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Record W4385977774 · doi:10.3390/fire6080322

Experimental Investigation of Concrete Cylinders Confined with PBO FRCM Exposed to Elevated Temperatures

2023· article· en· W4385977774 on OpenAlexaff
Reem Talo, Farid Abed, Ahmed El Refai, Yazan Alhoubi

Bibliographic record

VenueFire · 2023
Typearticle
Languageen
FieldEngineering
TopicMasonry and Concrete Structural Analysis
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMaterials scienceMortarComposite materialCompressive strengthRetrofittingCementitiousEpoxyFibre-reinforced plasticCementStructural engineering

Abstract

fetched live from OpenAlex

Externally bonded fiber-reinforced polymers (FRPs) have been widely used for strengthening and retrofitting applications. However, their efficacy is hindered by the poor resistance of their epoxy resins to elevated temperatures and their limited compatibility with concrete substrates. To address these limitations, fabric-reinforced cementitious matrix (FRCM), also known as textile reinforced mortar (TRM), systems have emerged as an alternative solution. In this study, experimental tests were performed on concrete cylinders confined with FRCM systems that consisted of mineral mortar and poliparafenilenbenzobisoxazole fabric (PBO). The cylinders with concrete strengths of 30, 45, and 70 MPa, were confined with one or two FRCM layers, and were subjected to different target temperatures (100, 400, and 800 °C). The experimental results highlighted the confinement effect of FRCMs on the compressive strength of the tested cylinders. Cylinders exposed to 100 °C exhibited a slight increase in their compressive strength, while no specific trend was observed in the compressive strength of cylinders heated to 400 °C. Specimens heated up to 800 °C experienced a significant reduction in strength, reaching up to 82%.

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 score0.003

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)0.0010.000

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 head0.012
GPT teacher head0.208
Teacher spread0.196 · 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

Citations13
Published2023
Admission routes1
Has abstractyes

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