Thermo-Mechanical Modeling of Abradable Coating Wear in Aircraft Engines
Bibliographic record
Abstract
In modern turbomachine designs, the nominal clearances between rotating bladed-disks and their surrounding casing are reduced to improve aerodynamic performances of the engine. This clearance reduction increases the risk of contacts between components and may lead to hazardous interaction phenomena. A common technical solution to mitigate such interactions consists in the deposition of an abradable coating along the casing inner surface. This enhances the engine efficiency while ensuring operational safety. However, contact interactions between blade tips and an abradable layer may yield unexpected wear removal phenomena. The aim of this work is to investigate the numerical modeling of thermal effects within the abradable layer during contact interactions and compare it with experimental data. A dedicated thermal finite element mesh is employed. At each time-step, a weak thermo-mechanical coupling is assumed: thermal effects affect the mechanics of the system, but the mechanical deformation of the elements has no effect on temperatures. Weak coupling is well appropriated in the case of rapid dynamics using small time-step and explicit resolution schemes. Moreover, only heat transfer by conduction is considered in this work. To reduce computational times, a coarser spatial discretization is used for the thermal mesh comparing to the mechanical one. The time-step used to compute the temperature evolution is larger than the one used for the mechanical iterations since the time constant of thermal effect is larger than contact events. The proposed numerical modeling strategy is applied on an industrial blade to analyze the impact of thermal effects on the blade's dynamics.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".