Improving Frost Durability Prediction based on Relationship between Pore Structure and Water Absorption
Bibliographic record
Abstract
In North America, clay bricks are qualified as durable if they meet either the ASTM C216 or CAN/CSA A82.1 standard. Although these standards are widely used in North America, they have not been linked with pore Structure (PS). Furthermore, moisture content and pore structure (PS) are two significant parameters that influence the performance of clay bricks during the freezing-thawing process. Thus, finding a relationship between them will lead to a quick assessment of water absorption (WA) and knowing their effect on frost resistance (FR). This work aims to investigate the relationship between PS and WA of clay bricks. Five different types of clay bricks were examined. WA of brick samples was determined according to the CAN/CSA A82.1 standard. Mercury Intrusion Porosimetry (MIP) was used to determine the total porosity and pore size distribution (PSD). The variation of 24-h cold water absorption (CWA) among samples of each type of brick was analyzed and each type of brick was divided into three groups according to their 24-h CWA: low - medium - high. The PSD of bricks was also divided into several ranges based on the pore size. The results indicated that some types of brick have a wide variation in 24-h CWA, which could affect the frost resistance evaluation. The strong relationship between WA and PSD was found, which could be used as a base for determining 24-h CWA.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".