Performance of timber moment connections with a decoupled mechanism: Glued-in rods for moment and dowels for shear
Bibliographic record
Abstract
Mass timber construction has created a growing need for high-performance moment-resisting connections, particularly in tall building design. Although glued-in rod (GIR) connections provide superior strength and aesthetic benefits, their performance under combined loading poses significant challenges. This study presents an innovative moment connection system that strategically uncouples moment and shear resistance through the integration of GIRs and a dowelled connection. The proposed system employs slotted holes to decouple GIRs from shear forces, enabling them to primarily resist moments, while a dowelled connection determining the proposed system achieved 30.8 % higher moment capacity than conventional GIR connections, while maintaining comparable deformation capacity. Both connection types exhibited ductile behavior through controlled yielding of GIRs, successfully protecting the brittle timber elements. An analytical model developed based on the transformed section method showed good agreement with the experimental results, with differences of 0.7 %, 7.0 %, and −1.9 % for rotational stiffness, yield moment, and ultimate moment capacity, respectively. The decoupling of force-resisting elements not only enhanced structural performance but also enabled reliable prediction of connection behavior using well-established GIR withdrawal properties, offering a practical solution for moment-resisting timber connections.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".