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PBO-FRCM and CFRP strengthened reinforced concrete columns: In fire and post-fire behavior

2025· article· en· W4411362160 on OpenAlexaff
Salem Khalaf, Farid Abed, Ahmed El Refai, Yazan Alhoubi, Sanaz Ramzi, Hamzeh Hajiloo

Bibliographic record

VenueConstruction and Building Materials · 2025
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsCarleton University
FundersAmerican University of Sharjah
KeywordsMaterials scienceStructural engineeringComposite materialReinforced concreteFire performanceFire resistanceForensic engineeringEngineering

Abstract

fetched live from OpenAlex

This paper experimentally investigates the thermal response and post-fire structural behavior of seven short circular reinforced concrete columns. The variables include the type of strengthening system applied polypara-phenylene-benzo-bisthiazole (PBO) fiber-reinforced polymer (FRP) and fabric-reinforced cementitious matrix (FRCM), exposures (unexposed or fire-exposed), and using a cementitious-based Spray-applied Fire Resistive Materials (SFRM) insulation. Four columns were subjected to an ASTM E119 fire without any sustained load during the fire, while the other three columns were unexposed and served as controls. Two months after the fire test, fire-exposed columns were tested under axial loading and compared with unexposed ones. The steel rebar temperature in the insulated FRCM column remained below 150 °C for three hours, while this temperature was over 700 °C for the insulated CFRP-wrapped column. The post-fire axial tests indicated that the fire-exposed, insulated PBO-FRCM wrapped column retained a residual axial capacity of 92 %, significantly higher than the 21–66 % range observed in the other three columns. Considering reduced material properties, ACI code-based predictions for axial capacity showed reasonable accuracy with predicted-to-experimental ratios ranging from 0.86 to 1.16.

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 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 score0.046
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
Bibliometrics0.0000.000
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 head0.006
GPT teacher head0.222
Teacher spread0.217 · 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.

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

Citations9
Published2025
Admission routes1
Has abstractyes

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