MétaCan
Menu
Back to cohort
Record W1979782302 · doi:10.1115/gt2012-68171

Numerical Simulation of Tool/Abradable Material Interaction Experiments

2012· preprint· en· W1979782302 on OpenAlexaff
Alain Batailly, Marion Cuny, Mathias Legrand

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicTribology and Lubrication Engineering
Canadian institutionsMcGill University
FundersOffice National d'études et de Recherches AérospatialesSafranCentre National de la Recherche Scientifique
KeywordsMaterials scienceCoatingCasingContext (archaeology)ViscoplasticityComputer simulationRotor (electric)MechanicsMechanical engineeringComposite materialStructural engineeringFinite element methodConstitutive equationEngineeringPhysics

Abstract

fetched live from OpenAlex

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.518
Threshold uncertainty score0.963

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)0.0010.000

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 head0.024
GPT teacher head0.280
Teacher spread0.255 · 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 designSimulation or modeling
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
Published2012
Admission routes1
Has abstractyes

Explore more

Same topicTribology and Lubrication EngineeringFrench-language works237,207