MétaCan
Menu
Back to cohort

Bridge Deck and Guardrail Anchorage Detailing for Sustainable Construction

2014· article· en· W1996466925 on OpenAlexaff
Hossein Azimi, Khaled Sennah, Mahmoud Sayed-Ahmed, Navid Nikravan, Jacob Louie, Adam Hassaan, Nabil Al-Bayati

Bibliographic record

VenueJournal of Bridge Engineering · 2014
Typearticle
Languageen
FieldEngineering
TopicStructural Response to Dynamic Loads
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsStructural engineeringFibre-reinforced plasticDeckSpallSlabFinite element methodCantileverConcrete coverJoint (building)Materials scienceFull scaleShear (geology)Fiber-reinforced concreteEngineeringGeotechnical engineeringComposite materialReinforced concrete

Abstract

fetched live from OpenAlex

This paper investigates the use of glass fiber reinforced polymer (GFRP) bar bents as stirrups at the joint between the steel posts of a bridge guardrail system with a deck slab cantilever. In addition, GFRP bars with headed ends are used for better anchorage at the postdeck slab joint. Four full-scale cantilever post specimens were erected and tested to collapse. Two specimens were reinforced with steel bars as control specimens, whereas the other two specimens were reinforced with GFRP straight bars, bent bars, and headed bars at applicable locations. Similar failure modes were observed in all specimens because of curb external side face breakout. Failure occurred in unconfined concrete cover because of significant compressive and frictional shear stresses and also torsional effects, resulting in concrete spalling at the side face of the cantilever at the bottom of the posts. Although it is recommended to consider larger edge distance of the post to prevent premature failure in the unconfined concrete cover, the obtained experimental capacity of the postcurb region was concluded to be sufficient to resist design loads. To calculate the share of the design lateral loads received by each post, a linear finite-element analysis (FEA) and a simplified FEA were used. The analysis showed that the share of each post decreases with decrease in spacing between posts.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.005
GPT teacher head0.203
Teacher spread0.198 · 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 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

Citations6
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Bridge EngineeringSame topicStructural Response to Dynamic LoadsFrench-language works237,207