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Record W4376881276 · doi:10.31399/asm.cp.itsc2023p0001

Influence of Surface Geometry and Microstructural Features on the Delamination and Crack Propagation of Brittle Convex Thermal Barrier Films during Thermal Cyclic Loading

2023· article· en· W4376881276 on OpenAlexaff
Aleksandra Nastic, Larry Pershin, J. Mostaghimi

Bibliographic record

VenueThermal spray · 2023
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials scienceComposite materialTemperature cyclingThermal barrier coatingCoatingBrittlenessDelamination (geology)MicrostructureResidual stressSurface finishUltimate tensile strengthFracture mechanicsSurface roughnessPorosityThermal

Abstract

fetched live from OpenAlex

Abstract The influence of air plasma sprayed alumina coating geometry, microstructure, interface roughness on its delamination and crack propagation resistance during low temperature thermal cycling, i.e. thermal mismatch stress, is investigated both numerically and experimentally. Previous studies on thermal cycling loading concentrate on flat, numerically designed locally curved specimens and/or mathematically modeled roughness without extension towards real coating morphology, which renders the conclusions less practically driven. Results show that arbitrarily oriented cracks originate predominantly near the coating/substrate interface and propagate along zones of high tensile and shear residual stress. The crack path deflection was attributed to the complex stress concentration structure resultant from the intricate microstructural porosity and coating general convex geometry. Microstructural features such as porosity increase the interfacial and coating tensile stress, which may lead to important delamination processes even during low temperature thermal cycling.

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 score0.452
Threshold uncertainty score0.573

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 head0.006
GPT teacher head0.211
Teacher spread0.205 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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