Development of Concrete Water Absorption Testing for Quality Control
Bibliographic record
Abstract
Concrete durability can be evaluated by a number of properties - such as water absorption and chloride diffusion. Each of these properties can be measured using Standardized methods. Water absorption can be linked to porosity and therefore to eventual deterioration. Tests based on absorption have the potential to be simple and rapid tests for placed concrete. However, it is impossible to provide the Standard conditions for in-situ measurements. Water absorption is strongly affected by environmental temperature and concrete moisture content. These different conditions may cause incorrect evaluation of concrete performance. \nIn this thesis, several samples were taken from three different construction projects in the Montréal region. These samples were taken to the laboratory, conditioned in different relative humidity and temperature environments and later water absorption tests were performed on them to investigate the effect of these two factors. In addition, three samples of each concrete mixture were placed outdoors and were tested in different environmental situations. Lastly, in-situ water absorption tests were performed on real concrete elements for one of the projects in actual field conditions. \nIt was found that the concrete water absorption rate increases linearly with increasing temperature and decreasing moisture content. In addition, surface relative humidity was found as an accurate and practical indicator of concrete moisture content. These relationships were verified by additional exposed and in-situ measurements. It is suggested to perform several water absorption tests along with temperature and concrete surface relative humidity measurements to arrive at a Standardized value for quality control purposes.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".