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Record W2798202516 · doi:10.1177/0361198118755665

First Application of UHPC Bridge Deck Overlay in North America

2018· article· en· W2798202516 on OpenAlexaff
Sri Sritharan, Gaston Doiron, Dean Bierwagen, Brian Keierleber, Ahmad Abu-Hawash

Bibliographic record

VenueTransportation Research Record Journal of the Transportation Research Board · 2018
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsLafargeHolcim (Canada)
Fundersnot available
KeywordsOverlayBridge deckDurabilityDeckCrackingSlumpingEngineeringStructural engineeringBridge (graph theory)Computer scienceCivil engineeringGeologyMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Deterioration of existing bridge decks, which usually originates with the deck cracking on the top surface, is a common problem in North America. It causes frequent repair of the decks to limit further damage resulting from water/chloride ingress. Superior engineering and durability properties facilitate the use of ultra-high performance concrete (UHPC) as an attractive alternative for a deck overlay, minimizing both deck deterioration and maintenance costs. Recently developed UHPC thixotropic mix designs, which are different from commonly used self-leveling UHPC, enable UHPC overlay to be used on decks with slopes and meet specific crowning requirements. The use of a UHPC thixotropic mix design with 3.25% of steel fibers was successfully evaluated under laboratory conditions by applying it on sloping deck surfaces with appropriate roughness between the normal concrete (NC) and UHPC. The feasibility of applying this technology in the field was then investigated on a small bridge for the first time in North America in May 2016. This paper presents the details about the laboratory evaluation, field implementation of UHPC overlay, and lessons learned from this first UHPC overlay project in North America.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.962

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.056
GPT teacher head0.347
Teacher spread0.292 · 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 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

Citations41
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueTransportation Research Record Journal of the Transportation Research BoardSame topicInnovative concrete reinforcement materialsFrench-language works237,207