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Record W7054925158

Behaviour of ultra-high performance concrete as a joint-fill material for precast bridge deck panels subjected to negative bending

2015· dissertation· en· W7054925158 on OpenAlexfundno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2015
Typedissertation
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Memphis
KeywordsDeckPrecast concreteBridge deckTransverse planeJoint (building)Bending momentShear (geology)Bending
DOInot available

Abstract

fetched live from OpenAlex

This thesis investigates the behaviour of UHPC as a fill material for precast deck panels subjected to negative bending. Two full-scale test specimens were constructed. The transverse joints between the panels, the shear pockets, and the deck haunches were all filled with UHPC. A total of four tests were performed including two static tests to failure and two fatigue tests, one of which was performed to failure. Testing consisted of a loading apparatus acting upwards on the deck soffit in an attempt to impose tensile stresses across the transverse joints, representing the conditions that a transverse joint in the negative moment region of a continuous bridge deck would experience. It was concluded that the transverse UHPC joint performed satisfactorily by transferring bending stresses and shear stresses across the joint from one panel to the adjacent panel. Overall, the test specimens displayed performance levels expected from conventional cast-in-place concrete deck alternatives.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.021
GPT teacher head0.220
Teacher spread0.199 · 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 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

Citations0
Published2015
Admission routes1
Has abstractyes

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