Numerical analysis of RC Gerber bridge girder subjected to fatigue loading
Bibliographic record
Abstract
Numerous RC bridge girders are on service, various cracks are identified owing to exposure to millions of traffic loads during their service time. The predicted life cycles of these RC members under recurrent loading is difficult to establish. These problems are becoming worrisome since aging bridges are everywhere, hence, their immediate solution is exigent. A case of the collapse of the Gerber bridge girder (De la Concorde) in Canada has been identified and numerically analyzed. Three-dimensional failure mode of the girder subjected to high cyclic loading has been predicted under moving wheel, and fixed-point pulsating at the centre and a span away from the centre. A step-wise load application of 5 million cycles of 5 time-steps, corresponding to 0.003 seconds. Constitutive model of smear cracks in concrete using the direct path-integral approach, and mesh model of quadrilateral elements of eight nodes that captures the shear, compression and tension scenarios was adopted. The random application of cyclic loads, material properties and geometry are the contributing factors to the failure of the Gerber girder as shown by the analysis. Critical areas/sections that required attention have been identified.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".