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Record W2122316417 · doi:10.1115/1.4027204

Experimental Evaluation of Service-Exposed Nozzle Guide Vane Damage in a Rolls Royce A-250 Gas Turbine

2014· article· en· W2122316417 on OpenAlexaff
D. Bouchard, Asad Asghar, Marc LaViolette, W. Allan, R. Woodason

Bibliographic record

VenueJournal of Engineering for Gas Turbines and Power · 2014
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsTrailing edgeNozzleTransonicAerospace engineeringMarine engineeringTurbineLeading edgeEnhanced Data Rates for GSM EvolutionStructural engineeringMechanical engineeringGeologyMaterials scienceComputer scienceEnvironmental scienceEngineeringAerodynamics

Abstract

fetched live from OpenAlex

A unique methodology and test rig was designed to evaluate the degradation of damaged nozzle guide vanes (NGVs) in a transonic annular cascade in the short duration facility at the Royal Military College. A custom test section was designed which featured a novel rotating instrumentation suite. This permitted 360 deg multispan traverse measurements downstream from unmodified turbine NGV rings from a Rolls-Royce/Allison A-250 turbo-shaft engine. The downstream total pressure was measured at four spanwise locations on both an undamaged reference and a damaged test article. Three performance metrics were developed in an effort to determine characteristic signatures for common operational damage such as trailing edge bends or cracked trailing edges. The highest average losses were observed in the root area, while the lowest occurred closer to the NGV tips. The results from this study indicated that multiple spanwise traverses were required to detect localized trailing edge damage. Recommendations are made for future testing and to further develop performance metrics.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.238
Teacher spread0.229 · 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

Citations12
Published2014
Admission routes1
Has abstractyes

Explore more

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