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Record W2920822443 · doi:10.3390/app9050994

Experimental and Numerical Study of Engineered Cementitious Composite with Strain Recovery under Impact Loading

2019· article· en· W2920822443 on OpenAlexafffund
Moncef L. Nehdi, Mohamed A.E.M. Ali

Bibliographic record

VenueApplied Sciences · 2019
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceComposite numberComposite materialShape-memory alloySMA*Impact resistancePolyvinyl alcoholComputer science

Abstract

fetched live from OpenAlex

An engineered cementitious composite, endowed with strain recovery and incorporating hybrid shape memory alloy (SMA) and polyvinyl alcohol (PVA) short fibers, was subjected to drop weight impact loading. Numerical simulation of the composite’s impact behavior was performed, and the model predictions agreed well with the experimental findings. Numerical and experimental investigations demonstrated that incorporating SMA fibers in the composite yielded superior impact resistance compared to that of control mono-PVA specimens. Heat treatment stimulated the SMA fibers to apply local prestress on the composite’s matrix owing to the shape memory effect, thus enhancing energy absorption capacity, despite the damage incurred by PVA fibers during the heating process. The superior impact performance of the hybrid composite makes it a strong contender for the construction of protective structures, with a potential to enhance the safety of critical infrastructure assets against impact and blast loading.

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 score0.042
Threshold uncertainty score0.389

Codex and Gemma teacher scores by category

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

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 head0.013
GPT teacher head0.249
Teacher spread0.236 · 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

Citations20
Published2019
Admission routes2
Has abstractyes

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