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Record W2039417321 · doi:10.1520/jte102386

Size Effects in Flexural Toughness of Fiber Reinforced Concrete

2010· article· en· W2039417321 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Testing and Evaluation · 2010
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFlexural strengthMaterials scienceComposite materialToughnessFiber-reinforced concreteFiberFracture toughness

Abstract

fetched live from OpenAlex

Abstract The influence of specimen size on measured flexural toughness of fiber reinforced concrete (FRC) remains largely unknown. Towards this end, an experimental program was carried out where flexural toughness tests were performed on specimens of two different sizes using ASTM C1609/C1609M-07 test procedure. Two specimen sizes of 100×100×350 mm3 and 150×150×500 mm3 were tested. A hybrid polymeric fiber at three fiber dosage rates of 3.0, 4.5, and 6.0 kg/m3 was investigated. Results indicate that the specimen size affects not only the toughness properties but also the variability in data as quantified by the coefficient of variation (COV). Size effect was more pronounced in the early part of the load-deflection curve and decreased with an increase in the fiber volume fraction. At a given fiber volume fraction, the COV, moduli of rupture, and post-crack residual strengths were all higher for the specimens of smaller size. Finally, the small size specimens showed a greater deflection hardening than the large size specimens. The last conclusion is significant in that deflection hardening is now often cited as the required performance characteristic of high performance FRC, and this property may depend more on the size of the specimens than on the composite itself.

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.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.503
Threshold uncertainty score0.441

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
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 head0.024
GPT teacher head0.281
Teacher spread0.257 · 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