SEISMIC BEHAVIOUR AND DESIGN OF MODERN REINFORCED MASONRY BUILDINGS: CANADIAN PRACTICE
Bibliographic record
Abstract
Reinforced masonry (RM) has been used in Canada since 1960s, mostly for construction of low- and mid-rise buildings. The concept of RM construction in Canada involves the use of hollow concrete blocks reinforced with vertical and horizontal steel bars embedded in cementitious grout as needed. The approach for seismic design of RM wall structures has been well established and incorporated in Canadian masonry design standard CSA S304-14. The design procedures are intended to ensure ductile performance of RM shear walls and ensure adequate strength due to seismic shear forces, as well as combined axial load and flexure. Detailing of the walls depends on the required performance/ductility, and the walls are broadly classified as Moderately Ductile and Ductile. In the last two decades a few major research studies were performed at Canadian universities, focused on the seismic response of RM shear walls with different design and detailing arrangements. The paper will present the key findings of these research studies, in the context of critical parameters that influence seismic response of RM shear walls, as well as the special detailing provisions, such as boundary elements, which are required to enhance ductile seismic performance of tall RM structures. Future research needs related to seismic response of ductile RM structures will be also discussed.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".