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Record W4311869331 · doi:10.2514/1.t6595

Conjugate Heat Transfer Simulations of a Nozzle Flow over a Film-Cooled Plate

2022· article· en· W4311869331 on OpenAlexaff
Krishna Zore, Cristhian Aliaga, Shoaib Shah, John Stokes, Laith Zori, B. P. Makarov

Bibliographic record

VenueJournal of Thermophysics and Heat Transfer · 2022
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsAnsys (Canada)Avensys (Canada)
Fundersnot available
KeywordsNozzleHeat transferMechanicsPlenum spaceMaterials scienceTurbulenceComputational fluid dynamicsAerodynamicsPolygon meshFluentReynolds-averaged Navier–Stokes equationsMechanical engineeringPhysicsThermodynamicsComputer scienceEngineering

Abstract

fetched live from OpenAlex

This paper presents Ansys Fluent results for a rectangular exhaust nozzle test case from the Fifth AIAA Propulsion Aerodynamics Workshop. The main objective of the workshop was to assess the aerothermal interaction of a heated air exhaust with a film-cooled plate downstream of a convergent nozzle exit, which is representative of engine exhaust flow applications with film cooling. Two sets of hierarchical computational meshes are employed. The first set of meshes consists of workshop-provided Pointwise® meshes. The second set of meshes is generated using Ansys Fluent meshing. Steady conjugate heat transfer simulations with radiation are performed to account for heat conduction through solid materials as well as the electromagnetic heat produced by the solid surfaces of the plate, plenum, and nozzle. Reynolds-averaged Navier–Stokes simulations using the shear-stress [Formula: see text] turbulence model are conducted for a workshop-defined nozzle condition, set point 42, using three blowing ratios. Computational fluid dynamics results are validated against experimental velocity and temperature measurements recorded above the film-cooled plate.

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 categoriesMeta-epidemiology (narrow)
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 score0.258
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.211
Teacher spread0.200 · 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.

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

Citations4
Published2022
Admission routes1
Has abstractyes

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