Impact of beam hanger rotational stiffness on column bending moment in glulam frames
Bibliographic record
Abstract
,The use of glulam column-and-beam frames is increasingly favored in modern construction due to their effectiveness in accommodating long spans and creating open interior spaces. These systems frequently employ deep glulam beams connected to columns using pre-engineered beam hangers. Although such connections are typically idealized as pinned, they often exhibit rotational stiffness under lateral loading, inducing bending moments in the columns that can affect their load-carrying capacity. Therefore, it is essential for structural engineers to account for the beam hangers’ rotational stiffness in design to ensure safety. In this thesis, the structural behavior of two full-scale, two-bay glulam frames utilizing pre-engineered beam-to-column connections was investigated through a comprehensive experimental testing program under both gravity and lateral loading. It is noteworthy that all frames maintained their load-carrying capacity at a 3% drift ratio, which exceeds the 2.5% limit specified by the National Building Code of Canada. The analysis indicated that the columns must be designed to resist both bending moments and axial forces. Furthermore, the stiffness of the connections plays a critical role in the structural response to lateral loading, which can significantly influence seismic performance. Although beam hangers act flexibly when used singly on exterior columns, tests show that when used on both sides of an interior column, they behave semi-rigidly rather than as pinned connections. These findings underscore the necessity of considering these factors in the design of glulam frames to ensure safer and more resilient structures.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".