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Record W4221115222 · doi:10.3390/civileng3020011

Finite-Element Analysis of Adjacent Concrete Box Girders Transversely Post-Tensioned at the Top Flanges Only

2022· article· en· W4221115222 on OpenAlexafffund
Shady N. Labib, Ehab El-Salakawy

Bibliographic record

VenueCivilEng · 2022
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversity of ManitobaTetra Tech (Canada)
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStructural engineeringPrecast concreteFinite element methodTransverse planeGirderPrestressed concreteEngineeringStructural loadParametric statisticsCrackingSlabGeotechnical engineeringMaterials scienceComposite materialMathematics

Abstract

fetched live from OpenAlex

A three-dimensional non-linear finite-element model (FEM) was constructed using a commercial software (ATENA-Studio) to investigate the transverse load distribution behavior of adjacent precast prestressed concrete box-girder bridges. An innovative connection between box girders was used, where transverse post-tensioning was applied at the top flanges only eliminating the need for intermediate transverse diaphragms. The FEM was validated in terms of deflections, strains, cracking and ultimate loads against experimental results previously reported by the authors. The validated FEM was then used to perform a parametric study investigating the influence of adding concrete topping, load location, and bridge width on the transverse load distribution behavior of the newly developed connection. The results of the FEM demonstrated the efficiency of concrete topping in limiting mid-span deflections up to 25%. Additionally, the maximum live load moment distribution factors (LLMDFs) for different load locations and bridge widths were evaluated.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.381
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.011
GPT teacher head0.213
Teacher spread0.202 · 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 teacher head, not a consensus.

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

Citations1
Published2022
Admission routes2
Has abstractyes

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