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Record W2902114291 · doi:10.1680/jcoma.18.00048

Behaviour of hybrid fibre-reinforced engineered cementitious composites with strain recovery

2018· article· en· W2902114291 on OpenAlexaff
Mohamed A.E.M. Ali, Moncef L. Nehdi

Bibliographic record

VenueProceedings of the Institution of Civil Engineers - Construction Materials · 2018
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsWestern University
Fundersnot available
KeywordsMaterials scienceComposite materialShape-memory alloyFlexural strengthComposite numberUltimate tensile strengthDuctility (Earth science)BendingSMA*Structural engineeringTensile testingComputer scienceCreep

Abstract

fetched live from OpenAlex

A self-centring engineered cementitious composite (ECC) was developed. The novel ECC incorporates a hybrid combination of short and dispersed polyvinyl alcohol and shape memory alloy (SMA) fibres, thus achieving superior tensile and flexural characteristics. In addition to its enhanced ductility, the composite is endowed with strain recovery capability, which could be achieved by heat treatment, leading to crack closing through the shape memory effect of the SMA fibres. An inverse analysis method was proposed based on the experimental results to predict the uniaxial tensile test results of the ECC composites using simple flexural test results. The inverse method proved to be an effective predictive tool, cost effective in terms of laborious direct tensile tests and the associated sophisticated test set-up. The ductile composite endowed with crack-closing capability is a strong contender for critical infrastructure projects and protective structures.

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 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 score0.030
Threshold uncertainty score0.949

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.187
Teacher spread0.181 · 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 teacher head, 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

Citations1
Published2018
Admission routes1
Has abstractyes

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Same venueProceedings of the Institution of Civil Engineers - Construction MaterialsSame topicInnovative concrete reinforcement materialsFrench-language works237,207