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Record W3102817427 · doi:10.11159/iccste20.240

Performance of Steel I-Beams Strengthened by Fastening Hybrid FRPStrips

2020· article· en· W3102817427 on OpenAlexvenueno aff
Omnia R. AbouEl-Hamd, Amr M.I. Sweedan, Bilal El-Ariss

Bibliographic record

VenueProceedings of the International Conference on Civil, Structural and Transportation Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsnot available
Fundersnot available
KeywordsSTRIPSFibre-reinforced plasticStructural engineeringMaterials scienceComposite materialEngineering

Abstract

fetched live from OpenAlex

Fiber-Reinforced Polymers (FRPs) have been widely used in strengthening steel structures. Few researches were conducted to verify the adequacy of strengthening steel structures by fastening FRPs. The current paper reports on the outcomes of an experimental study aimed at strengthening steel I-beams by fastening hybrid FRP (HFRP) strips. A total of ten UB203x102x23 beams were tested in a four-point loading setup. Steel bolts were used to fasten the HFRP strips to the beam bottom flange. The effect of HFRP length was assessed by considering three scenarios (1,620, 1,170 and 810 mm) that correspond to 90%, 65% and 45% of the clear span length of tested beams. Single and double HFRP strips were utilized to evaluate the effect of HFRP thickness on the performance of the strengthened beams. Staggered and uniform bolt arrangements were used to assess the effect of bolt arrangement on the performance of the fastened systems. All strengthened beams exhibited better yield and ultimate strength as compared to the control beam. Fastening two HFRP strips with lengths of 90% of the beam clear span revealed 21% enhancement in the ultimate capacity of the strengthened beam.

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 score0.337
Threshold uncertainty score0.608

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 head0.012
GPT teacher head0.196
Teacher spread0.184 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the International Conference on Civil, Structural and Transportation EngineeringSame topicStructural Behavior of Reinforced ConcreteFrench-language works237,207