Numerical Investigation of the Axial Stress Distribution of Self-Tapping Screws in Mass Timber Products during Wetting or Drying
Bibliographic record
Abstract
Self-tapping screws (STS) are used in wood-to-wood and wood-to-steel connections in timber structures. Premature failure of STS during the construction phase has been reported by structural engineers and contractors in relation to a few North American mass-timber projects. This STS failure type is suspected of having been precipitated by additional axial stress exerted on STS from swelling of the wood resulting from prolonged wetting. This study investigates the axial stress distribution of STS installed in two mass timber products, cross-laminated timber (CLT) and glulam, under axial loading and changing moisture conditions in the linear elastic regime. The focus is on modelling the stress distribution of STS during wood-wetting. Properties of self-tapping screws under axial loads, such as tensile and withdrawal properties, along with swelling properties of CLT and glulam, have been investigated. A numerical method to predict the axial stress distribution of the screw from these material property tests has been developed. The numerical model has been calibrated with test results. The method developed in this research helps in understanding the premature failure of self-tapping screw connections under the moisture content variation of wood. The next step will be developing an analytical model to predict the axial stress distribution of STS.
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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 | 0.001 |
| 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".