MétaCan
Menu
Back to cohort
Record W4225153321 · doi:10.11159/icsect22.148

Experimental Investigation on the Impact of Longitudinal Rebar Ratio on the Cracking Characteristics of R/C Components

2022· article· en· W4225153321 on OpenAlexvenueno aff
Theodoros Chrysanidis

Bibliographic record

VenueProceedings of the World Congress on Civil, Structural, and Environmental Engineering · 2022
Typearticle
Languageen
FieldDecision Sciences
TopicProbabilistic and Robust Engineering Design
Canadian institutionsnot available
Fundersnot available
KeywordsCrackingRebarMaterials scienceStructural engineeringComposite materialForensic engineeringEngineering

Abstract

fetched live from OpenAlex

Cracking phenomenon in reinforced concrete members has troubled researchers and engineers worldwide due to the many mechanical parameters affecting this phenomenon. One such mechanical parameter is the longitudinal reinforcement ratio used for the detailing of structural components in reinforced concrete structures. Although, the percentage of rebar content has been studied, it is the first time that cracking behaviour is studied using varying ratios of rebars strained under a uniaxial tensile loading till a high degree of elongation found only at buildings sustained severe earthquake actions. This research is experimental. Four test specimens in the form of R/C ties are used and strained using a monotonic uniaxial tensile loading simulating the tensile type of loading during the first cycle of dynamic seismic action. All specimens are strained till an elongation degree equal to 30. The ratios used for the reinforcement of column specimens take values equal to 1.79%, 4.02%, 5.47% and 7.15%. Significant conclusions are reached concerning cracking behaviour for different longitudinal ratios, e.g., number of cracks, crack width, etc.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score0.464

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.043
GPT teacher head0.257
Teacher spread0.214 · 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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the World Congress on Civil, Structural, and Environmental EngineeringSame topicProbabilistic and Robust Engineering DesignFrench-language works237,207