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Record W4392452214 · doi:10.1063/5.0194643

Heat transfer analysis of FRP–strengthened RC columns under fire

2024· article· en· W4392452214 on OpenAlexaff
Reem Talo, Salem Khalaf, Farid Abed, Yazan Alhoubi

Bibliographic record

VenueAIP conference proceedings · 2024
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsFibre-reinforced plasticMaterials scienceStructural engineeringComposite materialEngineering

Abstract

fetched live from OpenAlex

The use of externally bonded Fiber Reinforced Polymer (FRP) systems is becoming more relevant due to their superior performance in many structural applications. However, fire or elevated temperature exposure is a major concern for FRP systems due to the deterioration of the epoxy adhesive. This paper investigates the fire performance of unstrengthened and Carbon FRP (CFRP) strengthened Reinforced Concrete (RC) columns with and without fireproofing insulation. Four columns were modeled using the finite element software package ABAQUS to carry out the heat transfer analysis. All four columns were exposed to fire according to the ASTM E119 standard fire curve with an exposure period of three hours. The temperature-time curves were plotted 50 mm deep into the concrete, and 100 mm deep into the concrete, and at the longitudinal reinforcement. The results showed no noticeable improvement in the fire performance of RC columns with the addition of CFRP layers, where the temperature readings were almost the same. However, the use of the fireproofing insulation significantly affected the fire performance where the temperature at different times was significantly lower for the insulated columns compared to the uninsulated columns.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.886
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.017
GPT teacher head0.236
Teacher spread0.219 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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