Simplified flexural design approach of ultra high performance concrete bridge girders
Bibliographic record
Abstract
Ultra high performance fibre-reinforced concrete (UHPFRC) is a newly developed concrete material that provides very high strength and very low permeability. The renewal of aging highway bridges and the construction of new bridges using ultra high performance concrete can yield structurally efficient long life bridges, which will require minimum maintenance and low life cycle costs. A simplified flexural design approach of UHPFRC girders and a comparative study of the structural efficiency of UHPFRC and conventional precast prestressed concrete girder bridges are presented in this paper, and to compare its structural efficiency to conventional slab-on- concrete girder bridges. The proposed design approach is consistent with the Canadian Bridge Design Code (CHBDC) and is based on the state-of-the-art design recommendations for UHPFRC and checked using a three-dimensional finite element analysis. It is found that the use of UHPFRC in precast/prestressed concrete girders can yield a reduction of up to two girder lines with smaller girder sizes when compared to conventional concrete girders bridge. UHPC results in a significant reduction in concrete volume that can reach 40%, which turn leads to a more efficient design of the superstructure and a significant reduction in the dead loads on the substructure, which is very important for the safety of aging bridge substructures.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".