Compressive Behavior of Gusset Plates Connected with Single-Angle Members
Bibliographic record
Abstract
Gusset plate connections with single-angle steel members are commonly used in power transmission towers. However, little research has been carried out with regard to the compressive behavior and design of gusset plates connected with single-angle members. Due to the complexity of the connections and load eccentricity, it is difficult to predict the compressive strength of the gusset plates. In this study, two full-scale experimental tests and a numerical parametric study were conducted to investigate the compressive behavior of such gusset plate connections. In the tests, the buckling failure mode and lateral-torsional deformation were observed. Finite-element (FE) models were then established and validated through comparison against the test results. In the parametric study, the effects of gusset plate thickness, unbraced length, distance to bending line, and load on the adjacent bracing member were examined. On the basis of the findings of this study and currently available design methods, two design methods were proposed for predicting the compressive strength of gusset plates connected with single-angle members. Good agreements were observed between the FE and design results in terms of the compressive strength and it was found that one method based on plate buckling gave a better prediction of the strength of gusset plates connected with single-angle members than the other based on effective column.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".