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Record W2028373635 · doi:10.3141/2028-13

Alternative Reinforcing Details in Dapped Ends of Precast Concrete Bridge Girders

2007· article· en· W2028373635 on OpenAlexafffund
Rainer Herzinger, Mamdouh El‐Badry

Bibliographic record

VenueTransportation Research Record Journal of the Transportation Research Board · 2007
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaCement Association of Canada
KeywordsPrecast concreteGirderStructural engineeringReinforcementDiagonalEngineeringShear (geology)BendingMaterials scienceMathematicsComposite material

Abstract

fetched live from OpenAlex

The ends of precast girders often have a reduced depth over short lengths in the form of dapped ends. Girders with dapped ends normally are used in parking structures and pedestrian bridges. Because of the reduced depth at the girder ends, the shear stresses are high, and, therefore, the design of dapped ends requires special consideration. Dapped ends typically are reinforced with conventional stirrups and longitudinal reinforcing bars, which require hooks and bends and even welded plates to ensure sufficient anchorage. The efficiency of use of studs with single or double heads for reinforcing dapped ends is investigated. Strut-and-tie models are used to develop different layouts of the reinforcement. Two analytical methods based on the shear friction and diagonal bending theories are used to determine the location of the critical crack at failure and to examine the effectiveness of the reinforcement layouts. An experimental program is conducted on a series of dapped-end beams to corroborate the analytical study. The use of studs in dapped-end zones is shown to provide an efficient and reliable solution that prevents premature failure caused by inadequate anchorage of conventional reinforcement.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.400
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.003
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 head0.070
GPT teacher head0.360
Teacher spread0.289 · 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 designObservational
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

Citations13
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueTransportation Research Record Journal of the Transportation Research BoardSame topicStructural Behavior of Reinforced ConcreteFrench-language works237,207