Parametric Effects on Evaluation of an Impact-Damaged Prestressed Concrete Bridge Girder Repaired by Externally Bonded Carbon-Fiber-Reinforced Polymer Sheets
Bibliographic record
Abstract
This paper investigates the evaluation procedure of an AASHTO Type 3 precast-prestressed girder that was extensively damaged by truck impact and then repaired using externally bonded fiber-reinforced polymer (FRP) composites. Results of this study can be applied to bridges having similar vehicle impact incidents. Parameters whose effects were investigated on the evaluation procedure include (1) the effect of horizontal resistance of elastomeric bearing supports, (2) the presence of barrier wall and sidewalk, and (3) live load distribution factors obtained from finite-element analysis (FEA) compared with the simplified method prescribed by other codes. FEA showed that support horizontal resistance has negligible effects on live load distribution factors for shear, Fv, while it has considerable effect on live load distribution factors for moment, Fm. The live load distribution factors Fm and Fv calculated from the simplified method of analysis prescribed by other codes were observed to all be greater than those obtained from FEA, showing that the approach taken by other codes is conservative for the studied bridge. The Fm and Fv of external girders obtained by FEA were as much as 30 and 40% less than those of other codes. Inclusion of barrier wall and sidewalk in the analysis showed an additional 18% reduction for Fm, with insignificant effect on Fv. The live load capacity factor as the safety indicator in the bridge evaluation was calculated analytically by the load and resistance factor method and the mean load method and then correlated with experimental findings of proof load test on the repaired girder.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".