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Record W4240684550 · doi:10.32920/ryerson.14647941

Load distribution in concrete solid slab bridges

2021· preprint· en· W4240684550 on OpenAlexaffabout
Muhammad Ishtiaq

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsSlabStructural engineeringOrthotropic materialDeckBending momentFinite element methodParametric statisticsShear (geology)Moment distribution methodEngineeringMaterials scienceMathematicsComposite material

Abstract

fetched live from OpenAlex

Canadian Highway Bridge Design Code (CHBDC) specifies empirical equations for the moment and shear distribution factors for selected bridge configurations. These empirical equations were based on the orthotropic plate theory with equivalent slab bending and torsional rigidity. Also, they were based on analysis procedure and CHBDC truck loading condition slightly different from those specified in the current CHBDC code of 2006. In this study, a parametric study was conducted, using the finite-element modeling to determine the moment and shear distribution factors for solid slab bridges subjected to CHBDC truck loading. Shell elements were used to model the bridge deck slab supported over bearings on each side of the bridge at 1.2 m spacing. The results from the parametric study were correlated to those available in the CHBDC code. Results show considerable difference in FEA results and CHBDS equations, especially for shear distribution factors. This project provides research results that can be used further to develop more reliable expressions for moment and shear distribution factors for solid slab bridges.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.244
Teacher spread0.232 · 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 designSimulation or modeling
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
Published2021
Admission routes2
Has abstractyes

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