On the Fire Performance of Double-shear Timber Connections
Bibliographic record
Abstract
In heavy timber structures, double-shear connections, including wood-wood-wood (WWW), wood-steelwood (WSW) and steel-wood-steel (SWS) connections with either bolts or dowels as fasteners, are widely used to assembly structural members and transfer loads.However, connections with metal fasteners and components are potentially venerable links in fire exposure.A number of efforts have been devoted to study the fire performance of timber connections in the last two decades.With the knowledge and experimental data generated, new attempts have been made in order to develop new calculation methods and improve design rules for timber connections in fire.In this paper, existing models are discussed and new correlations are presented for the calculation of the fire resistances of double-shear timber connections.Various factors, i.e. timber thickness, fastener diameter, and load ratio are considered in the correlations.Comparison between the predictions using the correlations and the measured results in fire resistance tests shows good agreement.For timber connections with protective membranes, the component additive method (CAM) can be used by adding the additive fire resistances of the protective membranes to the fire resistances of unprotected timber connections.Connections with concealed fasteners and intumescent paint are also discussed in this paper.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".