Experimental investigation of steel-timber shear connections with self-tapping screws
Bibliographic record
Abstract
Steel-timber composite floor systems consisting of a cross-laminated timber (CLT) floor slab and steel wide flange beams rely on a shear connection at the interface between the steel and CLT to maintain composite action. This paper discusses experimental results on the behaviour of self-tapping screws (STS) as shear connectors for steel-timber composite beams and examines the influence of several parameters on their performance, including screw type, size (i.e., length and diameter), installation angle, and the performance of combined screwed and glued connections. Experimental results demonstrate that varying STS types and installation conditions result in significant differences in stiffness, strength, and failure mechanisms. In general, fully threaded STS exhibit more variability in their response and brittle failure modes, whereas partially threaded STS exhibit ductile failures with the more consistent and predictable performance. Due to their consistent performance and their ease of installation, partially threaded STS are likely the most suitable for steel-timber composite beams, and so, a load slip model was proposed to model their response. The results show that the proposed load-slip model can predict the stiffness and maximum load for partially threaded STS within 5 % of the experimental result on average over a range of screw lengths and diameters. Limitations of the model are also discussed. • Testing of self-tapping screws as shear connectors for steel-timber composite beams. • Influence of screw type, screw size, installation angle, and glued connections. • Screw type and installation angle influences the stiffness, strength, and failure mode. • An empirical model is proposed for the load-slip response of partially threaded self-tapping screws. • Empirical model can effectively capture connection stiffness and strength.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".