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Repair of GFRP-Reinforced Concrete Bridge Barriers

2014· article· en· W2006986487 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Bridge Engineering · 2014
Typearticle
Languageen
FieldEngineering
TopicTransportation Safety and Impact Analysis
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsFibre-reinforced plasticBridge (graph theory)Structural engineeringMaterials scienceForensic engineeringEngineering

Abstract

fetched live from OpenAlex

The Canadian highway bridge design code provides dimensions and reinforcement detailing of concrete bridge barriers reinforced with glass fiber–reinforced polymer (GFRP) bars. However, there are no guidelines on the repair of such concrete elements in case of damage caused by vehicle accidents. Therefore, the main objective of this study is to evaluate the feasibility and efficiency of available techniques to repair damaged GFRP-RC bridge barriers. To fulfill this objective, three full-scale, 6.0-m-long, PL-2 concrete bridge barriers, totally reinforced with GFRP bars, were constructed and tested under an equivalent static load, simulating a vehicle crash test. Two different repair techniques, planting and near-surface-mounted (NSM) fiber-reinforced polymer (FRP) bars, were used to repair the damaged barriers. Repaired barriers were retested under similar conditions to evaluate the effectiveness of the repair techniques. It is concluded that the repaired GFRP-RC bridge barriers achieved similar capacities to their counterpart control (undamaged) barriers.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.332
Threshold uncertainty score0.658

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 head0.006
GPT teacher head0.198
Teacher spread0.192 · 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