A Statistical Assessment of the Damage State in Plasma-Sprayed Thermal Barrier Coating
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".