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Record W4381192903 · doi:10.32920/23542038

Structural Performance of Shear Deficient Beams with High Performance Reinforced Concrete Jacket

2023· preprint· en· W4381192903 on OpenAlexaff
Rehman Rana

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMaterials scienceFlexural strengthComposite materialDuctility (Earth science)Structural engineeringStiffnessShear (geology)CementitiousReinforced concreteEngineeringCementCreep

Abstract

fetched live from OpenAlex

This research investigates the performance of shear deficient concrete beams strengthened with reinforced jackets made of three different high performance concretes (HPCs) namely engineered cementitious composite (ECC), ultrahigh performance concrete (UHPC) and normal self-consolidating concrete (SCC) subjected to static monotonic and fatigue loading[.] The influence of HPC jackets is described based on strength, stiffness, energy absorbing capacity, steel/concrete strain developments and failure modes. Shear deficient beams with UHPC jacket showed highest strength, energy absorption capacity and ductility followed by those with ECC and SCC jackets. Shear deficient beams with UHPC jacket exhibited flexural failure. ECC jacketed beams subjected to fatigue loading exhibited lower stiffness, energy absorption capacity and strength degradation compared to their UHPC counterparts. This research confirms the viability of using ECC and UHPC as repair materials for the structural components.

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 score0.001
Threshold uncertainty score0.004

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 head0.019
GPT teacher head0.218
Teacher spread0.199 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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