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Record W2371517996

Numerical study on the conjugate heat transfer of a laval nozzle under different expansion states

2014· article· en· W2371517996 on OpenAlexaboutno aff
Ru Liu

Bibliographic record

VenueJournal of Solid Rocket Technology · 2014
Typearticle
Languageen
FieldEngineering
TopicRadiative Heat Transfer Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNozzleHeat transferMechanicsTurbulenceConvective heat transferFinite volume methodMaterials scienceHeat fluxConvectionFlow (mathematics)ThermodynamicsInletPhysicsMechanical engineeringEngineering
DOInot available

Abstract

fetched live from OpenAlex

A conjugate heat transfer( CHT) code was developed to study the flow structure and heat transfer of a nozzle under different expansion states.Navier-Stokes equations were used to govern both fluid and solid regions,cell-center based finite volume method was adopted to solve the governing equations,and k-ω SST model was used for turbulence closure.The CHT process is realized by keeping the heat flux on the coupled surface to be consistent.The CHT code is validated by experimental data,then used to numerically investigate a nozzle under different expansion states.The simulated results show that the flow separation occurs in the nozzle under over-expanded state,and the convective heat transfer is enhanced in the separation region and the nozzle wall is cooled by the gas in the downstream region of the separation with a relatively low level.The local convective heat transfer increases with the nozzle inlet pressure.

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)0.001
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.013
GPT teacher head0.244
Teacher spread0.230 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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