Behavior and Design of Block Shear Strength of Beam-End Bolted Connections Using Cold-Formed Steel Channels
Bibliographic record
Abstract
The block shear strengths of simple cold-formed steel bolted connections for members in tension have been thoroughly investigated, whereas the combined effects of shear rotation on the strengths of beam-end bolted connections failing in block shear have not been studied in detail. In this paper, an experimental program on full-scale shear beam-end bolted connections is presented, where the cold-formed steel (CFS) channels are bolted to mild steel T-shaped sections, which are then rigidly connected to a rectangular hot-rolled steel (RHS) column. A dual-actuator setup comprising two actuators was used in the test apparatus to investigate the effect of the combined shear force and beam-end rotation on the block shear behavior and shear strength of the connections. A total of 78 tests were carried out at the University of Sydney, with 200 mm depth CFS channels of thicknesses of 1.2 mm and 1.5 mm, in conjunction with various shear distances between the bolts as the main variable to evaluate the effect of the shear fracture paths and fracture process behavior on the shear strength rupture of the connections. Consequently, the test results are compared to the current cold-formed steel design procedures from AS/NZS 4600 and AISI S100 to verify whether the existing design equations and methodologies are accurate for determining the shear capacity of the full-scale shear beam-end bolted connections under the combined effects of shear rotation and fracture. A reliability analysis of the design equations is also included in the paper.
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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 | 0.001 | 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".