MétaCan
Menu
Back to cohort
Record W4236485937 · doi:10.1115/gt2014-25066

Performance Metrics and Experimental Testing of Erosion-Resistant Compressor Blade Coatings

2014· article· en· W4236485937 on OpenAlexafffund
Sean G. Leithead, W. Allan, Linruo Zhao

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsNational Research Council CanadaRoyal Military College of Canada
FundersNational Research Council CanadaMinistère de la Défense Nationale
KeywordsMaterials scienceDurabilityGas compressorErosionComposite materialTurbine bladeLeading edgeCoatingMetallurgyTurbineMechanical engineeringEngineeringGeology

Abstract

fetched live from OpenAlex

A durability test rig for erosion-resistant gas turbine engine compressor blade coatings was designed and commissioned. Bare and coated 17-4PH steel modified NACA 6505-profile blades were spun at an average speed of 10 860 rpm and exposed to garnet sand-laden air for 5 hours at an average sand concentration of 2.5gm3of air and a blade leading edge (LE) Mach number of 0.50. The rig was designed to represent a first stage axial compressor. Two 16μm-thick coatings were tested: Titanium Nitride (TiN) and Chromium-Aluminum-Titanium Nitride (CrAlTiN), both applied using an Arc Physical Vapour Deposition technique. A composite scale, defined as the LAZ score, was devised to compare the durability performance of bare and coated blades based on mass-loss and blade dimension changes. The bare blades’ LAZ score was set as a benchmark of 1.00, with the TiN-coated and CrAlTiN-coated blades obtaining respective scores of 0.69 and 0.41. A lower score identified a more erosion-resistant coating. Major locations of blade wear included: trailing edge (TE), LE and rear suction surface (SS). TE thickness was reduced, the LE became blunt, and the rear SS was scrubbed by overtip and recirculation zone vortices. The erosion effects of secondary flows were found to be significant. Erosion damage due to reflected particles was absent due to a low blade solidity of 0.7. The rig is best suited for durability evaluation of erosion-resistant coatings after being proven worthy of consideration for gas turbine engines through ASTM standardized testing.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.505

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 head0.018
GPT teacher head0.231
Teacher spread0.212 · 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 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

Citations1
Published2014
Admission routes2
Has abstractyes

Explore more

Same topicHigh-Temperature Coating BehaviorsFrench-language works237,207