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Record W3216108498 · doi:10.32920/ryerson.14661405.v1

Strain rate effects on ultra high performance fiber reinforced concrete (UHP-FRC) with various fiber contents

2021· preprint· en· W3216108498 on OpenAlexaff
Sayed-Mohammad Banitabaei-Koupaei

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMaterials Science
TopicHigh-Velocity Impact and Material Behavior
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsDuctility (Earth science)Materials scienceFlexural strengthStrain rateDurabilityCompression (physics)Fiber-reinforced concreteFiberComposite materialTension (geology)Structural engineeringEngineering

Abstract

fetched live from OpenAlex

Ultra High Performance Fiber Reinforced Concrete (UHP-FRC) was introduced in the mid-1990s and has made striking advances in recent years. Ductal® is a UHP-FRC technology that offers a unique combination of characteristics including but, not limited to ductility, strength and durability, while providing highly moldable products with quality surfaces. Compressive strengths, and equivalent flexural strengths reach up to 200 and 40 MPa, respectively. UHP-FRC also shows an outstanding performance under dynamic loading in structures subjected to extreme loading conditions such as impact, earthquake and blast. Moreover, UHP-FRC indicates an optimized combination of properties for a specific application. Three series of tests including compression, indirect tension, and flexure were conducted under various strain rates from quasi-static to dynamic loading with low strain rates. The objective of this project is to enhance knowledge of strain rate effects on UHP-FRC with various fiber contents and to report Dynamic Increase Factor (DIF).

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.026
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.002

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 head0.016
GPT teacher head0.245
Teacher spread0.229 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2021
Admission routes1
Has abstractyes

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