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Record W4317401450 · doi:10.18280/mmep.090613

A Study of the Structural Behavior of Recycled-Concrete Haunched Beams with Web Opening

2022· article· en· W4317401450 on OpenAlexvenueno aff
Fakhriya Obead Mosa, Abdulnasser M. Abbas

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2022
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsnot available
Fundersnot available
KeywordsBeam (structure)Materials scienceSquare (algebra)Structural engineeringAggregate (composite)Composite materialRange (aeronautics)MathematicsGeometryEngineering

Abstract

fetched live from OpenAlex

The structural behavior of Reinforced Concrete Haunched Beams (RCHBs) was investigated in this study. One prismatic control beam and fourteen Haunched Beams (HBs) were used in the experimental test and numerical analysis. The variables considered are Recycled Concrete Aggregate (RCA) ratio which is taken as 0, 30 %, and 60 %, opening shape (square and circular with the same area of 4560 mm2), and haunch angle (α) of 6.34° and 9.46°. The samples of dimensions (1750x200x300) mm were tested under a two-point load. The samples were simulated numerically using the Abaqus/CAE tool. The experimental outcomes show that using 30% RCA decreased the resistance by 8.24% - 26.45% compared with the control sample. While at 60% RCA, the resistance decreased by 16.35% - 34.71%. HBs with α=6.34° give a strength quite close to the control beam (PN) by 1.93%, while α=9.46° decreases the strength by 12.94% compared with PN. Compared with the solid beam, square holes in HBs provide a strength reduction range of 5.83% - 18.79% for α=6.34° and α=9.46°, respectively. The beams with circular apertures have a resistance decrease of about 3.43% - 14.70%, which corresponds to α=6.34° and α=9.46°. The numerical findings were 8.41% of the experimental data.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.016
GPT teacher head0.193
Teacher spread0.177 · 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
Published2022
Admission routes1
Has abstractyes

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