Load-carrying capacity of housings in solid timber beams
Bibliographic record
Abstract
Timber framing has traditionally relied on metal fasteners, with have a high carbon footprint and often limited aesthetic appeal. These challenges can be addressed by using traditional joints such as timber housings. However, there are no design guidelines available that account for the joint geometric parameters, mechanical reinforcements, or the wood moisture content during fabrication and when loaded. In this research, the influence of joint geometry, wood moisture and reinforcement on the load-carrying capacity of solid timber beams with housings was investigated. A total of 150 Pseudotsuga menziesii (Douglas fir) beams were tested according standard, considering different moisture condition (wet or dry) at the time of cutting and at the time of testing. The tests confirmed that greater bearing depth and the use of self-tapping screws as reinforcement lead to increased load-carrying capacity. However, moisture condition significant affected only the double housings, not the single housings. In addition, 198 small-scale specimens were tested for shear, tension and compression to evaluate the impact of small clear specimen material strength on the beam load-carrying capacity. The results showed that these properties were weak predictors of housing performance. Finally, a design approach based on existing Canadian code provisions is suggested.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".