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Record W4405182146 · doi:10.3390/constrmater4040043

Effectiveness of UHPC Jackets in Pier Retrofitting for Lateral Load Resistance

2024· article· en· W4405182146 on OpenAlexaff
Zoi G. Ralli, S. J. Pantazopoulou

Bibliographic record

VenueConstruction Materials · 2024
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsYork UniversityCIMA+ (Canada)
Fundersnot available
KeywordsRetrofittingPierStructural engineeringDurabilityDuctility (Earth science)EngineeringStructural loadMaterials scienceComposite materialCreep

Abstract

fetched live from OpenAlex

Ultra-high-performance concrete (UHPC) is a recently emerged material with exceptional durability and ductility. While widely used in bridge retrofitting, particularly to replace expansion joints and deck overlays, UHPC has seen limited use in jacketing piers for the improvement of lateral load resistance. It presents superior mechanical properties and deformation resilience, enabled by the distributed fibers and the dense microstructure, providing corrosion resistance and a maintenance-free service life. The significant tensile strength and ductility establish UHPC as an attractive resilient jacketing system for structural members. The experimental literature documents the effectiveness of this solution in enhancing the strength and ductility of the retrofitted member, whereas premature modes of failure (i.e., lap splices and shear failure in lightly reinforced piers) are moderated. A comprehensive database of tests on UHPC-jacketed piers under lateral loads was compiled for the development of practical guidelines. Various UHPC jacket configurations were evaluated, and detailed procedures were developed for their implementation in bridge pier retrofitting. These procedures include constitutive models for UHPC, confined concrete, and the strengthening of lap splices, flexure, and shear resistance. The results are supported by the database, providing a solid foundation for the broader application of UHPC in improving the lateral load resistance of bridge piers.

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 score0.005
Threshold uncertainty score0.569

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 head0.008
GPT teacher head0.242
Teacher spread0.233 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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