STRUCTURAL PERFORMANCE OF GLULAM TIMBER-STEEL BRACE CONNECTIONS REINFORCED WITH SELF-TAPPING SCREWS
Bibliographic record
Abstract
Modern mass timber braced frames rely on connection yielding to provide ductility and energy dissipation capacity under earthquake loads.However, the ductility and energy dissipation capacity of steel dowel connections can be limited by the onset of a brittle failure mechanism in the timber (e.g., row-shear, group tear-out, or tension failure) prior to significant dowel yielding.To address this challenge, this paper presents experimental results on the structural performance of timber-steel dowelled connections reinforced with self-tapping screws.Four full-scale connections were tested under monotonic loading with and without reinforcing screws.The tested connections had two internal steel plates that were fastened to the timber using steel dowels.The unreinforced connection was intentionally designed to exhibit a brittle row shear failure prior to yielding of the steel dowels.Results of the study demonstrated the brittle nature of row shear in timber connections and the potential for using self-tapping screws to promote a more ductile failure.While the unreinforced connections exhibited no ductility, the reinforced connections had an average ductility of 4.8.Overall, results of this study demonstrate the potential for using self-tapping screws to retrofit and reinforce a timber-steel brace connection for situations in which a connection may be predisposed to brittle row shear failure.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".