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Record W2011425174 · doi:10.1115/gt2003-38790

A Statistical Assessment of the Damage State in Plasma-Sprayed Thermal Barrier Coating

2003· article· en· W2011425174 on OpenAlexafffund
Xijia Wu, Prakash Patnaik, M. Liao, W.R. Chen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsNational Research Council Canada
FundersNational Research Council CanadaMinistère de la Défense Nationale
KeywordsThermal barrier coatingSuperalloyMaterials scienceCoatingComposite materialCrackingMicrostructurePlasmaThermal sprayingThermalTurbine bladeTurbineMechanical engineering

Abstract

fetched live from OpenAlex

Thermal barrier coatings (TBC), which consist of yttria-partially-stabilized zirconia top coat and metallic bond coat deposited onto superalloy substrate, are favorably used as protective coatings of the hot section parts in advanced gas turbine engines to withstand increased inlet temperatures and thus improve engine performance. However, understanding and modeling the damage evolution in TBC under service exposed conditions still remain to be a challenge. This is due to the failure by the coupled effects of the external load-environment, the thermal expansion mismatch between the bond coat and TBC, microstructure of the coating, and degradation of the bond coat. In this study, the damage state in an air-plasma-sprayed APS) thermal barrier coating system was assessed using metallurgical and statistical methods. The damage evolution in the TBC can thus be described with a high degree of confidence. A mechanistic model, representing the micro-cracking mechanism, is presented and its prediction is also assessed on a statistical basis.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.486
Threshold uncertainty score0.405

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 head0.008
GPT teacher head0.251
Teacher spread0.243 · 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

Citations3
Published2003
Admission routes2
Has abstractyes

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