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Record W3192783114 · doi:10.21838/uhpc.2016.124

Application of Ultra High Performance Concrete in Expediting the Replacement and Rehabilitation of Highway Bridges

2016· article· en· W3192783114 on OpenAlexaffabout
Mohammad Ataur Rahman, Tyler McQuaker

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicInfrastructure Maintenance and Monitoring
Canadian institutionsMinistry of Transportation of Ontario
Fundersnot available
KeywordsPrecast concretePierDurabilityStructural engineeringPrestressed concreteCulvertDeckEngineeringFormworkChristian ministryComputer science

Abstract

fetched live from OpenAlex

In Northwestern Ontario, the construction season is too narrow to complete the replacement and rehabilitation work of highway bridges using traditional cast-in-place concrete structural elements. In addition, the bridges built with cast in place concrete structural elements failed to exhibit durability. These cast-in-place concrete elements were disintegrating and severely scaled. To ensure long term durability and to accelerate construction of highway bridges, the Ontario Ministry of Transportation, in the Northwestern Region, started to incorporate precast prestressed concrete elements. The challenge in using these precast elements was to identify a reliable connection system to be installed among the precast elements. This paper presents examples of where Ultra High Performance Concrete (UHPC) was used for field cast longitudinal joints in precast prestressed adjacent concrete box girders and field cast joints and shear pockets in full depth precast deck panels. In addition, the details of a pier column shell and inverted T shaped pier cap built using UHPC are presented in this paper.

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 score0.172
Threshold uncertainty score0.099

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 head0.003
GPT teacher head0.193
Teacher spread0.190 · 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

Citations10
Published2016
Admission routes2
Has abstractyes

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