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Mechanical Properties of Fiber-Reinforced Concrete Made with Basalt Filament Fibers

2015· article· en· W2021157587 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 Materials in Civil Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsBasalt fiberMaterials scienceFiberComposite materialCompressive strengthModulusFiber-reinforced concreteBasaltGlass fiberCastingYoung's modulusProtein filamentGeology

Abstract

fetched live from OpenAlex

Fiber-reinforced concrete (FRC) has become a viable new material used in various constructions such as building pavements, large industrial floors, and runways. In this research, basalt chopped fibers in filament form were used to develop an FRC material called basalt fiber-reinforced concrete (BFRC) to study the possible improvement in the 28-day compressive strength and modulus of rupture, though the latter one is more important for the construction of pavements, industrial floors, and runways. The basalt fiber specimens were cast using basalt filament fibers of three different lengths and three different amounts. Clumping of fibers at high fiber amounts caused mixing and casting problems. These problems become even more severe when long fibers are used at the high fiber dosage amount. The results indicated that 36-mm-long chopped basalt filament fiber and a fiber amount of 8 kg/m3 are optimum for achieving high performance in both the compressive strength and modulus of rupture. This paper discusses the test matrix and test results obtained from various BFRC and plain concrete specimens.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.219
Threshold uncertainty score0.924

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.021
GPT teacher head0.208
Teacher spread0.187 · 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