MétaCan
Menu
Back to cohort
Record W2073622185 · doi:10.1115/gt2006-90566

Strut Losses in a Diverging Annular Diffuser With Swirling Flow

2006· article· en· W2073622185 on OpenAlexafffund
G. K. Feldcamp, A. M. Birk

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsInletChord (peer-to-peer)Diffuser (optics)MechanicsMaterials sciencePressure dropFlow (mathematics)Total pressureFlow separationAspect ratio (aeronautics)Overall pressure ratioStructural engineeringComposite materialOpticsPhysicsEngineeringTurbulenceMechanical engineeringComputer science

Abstract

fetched live from OpenAlex

An experimental investigation into the overall influence of struts spanning a double divergent annular diffuser followed by a straight cored annular diffuser has been undertaken in order to determine the performance of various strut configurations over a wide range of inlet swirl conditions. Two strut profiles have been investigated in four and eight strut configurations. Results have shown that the presence of struts under no swirl conditions have a relatively small effect on the overall total pressure loss. Increasing the inlet swirl angle to 20° has shown that the struts are able to assist in recovery of the swirling flow such that the pressure recovery nearly approaches that without struts, despite increased total pressure losses. Performance at 40° swirl is highly dependent on strut profile; the higher thickness-to-chord ratio strut configurations show minimal decrease in pressure recovery compared to 20° swirl, while the lower thickness-to-chord ratio configurations experiences a significant decrease as the result of significant flow separation from the struts. The exit swirl number has been shown to correlate strongly with the strut profile shape, while the number of struts had only a secondary influence. The exit velocity profiles show significant distortions at 40° swirl, and as a result the ideal pressure recovery calculated from the inlet and exit profiles change with strut configuration at 40° swirl.

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 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 score0.038
Threshold uncertainty score0.281

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 head0.144
Teacher spread0.142 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations6
Published2006
Admission routes2
Has abstractyes

Explore more

Same topicTurbomachinery Performance and OptimizationFrench-language works237,207