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Record W4417508162 · doi:10.24124/2025/30711

Impact of beam hanger rotational stiffness on column bending moment in glulam frames

2025· dissertation· W4417508162 on OpenAlexaboutno aff
Hamid R. Nasiri

Bibliographic record

Venuenot available
Typedissertation
Language
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsStiffnessBeam (structure)Bending stiffnessBending momentMoment (physics)BendingLimit (mathematics)Column (typography)

Abstract

fetched live from OpenAlex

,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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.839
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.012
GPT teacher head0.289
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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