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Record W1502256786 · doi:10.4236/msa.2015.67071

Wear Resistance and Indentation Behavior of Equiatomic Superelastic TiNi and 60NiTi

2015· article· en· W1502256786 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

VenueMaterials Sciences and Applications · 2015
Typearticle
Languageen
FieldMaterials Science
TopicShape Memory Alloy Transformations
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaGlenn Research CenterNational Aeronautics and Space Administration
KeywordsMaterials sciencePseudoelasticityShape-memory alloyIndentationReciprocating motionAlloyUltimate tensile strengthComposite materialMetallurgyWear resistanceMartensiteMicrostructureMechanical engineering

Abstract

fetched live from OpenAlex

Indentation and reciprocating wear tests are carried out to study dent and wear resistance of superelastic Ti-Ni alloys. The effect of loading rate on the superelastic behavior of TiNi under indentation loading is investigated and compared to a new generation of shape memory alloys, i.e., 60NiTi. Only limited amount of work has been done to investigate the dependency of superelasticity on loading rate of TiNi under localized compressive loads, but much work is directed towards understanding the effect of strain rate on tensile properties. Understanding the superelastic behavior helps to employ superelastic alloys in applications where high impact loading is expected as in bearings and gears. In the present study, it is found that dent resistance of Ti-Ni alloy is not significantly affected by loading rate (within the employed loading conditions). It has also been found that new-generation 60NiTi alloy exhibits superior wear and dent resistance, as well as higher hardness compared to equiatomic TiNi.

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)0.001
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 score0.039
Threshold uncertainty score0.287

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.040
GPT teacher head0.293
Teacher spread0.253 · 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