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Record W3024566950 · doi:10.1139/cjce-2019-0511

Experimental investigation of RC columns confined with Ni–Ti shape memory alloy wires versus CFRP sheets

2020· article· en· W3024566950 on OpenAlexafffundvenue
Khaled S. Abd‐Elrahman, Raafat El‐Hacha

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSMA*Shape-memory alloyMaterials scienceComposite materialCompression (physics)AlloySpiral (railway)Nickel titaniumStructural engineeringCompressive strengthMechanical engineeringComputer scienceEngineering

Abstract

fetched live from OpenAlex

The critical need to enhance existing strengthening methods with more efficient and effective ones has led to the evolvement of smarter and innovative class of materials termed shape memory alloys (SMA). The SMAs possess unique characteristic properties that lie in their ability to undergo large deformations and return to their undeformed shape through stress removal or heating process. Limited research studies conducted using SMAs have shown high potential for their use in building industry. Results presented in this research study are from an experimental study that investigated the compressive behaviour of uniaxial concentrically loaded nickel–titanium (Ni–Ti) SMA-spirally confined RC columns and compared with RC columns confined with conventional carbon fibre reinforced polymer (CFRP) sheets. The compression tests revealed that actively confining the concrete column with Ni–Ti SMA spiral wires increased the performance of the concrete dramatically. Additionally, the active Ni–Ti SMA-confinement system exhibited superior performance compared to the conventional passive CFRP-confinement system.

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 score0.002
Threshold uncertainty score0.007

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)0.0020.000

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 head0.015
GPT teacher head0.189
Teacher spread0.173 · 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

Citations5
Published2020
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Civil Engineering→Same topicStructural Behavior of Reinforced Concrete→French-language works237,207→