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Record W4293240902 · doi:10.18280/mmep.090209

Restoring Strength of Reinforced Concrete Horizontally Curved Box Beam with Opening Using Reactive Powder Concrete (RPC) and FRP Techniques

2022· article· en· W4293240902 on OpenAlexvenueno aff
Ameer Mohsin Hashim, Ammar Yasier Ali

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2022
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceBeam (structure)Deflection (physics)Structural engineeringSpan (engineering)Transverse planeComposite materialFibre-reinforced plasticOpticsEngineeringPhysics

Abstract

fetched live from OpenAlex

This study is devoted to test the structural response of reinforced concrete horizontally curved box beams in presence of vertical and transverse opening restored by CFRP Laminates or Reactive Powder Concrete (RPC) technique and compared to that having opening but without restoring. Six horizontally circular curved box beams were casted and tested in this experimental work, three specimens with opening in vertical direction and the other three specimens including opening in transverse direction. Accordingly, each direction has three types of beams, first one including opening without restoring and used as a reference specimen, second one with opening restored by CFRP Laminates technique and third one with opening restored by Reactive Powder Concrete (RPC) technique. The test program includes the main variables; direction of opening. The beams were tested as a two-span continuous beam, each span represents a quarter circle, under the effect of two concentrated loads each load positioned at top face of midspan of the beam. The findings of the experiments showed that the use of Reactive Powder Concrete (RPC) and CFRP Laminates and techniques around opening notably increased the ultimate load capacity of specimens (CB2.V60.S1, CB3.V60.S2, CB5.T60.S1 and CB6.T60.S2) by about (18.5% and 15.3%,135% and 38.3%) respectively, when compared with specimens without restoring. Service mid-span deflection response not give clear effect, while service mid-span twisting was improved by about (55.28%, 13%, 10.73% and 2.37%) for all restored specimens (CB2.V60.S1, CB3.V60.S2, CB5.T60.S1 and CB6.T60.S2) respectively. Genially, significant increase in stiffness can be observed for restored specimens as a comparison with those without restoring.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.020
GPT teacher head0.212
Teacher spread0.192 · 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 designSimulation or modeling
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

Citations1
Published2022
Admission routes1
Has abstractyes

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