Corrosion-Fatigue Strain-Life Model for Steel Bridge Girders under Various Weathering Conditions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Corrosion of existing infrastructure, such as steel bridges, would significantly reduce its anticipated fatigue life. There are very few corrosion-fatigue models that address civil engineering applications. To account for corrosion in the fatigue life prediction of steel bridges, a new fatigue strain-life model based on the Smith-Watson-Topper model is proposed. The proposed model provides the fatigue life predictions in the form of ranges with a minimum and a maximum value. The model takes into account the corrosivity of the environment, the stress level, and the corrosive behavior of the material used. The resulting fatigue life predictions using the proposed model matched well with the experimental results reported in the literature for 24 steel beams that were subjected to various fatigue and weathering conditions. The analytical predictions show that the proposed model is accurate, simple, and practical and can be easily calibrated for different materials.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it