Numerical and analytical investigations of steel-to-wood connections with fully threaded self-tapping screws under wetting
Bibliographic record
Abstract
Self-tapping screws (STSs) are widely used in mass timber connections due to their high strength and ease of installation. A new provision of STS connections has been implemented to the latest edition of Canadian timber design standard, CSA O86–24. However, the performance of STS connections under wetting condition has not been fully addressed and remains a critical concern since STS breakage was reported in several mass timber projects exposed to wetting during construction. This study investigates the failure mechanisms of steel-to-wood connections with fully threaded STSs under wetting condition through numerical and analytical approaches. Cohesive zone modeling method was employed to simulate the wood-screw interaction, validated with experimental data, while analytical solutions were developed to predict STS stress distributions. The investigated parameters included screw diameter, penetration length, moisture content change, and installation-induced loads. Results revealed two primary failure modes: (1) STS yielding close to the screw head due to the combined stress from wetting and installation loads, and (2) localized withdrawal failure at the screw tip caused by excessive wood swelling, particularly for the connections with long penetration length (>25 d 0 , where d 0 is the nominal diameter of STS) or large moisture content increase (e.g., 12 % to fiber saturation point). The proposed closed-form analytical model, whose key input parameters can be determined based on STS withdrawal load-displacement curves or empirical equations, showed good agreement with the verified numerical modeling results, offering a practical tool for designers to predict the wetting-induced STS stress in the design phase. This work bridges gaps in the current Canadian timber design standard by providing quantitative methods to evaluate moisture-dependent STS performance in steel-to-wood connections, therefore enhancing the safety and reliability of mass timber construction. • Analysis of wetting and installation-induced stress in self-tapping screws. • Self-tapping screws may yield at the heads or withdraw at the tips under wetting. • Developed analytical solution for STS stress prediction under wetting.
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.
How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".