Bibliographic record
Abstract
Hydration of magnesia-based refractory bricks could occur during storage, during drying after installation, or in service, and the hydration would cause damage to refractory bricks and furnace linings. In order to understand the hydration mechanisms of magnesia-based refractories, three types of bricks were chosen: magnesia, magnesia-spinel and magnesiachrome bricks, and hydration tests were performed at 60 to 130°C in 98% relative humidity, water, and steam. The variation of the modulus of elasticity (MOE), determined by the impulse excitation technique (IET), as well as apparent porosity, air permeability, pore size and pore size distribution were correlated with the hydration data. The phase compositions and microstructure modifications were also studied on selected specimens by XRD and SEM/EDS. Based on the experimental results, a hydration model of "cylindrical pore model" was established and a hydration mechanism was suggested. The hydration takes place in three stages. In the first stage, which is controlled by chemical reaction, a film of brucite forms and MOE quickly increases. During the second stage, which is controlled by diffusion, the MOE gradually reaches a maximum value followed by a slow, decrease due to the formation of cracks on the film and weakening of grain boundaries until the MOE reaches the initial value. At this point, the third stage, corresponding to "dusting", starts to take place until the brick disintegrates. The results also indicate that the hydration rate increases with rising temperature and the CaO/SiO₂ ratio. The variations in permeability and porosity are opposite to that in MOE. A nondestructive method - IET to assess the hydration degree of magnesia-based refractory bricks was proposed.
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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 | 0.000 |
| 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 | 0.000 |
| 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".