Composite steel-free deck bridges: Numerical modelling and pilot parametric study
Bibliographic record
Abstract
During the past decade, composite steel-free deck bridges came to reality in Canada through the construction of five bridges. The new structural system enables the construction of a concrete deck that is totally devoid of all internal steel reinforcement. Traditionally, reinforced concrete bridge decks are designed to sustain loads in flexure. The steel-free deck bridge system develops internal compressive forces "internal arching," which leads to failure by punching shear at substantially higher loads than the flexural design load. The fibre-reinforced concrete deck is usually attached to the steel girders through flexible shear connectors. These steel girders are transversely tied together by steel straps and cross frames. In this paper, the concept of the new bridge system is briefly discussed. The generations of the deck slabs are introduced. Brief outlines of the bridges built to date with this new technology are presented. A three-dimensional finite element model is then proposed to study the behaviour of the main structural component of the new system. The model is verified against previous experimental results and is used to perform a parametric study on some aspects which are thought to significantly affect the behaviour of the new steel-free deck bridge system.Key words: bridges, composite girders, finite element method, steel-free deck, steel straps.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".