MétaCan
Menu
Back to cohort
Record W2523313877 · doi:10.1115/gt2016-56344

Application of an Overset Grid Method to the Large Eddy Simulation of a High-Speed Multistage Axial Compressor

2016· article· en· W2523313877 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsStatorAerodynamicsRotor (electric)Axial compressorGas compressorLarge eddy simulationGridTurbulenceVortexMechanicsComputational fluid dynamicsComputer simulationComputer scienceCoupling (piping)WindageAerospace engineeringMechanical engineeringSimulationPhysicsEngineeringGeometryMathematics

Abstract

fetched live from OpenAlex

The present study aims at evaluating the feasibility and the accuracy of the Large-Eddy Simulation of an actual high-pressure multistage compressor, performed with the TurboAVBP numerical method. TurboAVBP relies on the coupling of several domains via an overset grid method. The latter is demonstrated to keep the order of accuracy of the numerical scheme across six successive rotor-stator interfaces. The simulated configuration corresponds to the 3.5 stage axial compressor CREATE. Three unstructured grids of CREATE, with different resolutions, are generated. They contain 37 blades, the actual rotor tip clearances and a recirculating cavity. The predictions of the global aerodynamic performances and of the radial profiles are found to agree well with experimental data. The analysis of the flow shows that the finest grid exhibits the turbulent flow structures expected in such a configuration, including the blade and vane wakes and the rotor tip leakage vortices.

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.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.832
Threshold uncertainty score0.173

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 head0.007
GPT teacher head0.264
Teacher spread0.257 · 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