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Record W2010192482 · doi:10.1115/2001-gt-0421

Optimizing Deformation Path for Stress Relaxation Tests on Superalloys at High Temperatures

2001· article· en· W2010192482 on OpenAlexaff
Nirmal K. Sinha, Rick Kearsey

Bibliographic record

VenueVolume 4: Manufacturing Materials and Metallurgy; Ceramics; Structures and Dynamics; Controls, Diagnostics and Instrumentation; Education; IGTI Scholar Award · 2001
Typearticle
Languageen
FieldEngineering
TopicHigh Temperature Alloys and Creep
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsSuperalloyMaterials scienceIsothermal processRelaxation (psychology)Stress relaxationMicrostructureStress (linguistics)WeldabilityMetallurgyDeformation (meteorology)CreepComposite materialThermodynamicsWelding

Abstract

fetched live from OpenAlex

Stress relaxation results are highly sensitive to test conditions at elevated temperatures. The tests require precise control of environmental conditions and test methods. An experimental technique has been developed for conducting isothermal closed-loop controlled, constant strain, tensile stress relaxation tests at low strains (lower than 0.003) imposed in about one second. It is based on optimizing the initial strain, initial loading path and subsequent control of strain during the hold time. The methodology developed and the technical details used in conducting the stress relaxation tests, for temperatures up to 1000°C, are presented by using a nickel-base superalloy (IN-738LC) as a test material. The approach discussed has been found to be suitable for evaluating the microstructure - flow properties relationship of superalloys, corresponding to as-heat-treated initial microstructure, and could be applicable to any metals, alloys and ceramics at elevated temperatures. The method is being assessed as a means of evaluating the weldability of nickel-base superalloys.

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 categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.703
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.205
Teacher spread0.201 · 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.

Study designObservational
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
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueVolume 4: Manufacturing Materials and Metallurgy; Ceramics; Structures and Dynamics; Controls, Diagnostics and Instrumentation; Education; IGTI Scholar AwardSame topicHigh Temperature Alloys and CreepFrench-language works237,207