MétaCan
Menu
← Back to cohort
Record W7162822423

ShearCapacity ofBasaltFiberReinforcedPolymerReinforcedRecycledConcreteDeepBeamWithoutWebReinforcement

2015· article· zh· W7162822423 on OpenAlexaboutno aff
刘华新, 柳根金, 王学志, 孙英明

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2015
Typearticle
Languagezh
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsnot available
Fundersnot available
KeywordsShear (geology)Compressive strengthFailure mode and effects analysisReinforcementRebarShearing (physics)Shear strength (soil)T-beam
DOInot available

Abstract

fetched live from OpenAlex

Abstract:In order to study the shear capacity of basalt fiber reinforced polymer reinforced recycled concrete deep beam without web reinforcement,9 deep beams under 4 point bending test were conducted.The failure process and failure mode of the tested beam were analyzed.The relationship of shear strength among the shear span ratio,reinforcement ratio of BFRP rebar and the compressive strength of recycled concrete was also discussed,respectively.A formula based on Canadian specification and data fitting for calculating the shearing capacity of the specimens was proposed.Results showed that the main failure mode of BFRP reinforced recycled concrete deep beam without web reinforcement was the shear failure and with the increase of shear span ratio,the shear failure transforms to flexural-shear failure.The shear capacity of experimental beams decreased with the increase of the shear span ratio,while increased with the increase of the reinforcement ratio of BFRP reinforcement and compressive strength of recycled concrete.The predicted results of the adopted calculation model fitted well with the test results and had a certain degree of safety.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.238
GPT teacher head0.502
Teacher spread0.263 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueDOAJ (DOAJ: Directory of Open Access Journals)→Same topicStructural Behavior of Reinforced Concrete→French-language works237,207→