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Development and Characterization of a Damage Tolerant Microstructure for a Nickel Base Turbine Disc Alloy

2000· article· en· W2328373095 on OpenAlexafffund
Richard Kearsey, A. K. Koul, J. Beddoes, Christopher R. Cooper

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHigh Temperature Alloys and Creep
Canadian institutionsCarleton UniversityNational Research Council Canada
FundersPratt and Whitney Canada
KeywordsSuperalloyMaterials scienceCreepMicrostructureUltimate tensile strengthDamage toleranceAlloyTurbineGrain boundaryMetallurgyGrain sizeTensile testingStress (linguistics)Characterization (materials science)Composite materialFracture (geology)Structural engineeringMechanical engineeringNanotechnologyEngineeringComposite number

Abstract

fetched live from OpenAlex

A modified heat treatment has been developed for the nickel-base superalloy, PWA 1113, to create a damage tolerant microstructure @TM) using mechanistic microstructural design concepts.The DTM was designed with the aim of imparting improved fatigue crack growth resistance without forfeiture of other vital properties such as tensile strength, stress rupture life, and low cycle fatigue lifetimes.This was achieved by optimizing the material's grain size, grain boundary morphology, and the intragranular precipitate size and distribution.Mechanical testing demonstrated that when compared to the conventional microstructure (CM), the short crack growth rate for the DTM was slower by a factor of 3 at room temperature, and 2.2 times slower at 482 "C.Creep test results showed that at 690 MPa (100 ksi) and 705 "C, the creep-rupture life was extended by a factor of almost 4 for the new DTM.Tensile test results indicated minimal strength losses for the DTM with respective YS and UTS values of 80% and 90% of the CM baseline values at both test temperatures.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.004
GPT teacher head0.179
Teacher spread0.175 · 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 source (direct Gemma or distilled Codex), 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

Citations8
Published2000
Admission routes2
Has abstractyes

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