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One-Dimensional Shape Memory Alloy Model Applicable to Any Status of Stress and Temperature

2006· article· en· W1975632373 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueKey engineering materials · 2006
Typearticle
Languageen
FieldMaterials Science
TopicShape Memory Alloy Transformations
Canadian institutionsKootenay Association for Science & Technology
FundersKorea Advanced Institute of Science and Technology
KeywordsShape-memory alloyAusteniteMaterials scienceMartensiteKineticsTransformation (genetics)Stress (linguistics)ThermodynamicsWork (physics)AlloyDiffusionless transformationMetallurgyPhysicsMicrostructureChemistryClassical mechanics

Abstract

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The transformation kinetics formulation is the principal factor underlying the constitutive model of shape memory alloys. Therefore, the transformation kinetics formulation, which is applicable to any status of stress and temperature, is essential for predicting the material behavior of SMAs. In this work, we show that the transformation kinetics of the Brinson model, which is the most widely used 1-dimensional model, has shortcomings under certain stress and temperature histories. In addition, we propose a modified transformation kinetics model that can be used for any stress or temperature conditions. The martensite transformation kinetics is modified so that the transformation from austenite into temperature-induced martensite, due to the decrement of temperature, is coupled with a transformation from austenite or temperature-induced martensite into stress-induced martensite, due to the increment of the stress. Through this modification, the suggested model can simulate the behavior of shape memory alloy materials under arbitrarily changed circumstances at every stress-temperature region.

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.

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 score0.287
Threshold uncertainty score0.876

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 head0.009
GPT teacher head0.206
Teacher spread0.198 · 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