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Record W3203941272 · doi:10.3934/matersci.2021043

Numerical investigation of reinforced-concrete beam-column joints retrofitted using external superelastic shape memory alloy bars

2021· article· en· W3203941272 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

VenueAIMS Materials Science · 2021
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsWestern University
Fundersnot available
KeywordsSMA*Shape-memory alloyRetrofittingStructural engineeringParametric statisticsBeam (structure)Reinforced concreteMaterials scienceFinite element methodColumn (typography)ReinforcementComputer scienceComposite materialEngineeringMathematicsAlgorithm

Abstract

fetched live from OpenAlex

<abstract> <p>The unique properties of Shape Memory Alloys (SMAs) have motivated researchers to use them as primary reinforcement in reinforced concrete (RC) structures. In this study, the applicability of using external unbonded SMA bars to retrofit RC beam-column joints (BCJs) is investigated. A three-dimensional finite element model, which simulates the suggested retrofitting technique, is first developed, and validated using ABAQUS software. The model is then further simplified and utilized to conduct a parametric study to investigate the behaviour of SMA retrofitted RC BCJs. Results of the parametric study are used to perform multiple linear regression analysis. Simple equations, which can be used to calculate the length and amount of SMA bars required to retrofit a RC BCJ, are then developed.</p> </abstract>

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 categoriesMeta-epidemiology (narrow)
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 score0.076
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.018
GPT teacher head0.233
Teacher spread0.214 · 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