Capacity-Based Design for Cross-Laminated Timber Buildings
Bibliographic record
Abstract
The use of cross-laminated timber (CLT) in residential and non-residential buildings is becoming increasingly popular in North America. While the 2016 supplement to the 2014 edition of the Canadian Standard for Engineering Design in Wood, CSAO86, provides provisions for CLT structures used in platform type applications, it does not provide guidance for the in-plane stiffness and strength of CLT shearwalls. The research presented in this paper investigated the in-plane stiffness and strength of CLT shearwalls with different connections for platform-type construction. Finite element analyses were conducted where the CLT panels were modelled as an orthotropic elastic material, and non-linear springs were used for the connections. The hysteretic behaviour of the connections under cyclic loading was calibrated from quasi-static tests; the full model of wall assemblies was calibrated using experimental tests on CLT shearwalls. A parametric study was conducted that evaluated the change of strength and stiffness of walls with the change in a number of connectors. Finally, a capacity-based design procedure is proposed that provides engineers with guidance for designing platform-type CLT buildings. The philosophy of the procedure is to design the CLT buildings such that all non-linear deformations and energy dissipation occurs in designated connections, while all other connections and the CLT panels are designed with sufficient over-strength to remain linear elastic.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".