Behaviour of steel I-beams reinforced with welded cover plates in the negative bending moment region
Bibliographic record
Abstract
Steel I-beam bridges often require strengthening due to changes in loading requirements or to increase the design life of the bridges. As the bottom flange of the I-beam is accessible most of the time, an economical option is to weld a steel cover plate to the bottom flange of the existing beam. In a continuous bridge, the bottom flange of the I-beam at the pier location is in compression. This paper presents a numerical study on preloaded steel I-beams reinforced with steel cover plates welded at the compression flanges of the beams. A series of steel I-beams are analyzed to study the effects of different parameters, such as preload level, cover plate thickness, unbraced length of the beam, material grade difference between the original I-beam and the reinforcing plate, length of the cover plate, on the behaviour of I-beams strengthened with welded cover plates at the compression flanges. Three-point loading condition was considered to simulate continuous span bridges. Finite element (FE) analyses show that adding cover plates to adjacent spans of interior support increases the ultimate capacity and the stiffness of the beam, and there is no need to extend the cover plate beyond the zero-bending moment location. Also, the reinforcement can prevent the beam from lateral torsional buckling failure. Furthermore, the preloading level has an insignificant effect, less than 3% for a preload level up to 60% of the base beam capacity, on the capacity of the steel I-beams reinforced with welded cover plates in the negative moment region. FE analysis also shows that AASHTO can reasonably predict the flexural capacities of I-beams reinforced with welded cover plates in the negative moment region.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".