Study of Local Failure of a Multi-Plate Arch Bridge by Numerical Modeling
Bibliographic record
Abstract
An old multi-plate arch bridge (arch bridge) was built at a busy mining site for mine transportation in Western Australia in the early 1970s. After operation for more than 30 years, large deformations were noticed at the openings of two steel plate arches out the four at one side of the bridge. Site survey and inspection were carried, showing some corrosion and large deformation at the eastern end of the middle two arches of the bridge. This paper presents a simplified 2D finite element analysis (FEA) for predicting and evaluating the excessive deformation of the aged plates of the bridge. The finite element analysis results are consistent with the survey data for the deformed shape. It is found that the local failure was mainly caused by inadequate engineering design of skewed bridge a structure under the heavy traffic loads from iron ore mining trains on top of it.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".