Design and construction of SFRC bridge decks : building on past experiences and recent developments
Bibliographic record
Abstract
Using steel fibres for primary reinforcement in structural elements requires design methods based on meaningful material properties and good construction practices. In recent years, worldwide research efforts have brought the knowledge on these two aspects to a level which allows steel fibres to be considered for primary reinforcement for structural applications. Experiences in Canada have shown that using steel fibres in bridge deck design is a sound and economical solution that can solve several issues related to conventional reinforced concrete (R/C) design. This paper presents the proposed solution for bridge deck design in which SFRC is considered for primary reinforcement. It describes the concept and the main steps of the research program that supported its development. The performance of the proposed approach is shown in service and ultimate conditions. The design of a real bridge deck with reduced reinforcement illustrates the application of a proposed simplified design method. Recommendations for designing bridge elements made with SFRC are suggested.fr\ndc.identifier.uri http://hdl.handle.net/20.500.11794/40173\n
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".