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Record W607461436 · doi:10.1177/0021998315590262

Degradation characteristics of new bio-resin based-fiber-reinforced polymers for external rehabilitation of structures

2015· article· en· W607461436 on OpenAlexaff
Mohammadreza Foruzanmehr, Saïd Elkoun, Amir Fam, Mathieu Robert

Bibliographic record

VenueJournal of Composite Materials · 2015
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsQueen's UniversityUniversité de Sherbrooke
Fundersnot available
KeywordsMaterials scienceThermosetting polymerComposite materialEpoxyPolymerGlass fiberFibre-reinforced plasticAbsorption of waterDegradation (telecommunications)Composite numberFiber

Abstract

fetched live from OpenAlex

Sustainability has recently become a key issue in the design and manufacture of products, due to dwindling oil reserves and increased environmental awareness. Therefore, bio-sourced resins are suggested to be used as an alternative in order to reduce the environmental impact of composite production. This paper presents the mechanical and physico-chemical characterization and the environmental degradation evaluation of furan resin-based glass fiber reinforced polymer (bio-sourced glass fiber reinforced polymer) for structural retrofitting applications in comparison with those of an equivalent thermoset-based glass fiber reinforced polymer (petro-sourced glass fiber reinforced polymer). Epoxy resin was used as a representative for petroleum-derived synthetic thermoset. To conduct this preliminary study, the following steps were taken: (1) prepare composites made from furan and epoxy resins, (2) characterize the mechanical and physico-chemical properties of the composites, (3) study the moisture absorption, and finally, (4) evaluate the degradation of both composites when subjected to alkaline solutions which was simulated to leached concrete pore solution. The experimental results show that the use of furan resin as polymer matrix in glass fiber reinforced polymer leads to an increase in the moisture absorption and a significant decrease in the degradation in alkaline solution.

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)0.001
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 score0.069
Threshold uncertainty score0.725

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.019
GPT teacher head0.276
Teacher spread0.257 · 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

Citations21
Published2015
Admission routes1
Has abstractyes

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