Numerical Simulation of the Thermo-Mechanical Behaviour of Thermally Sprayed Abradable Coatings
Bibliographic record
Abstract
Abstract The newly designed abradable coatings are usually validated by rig tests, where samples are rubbed by the contact of a dummy blade with given running speed and incursion rate, simulating actual working conditions in an aircraft engine. The aim of this work was to develop a model of abradable coating rig tests, allowing extensive studies on the influence of coating properties and test conditions on the thermal behaviour of the system. The proposed model includes several steps implementing different numerical tools. Firstly, a relevant structural description of an abradable coating is obtained from micrographs, using an original image analysis route. FE (Finite Element) calculations based on this description allow then to estimate the coefficients of an anisotropic elastic law of mechanical behaviour. Furthermore, a plasticity law is deduced from a FE simulation of the material HR15Y hardness. These parameters are used as input of a FE simulation of a single blade-to-coating rubbing hit, resulting in calculated stresses and temperatures. Finally a global approach of the complete abradability test, based on the results obtained from the simulation of a single hit and on various assumptions, provides predictions of the blade and coating temperature variations versus time during a complete abradability test.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".