Finite element modeling of mixed adhesive layer fracture mode for FRP web strengthening of steel bridges
Bibliographic record
Abstract
Buckling of thin-walled web plates of steel girders can be delayed using bonded glass fiber reinforced plastic (GFRP) stiffeners using the strengthening-by-stiffening (SBS) strengthening technique. The stress state between the bonded adherents (steel web and GFRP stiffener) is complex, varies greatly pre- and post-buckling, and causes adhesion- and/or cohesion-dominant failure modes. Full-scale experiments of SBS-strengthened steel beams showed a need to investigate the fracture mode of the adhesive layer. A finite element model of the full-scale beams was built to study the adhesive layer using sub-modeling techniques considering different steel plate thicknesses, epoxy types, and initial crack to determine the phase angle shift during web buckling. It was observed that the SBS failure is controlled by a mixed mode that starts initially with a phase angle of 29°; i.e., Mode II is the dominant failure mode during the linear phase. Thereafter, Mode I with a 59° phase angle became prevalent during the nonlinear phase of the behavior implying that the buckling-driven failure of web plate changes the phase angle.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".