Cyclic Experimental Behavior of Angles and Applications for Connection Design and Modeling
Bibliographic record
Abstract
Recent work on the seismic behavior of low-ductility, steel-braced frames has suggested that adding top and seat angles to gravity-framing connections can increase a building's reserve capacity and, hence, its collapse performance. To this end, a comprehensive suite of 133 tests has been developed and is currently in progress to establish a baseline of ultimate capacities under monotonic and cyclic loading. Angles range in size from L4x4x5/16 to L8x6x3/4 and will be fastened using 3/4" A325, 1" A325, and 1" A490 bolts. The distance from the heel of the angle to the bolt centerline in the vertical leg, referred to as the gage, has previously been shown to be an important parameter, particularly in relation to the thickness of the angle. Low gage-to-thickness ratios indicate stocky configurations, while high ratios indicate slender, flexure-controlled configurations. The ratios within this study range from 1.25 to 8.00. Based on the test results, this study aims to develop simple analytical models that can reasonably predict ultimate moment capacities and rotations of beam-to-column connections reinforced with top and seat angles.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".