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Record W3163691450 · doi:10.3390/buildings11050180

Experimental Investigation of ECC Jackets for Repair of Pre-Damaged R.C. Members under Monotonic Loading

2021· article· en· W3163691450 on OpenAlexaff
Anthos Ioannou, S. J. Pantazopoulou, M. Petrou, Dimos C. Charmpis

Bibliographic record

VenueBuildings · 2021
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsBerger (Canada)York University
Fundersnot available
KeywordsFlexural strengthMaterials scienceStructural engineeringReinforcementDuctility (Earth science)Composite numberComposite materialEngineeringCreep

Abstract

fetched live from OpenAlex

With the advent of strain-hardening cementitious composites (SHCC), an opportunity for alternative jacketing solutions is presented, where the internal confinement exerted by the fibers in the material may effectively encase the structural component, thereby enhancing the strength and deformation capacity in the critical regions. This concept is explored in the present paper through testing of four pre-damaged prismatic flexural reinforced concrete members with various reinforcing deficiencies. Thin SHCC jackets constituted of a fiber-reinforced Engineered Cementitious Composite (ECC) are used to replace the damaged cover without any additional confining reinforcement. An advantage of cover replacement is that strengthening is achieved without altering the dimensions of the members. The experimental results documented the SHCC jackets’ effectiveness as a rehabilitation strategy, enhancing both the strength and ductility of the retrofitted elements and mitigating the deficiency in transverse reinforcement detailing. The strength recovery showed that the cover-thin SHCC jacket sufficed to enhance flexural and shear resistance through confinement and mobilization of stress transfer at the interface with the encased core.

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 score0.019
Threshold uncertainty score0.617

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 head0.017
GPT teacher head0.254
Teacher spread0.237 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

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