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Record W770557429

Rehabiliation Criteria for Post-Tensioned Void-Slab Bridges

2004· article· en· W770557429 on OpenAlexvenueaboutno aff
Christopher R. Scollard, F. Michael Bartlett

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2004
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsnot available
Fundersnot available
KeywordsSlabStructural engineeringShrinkageLimit state designCreepUltimate tensile strengthFlexural strengthBridge (graph theory)Void (composites)Prestressed concreteEngineeringMaterials scienceComposite material
DOInot available

Abstract

fetched live from OpenAlex

Current rehabilitation practices for aging, post-tensioned voided-slab bridges typically reduce the geometric properties of the concrete cross section and so permanently increase post-tensioning stresses, change primary and secondary prestress moments, and create new primary and secondary moments because the original concrete restrains shrinkage of new concrete. These changes affect the resistance of the rehabilitated bridge at limit states specified for new construction in the Canadian Highway Bridge Design Code (CHBDC) and may cause other limit states not currently identified in the CHBDC to govern. Rehabilitation schemes should be checked for a severiceability limit state of tensile stresses of the original concrete, which is typically not detailed to control crack widths. Ultimate limit states to check are: (1) flexural resistance over interior supports, where the total factored demand can be increased markedly by the rehabilitation; and (2) creep-initiated failure of concrete due to permanent compressive stresses. The application of these procedures is illustrated through example calculations for a typical continuous bridge.

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)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.008
GPT teacher head0.206
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 designNot applicable
Domainnot available
GenreMethods

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

Citations0
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Civil Engineering→Same topicStructural Behavior of Reinforced Concrete→French-language works237,207→