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Record W2018325600 · doi:10.1115/smasis2014-7499

The Effect of Laser Welds on the Thermomechanical Fatigue of NiTi Shape Memory Alloys

2014· article· en· W2018325600 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicShape Memory Alloy Transformations
Canadian institutionsSmarter Alloys (Canada)University of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNickel titaniumMaterials scienceShape-memory alloyWeldingBrittlenessIntermetallicMetallurgyUltimate tensile strengthFatigue limitPseudoelasticityComposite materialMartensiteMicrostructureAlloy

Abstract

fetched live from OpenAlex

Welding and joining of NiTi based shape memory alloys (SMAs) is essential for their integration into an increasing variety of applications. The titanium elemental constituent significantly complicates joining, especially with dissimilar materials where brittle intermetallics are often formed. There have been a relatively small number of investigations of the welding of NiTi in similar and in dissimilar joints. Of these studies, a few have investigated the effect of similar welded joints on the pseudoelastic fatigue of NiTi. To the author’s knowledge there are no investigations on the effect of joining on the fatigue of thermally actuated NiTi. The current work investigates the physical, thermomechanical fatigue and shape memory properties of welded shape memory wires. The welded NiTi wires successfully achieved 86% of the base metal ultimate tensile strength. The cycle lives of the welded wires that underwent thermomechanical fatigue were significantly less than the base metal.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.047
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.252
Teacher spread0.234 · 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

Quick stats

Citations1
Published2014
Admission routes2
Has abstractyes

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