Experimental drying shrinkage behaviour of concrete masonry for climate change design adaptation
Bibliographic record
Abstract
The analysis of the Climate Change Adaptation Standards inventory conducted by the Canadian Standards Association (CSA) in 2018 revealed the need for urgent provisions for climate change adaptation in cavity-wall design. The distress in masonry cavity-walls is often attributed to the differential movements between the outer veneer and inner loadbearing members. In the case of concrete masonry blocks used for structural backups, drying shrinkage phenomena are the primary cause of deformations leading to damage, which can worsen with the effects of climate change. However, the design of cavity-walls in Canada currently relies on outdated data that only pertains to individual concrete blocks. As part of a larger climate change design adaptation research project, this thesis paper presents a new testing methodology for unconstrained mortared concrete masonry prisms to gather insights on moisture-induced shrinkage and explore the influence of mechanical interaction between blocks and mortar. The methodology involves a two-step process where specimens are first allowed to dry from a saturated surface dry state over 12 weeks and then tested using the rapid method outlined in ASTM C426-06. The preliminary results and ongoing new results obtained are in good agreement with those obtained by previous Canadian researchers and suggest that the presence of mortar joints does not noticeably influence the shrinkage behaviour of the mortared concrete masonry assemblies tested so far. This research builds and tests an experimental infrastructure and framework that was not available at McGill University before, providing a significant contribution to the field. It aims to provide missing data to calibrate numerical models for designing cavity-walls in the future
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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 | 0.000 | 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) | 0.002 | 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".