Effective Shear Design of Reinforced Masonry Beams
Bibliographic record
Abstract
The objective of this paper is to analyze shear design provisions for reinforced concrete masonry (RCM) beams. Design provisions from various building codes are assessed in terms of reliability and predictive capabilities. A database of 112 shear tests reported in the literature on RCM beams without stirrups is assembled, and the failure shear stresses of these beams are predicted using four different masonry design codes. The analyzed codes include CSA S304.1-04 (Canada), TMS 402-08 (US), AS 3700-2001 (Australia), and BS 5628-2:2005 (UK). A fifth set of shear design provisions is chosen as well – the General Method of shear design from the CSA A23.3-04 code for reinforced concrete. The study showed that the average Vexp/Vpred ratios for the masonry codes ranged from 1.05 to 1.53. However, high coefficients of variation for all four masonry codes indicated that low strength reduction factors are required in order to apply the design codes with appropriate levels of safety. Interestingly, the CSA A23.3 general method had the lowest coefficient of variation of all five codes, and the third lowest average ratio of tested to predicted strength. It is concluded that RCM beams exhibit similar behaviour in shear as reinforced concrete beams, and that their shear strengths can be more accurately and safely predicted using the CSA A23.3 code than current masonry codes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".