Bond Strength of Adhered Manufactured Thin Stone/Brick Masonry Veneer Units to Setting Bed Mortar at Different Temperatures and Different Cycles of Freeze-Thaw
Bibliographic record
Abstract
Close to no study has been conducted to identify the possible influential physical and mechanical characteristics of adhered thin masonry units and mortars on the bond strength in adhered thin masonry veneer (ATMV) applications. There have been numerous cases of bond failures in ATMV applications probably due to lack of knowledge and the lack of any standards for the design and installation of ATMV. In the Canadian climate, exposure to extreme weather conditions like very low temperatures and freeze-thaw cycles are common and may be a cause of bond deterioration and failures. Therefore, it is important to study the effects of exposure to extreme weather conditions on the bond strength. This research first measures and evaluates the physical and mechanical properties of thin masonry units and mortars. Then shear and tensile bond strengths are studied considering different age and environmental factors. At least three different ages, two different curing temperatures, three testing temperatures and four cycles of freeze-thaw were considered. Subsequently, any possible relationship between these characteristics and bond strengths were evaluated and proper practices were recommended.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".