Fire Performance of Self-Tapping Screws in Tall Mass-Timber Buildings
Bibliographic record
Abstract
Building elements are required to provide sufficient fire resistance based on requirements set forth in the National Building Code of Canada (NBCC). Annex B of the Canadian standard for wood engineering design (CSA O86-19) provides a design methodology to calculate the structural fire-resistance of large cross-section timber elements. However, it lacks at providing design provisions for connections. The objectives of this study are to understand the fire performance of modern mass timber fasteners such as self-tapping screws, namely to evaluate their thermo-mechanical behavior and to predict their structural fire-resistance for standard fire exposure up to two hours, as would be required for tall buildings in Canada. The results present the great fire performance of using self-tapping screws under a long time exposure on connections in mass timber construction. The smaller heated area of the exposed surface has limited thermal conduction along the fastener’s shanks and maintained their temperature profiles relatively low for two hours of exposure. Based on the heat-affected area, the study presents new design principles to determine the residual length of penetration that would provide adequate load-capacity of the fastener under fire conditions. It also allows determining safe fire-resistance values for unprotected fasteners in mass timber construction exposed up to two hours of standard fire exposure.
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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 | 0.000 | 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) | 0.001 | 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 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".