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Record W2896127718 · doi:10.2351/1.5061581

Laser cladding of In-625 alloy for repairing fuel nozzles for gas turbine engines

2009· article· en· W2896127718 on OpenAlexaff
Lijue Xue, Alex Prociw, Shenghui Wang, Jianyin Chen, Yangsheng Li

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHigh Entropy Alloys Studies
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMaterials scienceCladding (metalworking)LaserNozzleAlloyMetallurgyMechanical engineeringOpticsEngineering

Abstract

fetched live from OpenAlex

Laser cladding provides unique capabilities for repairing damaged components that currently are difficult or even impossible to repair using conventional methods. In this paper, laser cladding of IN-625 alloy was investigated. Testing results reveal that laser-clad IN-625 on wrought IN-625 substrate demonstrates comparable or even substantially improved fatigue life as compared to the IN-625 baseline specimens at the room temperature as well as at elevated temperature. Laser-clad IN-625 also shows slightly improved wear resistance. Therefore, laser cladding of IN-625 is very attractive for repairing various damaged wrought IN-625 components for aerospace gas turbine engines. A case study is also presented in this paper on laser cladding of IN-625 to restore fretted fuel nozzles that currently are difficult to repair using conventional methods.

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: Empirical
Teacher disagreement score0.122
Threshold uncertainty score0.627

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 head0.012
GPT teacher head0.234
Teacher spread0.222 · 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

Citations4
Published2009
Admission routes1
Has abstractyes

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