Cross-Laminated Timber Shear Connections with Double-Angled Self-Tapping Screw Assemblies
Bibliographic record
Abstract
The research presented in this paper examines the shear resistance performance of self-tapping screws (STS) in three-ply cross-laminated timber (CLT) panels. Specifically, the feasibility of using innovative STS assemblies with double inclination of fasteners was investigated for the shear connection of CLT panels. The specimens (1.5×1.5 m) were subjected to quasi-static and reversed-cyclic loading. The tests were set up to approximate pure shear loading, with three-panel CLT assemblies connected with STS. The resulting load-displacement and hysteretic curves were used to determine an equivalent energy elastic-plastic curve to estimate assembly capacity, yield load, yield displacement, ductility ratio, stiffness, and damping. Excellent structural performance in terms of capacity and stiffness was obtained while still providing the required ductility for the system to be used in seismic applications. The average static and cyclic yield loads were 6.0 kN/screw and 5.9 kN/screw, respectively. Average static and cyclic and ductility ratios were 7.7 and 4.1, respectively, allowing the connection to be classified as highly ductile under quasi-static loading and moderately ductile under reversed cyclic loading. The data obtained allow engineers to specify an innovative connection assembly with double inclination of fasteners for lateral load–resisting systems of CLT 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 | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".