MétaCan
Menu
Back to cohort
Record W2087199663 · doi:10.1115/gt2006-90838

The Effect of Stator-Rotor Hub Sealing Flow on the Mainstream Aerodynamics of a Turbine

2006· article· en· W2087199663 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsSyncrude (Canada)
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTurbineStatorAerodynamicsFlow (mathematics)Rotor (electric)Secondary flowTurbochargerReynolds-averaged Navier–Stokes equationsMechanicsTraverseEngineeringMechanical engineeringMaterials scienceMarine engineeringComputational fluid dynamicsAerospace engineeringPhysicsTurbulenceGeology

Abstract

fetched live from OpenAlex

An investigation into the effect of stator-rotor hub gap sealing flow on turbine performance is presented. Efficiency measurements and rotor exit area traverse data from a low speed research turbine are reported. Tests carried out over a range of sealing flow conditions show that the turbine efficiency decreases with increasing sealant flow rate but that this penalty is reduced by swirling the sealant flow. Results from time-accurate and steady-state simulations using a three-dimensional multi-block RANS solver are presented with particular emphasis paid to the mechanisms of loss production. The contributions toward entropy generation of the mixing of the sealant fluid with the mainstream flow and of the perturbed rotor secondary flows are assessed. The importance of unsteady stator wake/sealant flow interactions is also highlighted.

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: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.189

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 head0.002
GPT teacher head0.169
Teacher spread0.168 · 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