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Record W3110852367 · doi:10.1139/cjce-2019-0592

Tensile behaviour of ultra-high-performance steel fiber reinforced concrete

2020· article· en· W3110852367 on OpenAlexaffvenue
Yuechen Yang, Mohammed Ismail, S. J. Pantazopoulou, Dan Palermo

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsYork University
Fundersnot available
KeywordsFlexural strengthUltimate tensile strengthMaterials scienceComposite materialDuctility (Earth science)Compressive strengthBendingFiber-reinforced concreteBrittlenessFiberStructural engineeringThree point flexural testEngineeringCreep

Abstract

fetched live from OpenAlex

Recent developments in the area of ultra-high-performance steel fiber reinforced concrete (UHP-SFRC) has enabled a reduction in the use of steel reinforcement and has led to enhanced ductility and toughness of structural components owing to its resilient tensile behaviour. This paper presents the results of an experimental study that was conducted to investigate the tensile behaviour of UHP-SFRC. Four commercial mixes and two in-house mixes were evaluated using the procedures prescribed in the 2019 edition of Annex U of CSA-A23.1 and in Annex 8.1 of CSA-S6 2018. The tensile strength of UHP-SFRC was quantified and correlated through the direct tension test, splitting test, inverse analysis of four-point bending tests using either code expressions or nonlinear finite element analysis, and a calibrated empirical expression that links this property to the cylinder compressive strength. In addition, the effect of important parameters on flexural strength including casting methodology, volumetric ratio of steel fibers, and aspect ratio (shear span to depth ratio) of bending prisms have been assessed. The casting methodology affected the fiber distribution, an attribute that directly relates to flexural strength. Prisms containing 1% steel fibers by unit volume failed in a relatively brittle manner and possessed less flexural strength than the prisms containing 2% steel fibers. Prisms with an aspect ratio of 1 tended to develop greater flexural strength than the prisms tested with an aspect ratio of 2. The tensile strength obtained from inverse analysis is generally greater than the strength obtained from the direct tension test, the finite element analysis, and the calibrated empirical expression. Furthermore, it was determined that tensile strength obtained from the splitting test should be multiplied by a correction factor of ≈1/π, to match the strength obtained from the direct tension test. The majority of the mixes tested exhibited a tension hardening behaviour with a hardening ratio greater than 1.1 and an ultimate tensile strain greater than 0.001.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.531
Threshold uncertainty score0.951

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)0.0010.000

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 head0.010
GPT teacher head0.179
Teacher spread0.168 · 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

Citations7
Published2020
Admission routes2
Has abstractyes

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