Performance of Steel Shear Connections under Combined Moment, Shear, and Tension
Bibliographic record
Abstract
Beam-to-column connections play a critical role in a structural system's ability to resist widespread collapse by redistributing loads should localized damage occur due to an unanticipated extreme loading event such as a vehicular collision or an accidental explosion. Following the damage of a column in a steel frame designed to carry gravity loads, the strength and ductility demands on adjacent shear connections change substantially from those considered in conventional design. In addition to shear forces, large deflections can lead to the development of significant axial tension through what is known as catenary action. The behavior of steel shear connections under the combined effects of moment, shear, and tension has not been studied extensively and is not generally well-understood. However, this information is essential to assessing and improving the collapse resistance of structures. This paper presents the results of full-scale physical tests designed to investigate the behavior of common steel shear connections under load histories emulating the anticipated effects of the loss of an adjacent column, including large rotations and the development of axial tension. A variety of relative proportions of moment, shear, and tension were used for each type of connection, which included shear tab, single angle and double angle specimens, in order to permit a broad assessment of connection robustness applicable to different building geometries. This study examines the relative performance of these connection types, as well as the effects of connection geometry and combined loading. Observed connection capacities, ductility limits, and failure modes are presented and discussed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".