Load Distribution Factors in Straight and Skew Concrete I-Girder Bridges
Bibliographic record
Abstract
Skew bridges in modern highways have become increasingly popular for economic and aesthetic considerations. The current Canadian Highway Bridge Design Code (CHBDC) specifies skew factor equation for shear at the obtuse corner for braced steel I-girder bridges. However, skew factors for concrete I-girder bridges for girder moment and shear at obtuse and acute corners as well as middle supports due to CHBDC truck loading are yet unavailable. Also, CHBDC load distribution factor equations for moment and shear in straight bridges do not include the presence of concrete traffic barriers and intermediate diaphragms as integral parts of highway bridges. Moreover, literature review revealed that CHBDC overestimates the moment and shear at fatigue limit state design of slab-on-girder bridges. Despite the availability of computer software for bridge analysis, designers prefer simplified analysis methods to reduce the time and cost spent in the design. A practical-design-oriented parametric study was conducted, using the finite element modelling to address the shortcomings and gaps found in CHBDC. The first study included the analysis of straight and skew concrete I-girder bridges under dead load, while the second study included the analysis of such bridges under CHBDC truck loading conditions. The third study included the effect of concrete barrier stiffness and concrete intermediate diaphragms on the moment and shear distribution factors for this type of bridge. Different bridge configurations were considered to cover key parameters such as span length, skew angle, number of girders and girder spacing. The obtained results were compared with those available in CHDBC, AASHTO LRFD Bridge Design Specifications and previous research related to slab-on-girder bridges. Using the data generated from the parametric study, sets of empirical equations for moment and shear distribution factors for the studied bridge configurations under dead and live load were deduced to design such bridge types more reliably and economically. Results show that inclusion of intermediate diaphragms and concrete barriers built integrally with the deck slab generally affect bridge performance. This conclusion can be used to evaluate existing bridges since any additional girder strength would decide on keeping the bridge in service or address its structural deficiency.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".