fetched live from OpenAlex

By analyzing typical operating regimes of Laval nozzle,a zero-dimensional pneumatic model was built to evaluate the influence of Laval nozzle on the performance of aero-engine.The Laval nozzle model was integrated into a whole aero-engine component-level model.Numerical simulations were performed to study transient performance of aero-engine when nozzle throat and outlet areas decreased during accelerating process from idle to middle state.Results show that low pressure rotor speed decreases during some specific regimes,along with the reduction of Laval nozzle area in accelerating process,which also exists in real aero-engine rig tests.Besides,after normal shock clinging to nozzle outlet section was pushed out,there was a mach number break from subsonic to supersonic in nozzle outlet section,however,both the outflow rate and thrust changed smoothly without any break at the accelerating curve.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.005
GPT teacher head0.215
Teacher spread0.210 · 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
GenreMethods

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

Citations2
Published2009
Admission routes1
Has abstractyes

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