Canada/US (CANUS) Comparison of Reinforced Masonry Design: Project Overview and Design Examples
Bibliographic record
Abstract
This work is the first one of the four companion papers associated with the Canada/US (CANUS) collaborative project: Harmonization of Canadian and American Masonry Structures Design Standards. This paper provides an overview of the key differences in reinforced concrete masonry design provisions between the two countries. The first part of the paper summarizes these differences in a discussion format, while the second part provides two design examples: a two story mixed-use occupancy building and a multi-story residential building. Two locations are selected for high and low seismicity. While the critique of the building codes is out of the scope of this study, when appropriate, differences regarding the loading considerations from NBCC 2015 and ASCE 7-16 are highlighted. In some cases, the corresponding design checks align closely between the two countries’ design standards, while in other cases there are minor to significant differences. There are also instances where one of the standards is silent on a topic while the other addresses it comprehensively. In general, it is observed that TMS 402-16 allows a larger applicability of masonry design compared to CSA S304-14 due to the compounding effect of lower trust in masonry’s material strength and stricter considerations in design equations.
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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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".