The effect of slenderness on the lateral-torsional buckling and ultimate shear capacity of plate girders
Bibliographic record
Abstract
Lateral torsional buckling and shear buckling are two of the most significant structural responses that should be considered during the design process of plate girders. Particularly the importance of lateral torsional buckling was once again witnessed during the reconstruction process of a bridge in Edmonton, Alberta, Canada when the plate girders failed due to insufficient bracing. This current study aims to acquire a better understanding of the effect of geometric parameters such as the web slenderness, flange slenderness and span-to-depth ratio on the critical buckling moment and ultimate shear strength of plate girders. To achieve this goal the critical buckling moment and ultimate shear strength of a plate girder were parametrically studied for a large number of geometries using a load case from an experimental study. The results of this parametric study clarified the effects of web slenderness, flange slenderness and span-to-depth ratio on the structural performance of a plate girder. The visualization of the results was used to identify the ranges of these geometric parameters where the structural performance is most sensitive to changing them.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".