MétaCan
Menu
Back to cohort
Record W2080046284 · doi:10.1115/gt2012-69151

Impeller-Diffuser Interaction in Centrifugal Compressors

2012· article· en· W2080046284 on OpenAlexaff
Chris Robinson, Michael Casey, Brad Hutchinson, Robin Steed

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsAnsys (Canada)
Fundersnot available
KeywordsImpellerDiffuser (optics)Centrifugal compressorMechanicsRotor (electric)StatorGas compressorTransient (computer programming)Computational fluid dynamicsTurbochargerVoluteControl theory (sociology)Materials sciencePhysicsMechanical engineeringEngineeringComputer scienceOptics

Abstract

fetched live from OpenAlex

This paper reports several CFD analyses of a centrifugal compressor stage with a vaned diffuser at high pressure ratio using different techniques to model the rotor-stator interaction. A conventional steady stage calculation with a mixing-plane type interface between the rotor and stator was used as a baseline. This simulation gave excellent agreement with the measured performance characteristics at design speed, demonstrating the ability of the particular steady simulation used to capture the essential features of the blockage interaction between the components. A full annulus simulation using a transient rotor-stator interaction (TRS) method was then used at the peak efficiency point to obtain a fully unsteady reference solution, and this predicted a small increase in peak efficiency. Finally, a computationally less expensive unsteady calculation using a Time Transformation (TT) method was carried out. This gave similar results to the fully transient calculation suggesting that this is an acceptable approach to estimate unsteady blade loading from the interaction. The impeller diffuser spacing was then reduced from 15 to 7% of the impeller tip radius using the more affordable TT approach. This identified an increase in efficiency of 1% and predicted unsteady pressure fluctuations in the impeller which were 116% higher with the closely spaced diffuser.

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)0.001
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 score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.009
GPT teacher head0.216
Teacher spread0.208 · 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

Citations33
Published2012
Admission routes1
Has abstractyes

Explore more

Same topicTurbomachinery Performance and OptimizationFrench-language works237,207