Experimental verification of analytical strength and deformation methods for single and multi-panel nailed CLT shear walls
Bibliographic record
Abstract
Cross-laminated timber (CLT) is becoming a feasible alternative as structural material for midand high-rise buildings. Although CLT walls are appropriate for resisting lateral loads from wind and earthquakes, the current provisions in the Canadian Standard for Engineering Design in Wood lack analytical expressions for estimating their resistance and deflection. In this thesis, the performance of nailed single and couple CLT shear walls is investigated by comparing UNBC test data with the strength and stiffness predictions using analytical proposals. Four methods are considered: Method A (Casagrande et al. 2017), considers the minimum strength value of the hold-down and the vertical fasteners; Method B (Shahnewaz et al. 2019), which accounts for the rocking resistance of all connectors; Method C (Masroor et al. 2020) which accounts for the bi-axial behaviour of connectors; and Method D (Nolet et al. 2019) which describes the elastic-perfectly plastic behaviour of CLT shear walls while neglecting the bi-axial behaviour of brackets. The best match for the elastic behaviour of the nailed shear walls was achieved using Method B, while Method C reasonably predicted the inelastic shear wall behaviour. With the validation against test results, designers should consider using either method depending on the design intentions. Future research should aim at either extending Method B (Shahnewaz et al. 2019) towards the inelastic behaviour or improving Method C (Masroor et al. 2020) in the elastic range.
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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 | 0.002 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".