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Record W4239938496 · doi:10.1115/1.1415036

Wake–Wake Interaction and Its Potential for Clocking in a Transonic High-Pressure Turbine

2001· article· en· W4239938496 on OpenAlexfundno aff
Frank Hummel

Bibliographic record

VenueJournal of Turbomachinery · 2001
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsnot available
FundersRéseau Provincial de Recherche en Adaptation-Réadaptation
KeywordsWakeTransonicMechanicsTrailing edgeStatorPhysicsRotor (electric)Leading edgeTurbineShock (circulatory)Vortex sheddingVorticityVortexAerospace engineeringAerodynamicsEngineeringReynolds numberTurbulence

Abstract

fetched live from OpenAlex

Two-dimensional unsteady Navier–Stokes calculations of a transonic single-stage high-pressure turbine were carried out with emphasis on the flow field behind the rotor. Detailed validation of the numerical procedure with experimental data showed excellent agreement in both time-averaged and time-resolved flow quantities. The numerical timestep as well as the grid resolution allowed the prediction of the Ka´rma´n vortex streets of both stator and rotor. Therefore, the influence of the vorticity shed from the stator on the vortex street of the rotor is detectable. It was found that certain vortices in the rotor wake are enhanced while others are diminished by passing stator wake segments. A schematic of this process is presented. In the relative frame of reference, the rotor is operating in a transonic flow field with shocks at the suction side trailing edge. These shocks interact with both rotor and stator wakes. It was found that a shock modulation occurs in time and space due to the stator wake passing. In the absolute frame of reference behind the rotor, a 50-percent variation in shock strength is observed according to the circumferential or clocking position. Furthermore, a substantial weakening of the rotor suction side trailing edge shock in flow direction is detected in an unsteady flow simulation when compared to a steady-state calculation, which is caused by convection of upstream stator wake segments. The physics of the aforementioned unsteady phenomena as well as their influence on design are discussed.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.006
GPT teacher head0.221
Teacher spread0.215 · 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 designBench or experimental
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

Citations25
Published2001
Admission routes1
Has abstractyes

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