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Record W2808161558 · doi:10.20481/kscdp.2018.5.2.51

Shear Capacity of Reinforced Lightweight Concrete Beams: Concrete Recipes and Experimental Results

2018· article· en· W2808161558 on OpenAlexaboutno aff
Min Ook Kim, Nam Kon Lee, Boreum Won, Gi Joon Park

Bibliographic record

VenueKorea Society of Coastal Disaster Prevention · 2018
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsnot available
Fundersnot available
KeywordsCompressive strengthAggregate (composite)Reinforced concreteShear (geology)Structural engineeringMaterials scienceShear strength (soil)Beam (structure)PorosityGeotechnical engineeringComposite materialEnvironmental scienceEngineering

Abstract

fetched live from OpenAlex

British Standard 8110, Canadian Standards Association A23.3-04, and American Concrete Institute 318-11 suggest the equation to estimate the shear strength of reinforced lightweight concrete beam based on the 28-days compressive strength. However, the compressive strength of LWC can be variable depend on the type of lightweight aggregate selected and this can cause problems in the accurate prediction of shear strength. LWC generally showed the lower strength compared to that of conventional concrete due to the high internal porosity of lightweight aggregate. Understanding the effect of different aggregate type on the shear capacity of reinforced LWC beams is important to improve existing standards and better application of LWC in actual structures. Experimental studies were conducted to investigate the effect of aggregate type on the shear capacity of reinforced all lightweight concrete beams. Total 12 RC beams with three different coarse aggregates were prepared and comparisons were made with existing design guidelines. In sum, some important suggestions were made for the better use of LWC in actual concrete structures.

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 score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.019
GPT teacher head0.247
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; 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
Published2018
Admission routes1
Has abstractyes

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Same venueKorea Society of Coastal Disaster PreventionSame topicInnovative concrete reinforcement materialsFrench-language works237,207