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Record W2889857621 · doi:10.3390/jcs2030055

An Experimental Investigation of FRCC Shear Walls Reinforced with Steel and GFRP Bars

2018· article· en· W2889857621 on OpenAlexaff
Mohammad Javad Tolou Kian, Sina Ghazizadeh, Carlos A. Cruz Noguez

Bibliographic record

VenueJournal of Composites Science · 2018
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDissipationMaterials scienceFibre-reinforced plasticStiffnessStructural engineeringShear wallResidualShear (geology)Composite materialCementitiousGeotechnical engineeringCementGeologyEngineering

Abstract

fetched live from OpenAlex

Contemporary structures can resist earthquakes as they deform and dissipate energy. However, during strong ground motions, these structures can sustain significant concrete damage and overall permanent deformations. Therefore, it is of great benefit if earthquake-resisting structures can deform and dissipate energy, and yet sustain mitigated damage. This paper illustrates the findings of an experimental study focused on the mitigation of damage and reduction of residual displacements in reinforced concrete (RC) shear walls. In this study, the cyclic properties of two innovative shear walls—a slender and a squat wall—which were cast with fiber-reinforced cementitious composites and reinforced with steel and glass fiber reinforced polymer bars are investigated. Then, the improvements of the innovative specimens with respect to two conventional RC shear walls are discussed in terms of damage propagation, self-centering, stiffness retention and energy dissipation. As the experiments showed, the innovative walls sustained mitigated concrete damage and less residual drift ratios while illustrating significant stiffness and energy dissipation capacities.

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.242
Teacher spread0.232 · 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

Citations11
Published2018
Admission routes1
Has abstractyes

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Same venueJournal of Composites ScienceSame topicStructural Behavior of Reinforced ConcreteFrench-language works237,207