MétaCan
Menu
Back to cohort
Record W4297920368 · doi:10.31399/asm.cp.itsc2008p0336

Tailor-Made Coatings for Turbine Applications using the Triplex Pro 200

2008· article· en· W4297920368 on OpenAlexaff
K. Bobzin, F. Ernst, K. Richardt, D. Sporer, P. Fiala

Bibliographic record

VenueThermal spray · 2008
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsFort Saskatchewan Community Hospital
Fundersnot available
KeywordsMaterials scienceCoatingLubricantPorosityComposite materialThermal sprayingSurface roughnessSurface finishMetallurgy

Abstract

fetched live from OpenAlex

Abstract In modern jet engines, the efficiency of the compressor stages is highly dependent on the clearance between blade tip and casing. In order to improve efficiency of gas turbines (i.e. areo engines as well as land based gas turbines), the gap between the rotating turbine blades and casing has to be minimized. Any increase in the gap results in power loss. Abradable coatings permit a minimization of the clearance and control of the over-tip leakage by allowing the blade tips to cut into the coating. Thermal sprayed abradable coatings aim at a well balanced profile of properties relevant for the application as abradable seals. Amongst others these include: abradability, ageing resistance, corrosion and oxidation resistance, surface finish and bond strength to substrate materials. In this work, abradable coatings consisting of a multiphase material, comprising a metal matrix in addition to a solid lubricant as well as a defined level of porosity, were developed using the Triplex Pro 200 (Sulzer Metco, Wohlen, Switzerland) in order to increase the reproducibility and deposition efficiency. Additionally the influence of the process parameters on coating characteristics such as porosity, hardness and, resulting from this, coating erosion properties and abradability was investigated.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score0.562

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)0.0000.000

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 head0.036
GPT teacher head0.263
Teacher spread0.227 · 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 designBench or experimental
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

Citations1
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueThermal spraySame topicHigh-Temperature Coating BehaviorsFrench-language works237,207