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Record W7132896377

The Effect of Orientation and Distribution on the Material and Structural Behaviour of Ultra-High-Performance Fibre-Reinforced Concrete

2023· dissertation· W7132896377 on OpenAlexafffundabout
Andrew Benjamin Young

Bibliographic record

VenueTSpace · 2023
Typedissertation
Language
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsHudbay Minerals (Canada)
FundersGovernment of Ontario
KeywordsSlabPrecast concreteServiceability (structure)Ultimate tensile strengthFlexural strengthDeckStrength of materialsBridge deckPrestressed concrete
DOInot available

Abstract

fetched live from OpenAlex

This work continues research at the University of Toronto into a simple precast ribbed deck slab system using ultra-high-performance fibre-reinforced concrete (UHPFRC) for highway bridge overpasses. Two identical ribbed slab specimens are tested in the range of their serviceability and ultimate limit states and are tested to failure. These tests demonstrate that the proposed system is capable of supporting the required concentrated loads according to the Canadian Highway Bridge Design Code. Fibre properties including the distribution of fibres and their orientation are then examined in an effort to explain the behaviour of UHPFRC at the material and structural levels. In doing so, clear trends are identified between the fibre properties and the flexural tensile strength of UHPFRC. A general predictive equation for the tensile strength of UHPFRC is summarized and is then applied specifically for the current UHPFRC mix under study. Concrete and fibre properties as determined throughout the specimens are then related to the behaviour of the ribbed slab specimens.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.007
GPT teacher head0.263
Teacher spread0.256 · 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
Published2023
Admission routes3
Has abstractyes

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