Glulam connections assembled with screws in different installation angles
Bibliographic record
Abstract
Self-tapping screws are the recognized state-of-the-art in fastener technology for timber structures.Combining fasteners of different stiffness, such as self-tapping screws with different installation angles, can be advantageous to simultaneously achieve high connection stiffness and ductility.In this paper, experimental investigations on a total of 65 glued-laminated timber joints assembled with a variety of installation angles including several combinations of self-tapping screws acting axially in withdrawal with self-tapping screws acting laterally are presented.The connection performance was analyzed in terms of the load-carrying capacity, the deformation capacity, the stiffness, and the ductility.The findings demonstrated that joint assemblies with self-tapping screws loaded primarily laterally exhibit low stiffness but high ductility, whereas joint assemblies with self-tapping screws loaded primarily in withdrawal are very stiff but exhibit low ductility.Combining screws in different installation angles created glued-laminated timber connections that combine high stiffness with high ductility.Existing analytical expressions were deemed suitable to estimate load-carrying capacity through simple summation of the different screws' individual resistances.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".