Cyclic performance of existing moment connections in steel retrofitted with a reduced beam section and bottom flange reinforcements
Bibliographic record
Abstract
This study investigated the effectiveness of retrofit methods in improving the deformation capacity of existing moment connections in composite beams. Nonlinear finite element analysis was also performed to identify the cause of the connection failure prior to testing. Tests included one conventional specimen and four retrofit specimens. Three retrofit methods were introduced: a reduced beam section (RBS) only, an RBS with bottom flange reinforcement (RBR), and an RBS-shaped bottom flange reinforcement (RSR). A composite beam performs differently than a bare steel shape because the concrete compression flange greatly increases the tensile demands on an unreinforced bottom flange. Therefore, these retrofit methods were applied only to the bottom flanges of the beam. Quasi-static loading tests were performed. The main conclusions were as follows: (i) the deformation capacity of the existing moment connections in composite beams is not sufficiently improved by RBS alone; and (ii) both the RBR and RSR details move the plastic hinge away from the face of the column and reduce stress levels in the vicinity of the beam bottom flanges, sufficiently improving the deformation capacity.Key words: composite construction, seismic performance, reduced beam section (RBS), flange reinforcement, ductility, deformation capacity.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".