Reinforcing preloaded steel I-beams by considering welding heat effects and geometric imperfections
Bibliographic record
Abstract
Steel I-beams are often strengthened by welding steel cover plates to the bottom flanges of the beams. However, very limited studies have been conducted on the effect of welding heat on the behaviour of I-beams reinforced while under load. This paper presents a finite element (FE) analysis-based study on the behaviour of preloaded steel I-beams reinforced with cover plates welded to the bottom flanges of beams, considering welding procedure simulation. FE analysis is conducted to study the effects of welding heat, welding sequence, and weld length on the residual welding deformation and behaviour of steel I-beams reinforced while under load. It is observed that an appropriate welding sequence and weld length can reduce the residual lateral deformations induced from welding of a reinforcing plate to the bottom flange of the preloaded I-beam and thus control the unfavourable welding effects. Based on the analyses, a welding segment length of L/9, where L is the length of the beam, is recommended for practical applications. In addition, FE analysis shows that the direction and magnitude of the initial geometrical imperfection can change the value and direction of the residual deformation resulting from welding. Furthermore, it is observed that preloading does not have any significant effect on the behaviour and ultimate capacity of the I-beam reinforced at a preload level up to 50% of the strength of the unreinforced beam. Also, when compared with the current standards AISC 360-16 and CSA S16-9, FE analysis of reinforced steel I-beams considering welding simulation shows that the current standards significantly overpredict the moment capacities of the reinforced beams when the top flange loading effect is not considered.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".