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Record W2749338758 · doi:10.1061/40700(2004)38

The Development of Revised Effective Slab Width Criteria for Steel-Concrete Composite Bridges

2004· article· en· W2749338758 on OpenAlexaboutno aff
Methee Chiewanichakorn, Il-Sang Ahn, Amjad J. Aref, S. S. Chen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsSlabStructural engineeringGirderDeflection (physics)Finite element methodEurocodeLimit state designEngineeringMaterials sciencePhysics

Abstract

fetched live from OpenAlex

In design and analysis of steel-concrete composite girders, values of maximum deflection, stress and strength are typically obtained from simple beam theory by utilizing the effective slab width concept. Shear-lag effects are indirectly accounted for, by replacing the actual slab width by an appropriate reduced "effective" width. In this research, a new effective slab width definition is introduced. A three-dimensional non-linear finite element analysis is employed to evaluate and determine the actual effective slab width of steel-composite composite bridge girders. The resulting effective width is believed to be larger than the ones provided by many design specifications, both nationally and internationally. The revised effective slab width criteria based on the proposed effective slab width definition is compared with other design specifications, specifically AASHTO LRFD, British, Canadian, Japanese, and Eurocode design specifications. The comparative studies include the comparisons of service limit state, positive versus negative moment regions, and interior versus exterior girders of a multiple span continuous configuration.

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 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 score0.020
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

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

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 head0.009
GPT teacher head0.245
Teacher spread0.236 · 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.

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

Citations1
Published2004
Admission routes1
Has abstractyes

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