Curvature limits for composite steel box girder bridges
Bibliographic record
Abstract
Composite concrete deck over steel box girder bridges are used in curved alignments as an economical solution because of their high flexural and torsional strength. Curvature effects on bending, shear and deflection may be ignored for bridges with light curvature. The Canadian highway bridge design code (CHBDC), the American Association for State Highway and Transportation Officials (Aashto) guide specifications for horizontally curved bridges and Aashto LRFD bridge design specifications specify limitations to treat a horizontally curved bridge as a straight one in structural design for only girder bending moment. Also, CHBDC curvature limitation does not differentiate between open and closed bridge cross-sections. The curvature limitation of the Aashto guide does not consider the effect of bridge width, leading to an inaccurate estimate of the structural response. To investigate the accuracy of these curvature limitations, a series of horizontally curved composite steel box girder bridges were analysed using finite-element modelling. The key parameters considered in this study were the degree of curvature and bridge span, width and continuity. Longitudinal bending stresses, support reactions, deflections and frequencies were determined and compared with those obtained for straight bridges of identical configurations. Results showed that code curvature limits were unsafe and needed to be updated. Empirical expressions were developed to determine curvature limits more accurately and reliably.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".