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Curvature Limitations for Slab-on-I-Girder Bridges

2014· article· en· W2000137043 on OpenAlexafffund
Imad Eldin Khalafalla, Khaled Sennah

Bibliographic record

VenueJournal of Bridge Engineering · 2014
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStructural engineeringCurvatureGirderSlabFinite element methodParametric statisticsBridge (graph theory)EngineeringBendingGeometryMathematics

Abstract

fetched live from OpenAlex

In recent years, horizontally curved bridges have been widely used in congested urban areas, where multilevel interchange structures are necessary for modern highways. In bridges with light curvature, the curvature effects on bending, shear, and torsional stresses may be ignored if they are within an acceptable range. Treating horizontally curved bridges as straight bridges with certain limitations is one of the methods to simplify the design procedure. Bridge design specifications and codes have specified certain limitations to treat horizontally curved bridges as straight bridges. However, these limitations do not differentiate between bridge cross section configurations, in addition to being inaccurate in estimating the structural response. Moreover, these specifications were developed primarily for the calculation of girder bending moments. To investigate the accuracy of these limitations, a series of horizontally curved, braced concrete slab-over steel I-girder and slab-on-concrete I-girder bridges were analyzed, using three-dimensional finite-element modeling, to investigate their behavior under dead loading. The major internal forces developed in the members were determined, namely, girder longitudinal bending stresses, vertical deflections, vertical support reactions, and bridge fundamental flexural frequencies for different degrees of curvature, span length, bridge width, and span continuity. Empirical equations for these straining actions were developed as a function of those for straight bridges. The stipulations made in bridge codes for treating a curved bridge as a straight bridge were then correlated with the obtained values from the finite-element modeling. Results proved that such code limitations were unsafe. Based on the data generated from this parametric study, sets of empirical expressions were developed to determine such limitations more accurately and reliably.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.018
GPT teacher head0.218
Teacher spread0.200 · 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 designNot applicable
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

Citations11
Published2014
Admission routes2
Has abstractyes

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