Influence of screw angle and position on the extraction dynamics of Cross-Laminated Timber: an empirical analysis and comparative modeling study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The design of dowel-type fastener connections is crucial for the structural integrity of Cross-Laminated Timber (CLT) systems, with individual fastener anchorage capacity as a key factor. This study investigates the withdrawal performance of Self-Tapping Screws (STSs) in CLT systems using Canadian Douglas fir. Four driving angles—45°, 60°, 75°, and 90°—were tested, alongside screw placements within panel gaps. Optimal performance was observed at 75° and 90°, with 90° placement in gaps enhancing stiffness and ductility but reducing energy dissipation. The ratios of experimental capacities to model predictions were 1.26–1.49 for the Blaß and Uibel (B&U) model and 1.36–1.56 for Eurocode 5 (EC5). The new EC5 code, compared to the previous version, includes several advancements such as more accurate material properties and improved calculation methods for fastener withdrawal capacity, offering enhanced prediction accuracy for STS performance in CLT. The discrepancies in the over-strength factors predicted by the new EC5 version ranged from 1.07 to 1.37. These findings suggest the need to consider the incorporation of a specific calculation model for STS withdrawal capacity in CLT, such as the Ringhofer et al. model, in the next revision of EC5.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it