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Record W2090826289 · doi:10.1680/stbu.2009.162.1.69

Impact resistance of fibre-reinforced concrete

2009· article· en· W2090826289 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

VenueProceedings of the Institution of Civil Engineers - Structures and Buildings · 2009
Typearticle
Languageen
FieldEngineering
TopicStructural Response to Dynamic Loads
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMaterials scienceCompressive strengthToughnessComposite materialDrop (telecommunication)Engineering

Abstract

fetched live from OpenAlex

Fibre reinforcement increases the toughness of plain concrete under static compressive loading. The compressive toughness of fibre-reinforced concrete (FRC) under impact loading has not, however, previously been investigated. The current paper reviews the behaviour of high-strength fibre-reinforced concrete under uniaxial compressive impact loading. An instrumented drop weight impact machine was used to carry out compressive impact tests on various FRC systems with compressive strengths ranging from about 60 MPa to 120 MPa. The deformations of the FRC cylinders were determined using a high-speed video camera system. As expected, the compressive strength was found to increase with increasing drop height (or impact velocity). The dynamic compressive toughness was also found to increase with increasing drop height and with increasing matrix strength. It was observed that the mode of failure of the FRC was dependent upon the properties of the matrix and of the fibres, as well as on the drop height. Thus, the dynamic compressive toughness of FRC appeared to be dependent on the constitutive behaviour of the matrix, the fibre type and volume, the impact velocity and the mode of failure.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.674

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)0.0000.000

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 head0.004
GPT teacher head0.208
Teacher spread0.204 · 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