Numerical Simulation of Tool/Abradable Material Interaction Experiments
Bibliographic record
Abstract
Applying abradable coating on the casing of turbomachines has been widely recognized as a robust solution advantageously combining the adjustment of operating clearances with the reduction of potential non-repairable damages. Thus, the modeling of this material is a growing field of investigation. Based on the numerical strategy proposed and detailed in previous publication by the same authors, the present study aims at capturing the mechanical behavior of abradable coating in the context of high speed interaction with a rigid tool. The plastic law given is first enriched in order to take into account strain rate dependence. The sensitivity of the model regarding its main numerical parameters is assessed and highlights the role of each of these parameters. The calibration of numerical results with respect to experimental results lead to very satisfying results that confirm that the proposed strategy is well-suited for the modeling of abradable coating. Finally, the newly developped viscoplastic law is applied to a 3D rotor/stator interaction case to determine the criticity of strain rate dependence in the case of blade/casing contact.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.005 | 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".