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Record W2496485972 · doi:10.1088/0965-0393/23/7/075001

The effect of porosity on the hot corrosion failure of thermal barrier coatings

2015· article· en· W2496485972 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueModelling and Simulation in Materials Science and Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsUniversity of Toronto
FundersKing Fahd University of Petroleum and Minerals
KeywordsMaterials scienceThermal barrier coatingPorosityCorrosionComposite materialThermalMetallurgyForensic engineeringCoatingThermodynamics

Abstract

fetched live from OpenAlex

It has been found that the use of low-grade fuels in land-based turbines results in the hot corrosion (Type-I) degradation of turbine blades in Saudi Arabia. Due to the diffusion of a molten salt, V 2 O 5 , into the top coat of thermal barrier coatings, volumetric expansion of the coating occurs as a result of the tetragonal-to-monoclinic transformation of zirconia. The top coat material is usually made porous due to the need for higher thermal resistance in the coatings. In the present study, a phase field model that estimates the kinetics of microstructure evolution during the corrosion process is estimated at 900 °C. The transformation-induced stresses are predicted by coupling the phase transformation with elasticity. The governing equations are implemented numerically using the finite element method. The effect of pore size, shape, orientation, and dispersion is also investigated. The result shows that very high compressive stresses are developed within the coating cross-section, which eventually causes the spallation failure of the coating.

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.

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)0.001
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 score0.032
Threshold uncertainty score0.216

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.013
GPT teacher head0.222
Teacher spread0.209 · 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