Inhibiting Distortion-Induced Fatigue Damage in Steel Girders by Using FRP Angles
Bibliographic record
Abstract
The idea of retrofitting web stiffener ends in steel bridge girders susceptible to distortion-induced fatigue using adhesively bonded fiber-reinforced polymer (FRP) angles is introduced in this study. The proposed retrofit method is relatively cheap and easy to use and does not require deck removal or any other severe modification to the steel girder. Fatigue tests were conducted on specimens designed to model the conditions in the region between a web stiffener and a flange in a steel girder bridge. Fatigue life increases on the order of several hundred percent were achieved by implementing the proposed retrofit. The effect of the retrofit on the hot-spot stress in the critical weld detail can be seen in the experimental strain data and in a subsequent finite-element (FE) analysis of the tested specimen geometry. Further research is recommended to assess the performance of the retrofit on full-scale girders and to develop guidelines for fatigue verification and design of the FRP angle and adhesive. However, the presented research shows the potential of the proposed retrofit and the suitability of the hot-spot stress method for predicting its effectiveness.
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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 | 0.000 |
| 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) | 0.001 | 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".