Structural Reliability of Non-Slender Loadbearing Concrete Masonry Members under Concentric and Eccentric Loads
Bibliographic record
Abstract
Although the reliability levels of structural steel and reinforced concrete structures designed to the Canadian codes and standards have been investigated substantially in the past four decades, studies on the reliability of masonry structures are limited. Based on some preliminary studies in 1980s, the design of masonry structures using the limit states method was introduced in the 1994 edition of the Canadian standard S304 in order to provide more uniform and economical design guidelines. However, the limit states design criteria were not supported by a rigorous reliability-based analysis. The investigation reported herein was carried out to contribute to filling the gap in our knowledge on the reliability of structural masonry members designed using the limit states method, to establish reliability levels for masonry comparable to other structural materials and to help remove any unnecessary conservatism in the masonry design process. The first order reliability method was used to assess the reliability of unreinforced and reinforced non-slender concrete masonry walls under combined axial load and out-of-plane bending. In this research, only non-slender walls having a slender ratio (kh/t) not requiring consideration of second order effects are considered. Nevertheless, the procedure for performing the reliability analysis for walls with larger kh/t is proposed and explained.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".