Estimation of Erosion Line of Refractory Brick in Blast Furnace Hearth vie BEM and Cellular-Automata
Bibliographic record
Abstract
This paper is concerned with the method for estimating an erosion surface of refractory brick in blast furnace hearth. The boundary element method (BEM) is used combinedly with a cellular automata (CA) method. The meridional cross-section of the blast furnace hearth is divided into a number of uniform cells, and a state variable defined on each cell is altered by local rules and also a transition rule. The cost function is defined as the square sum of differences between the measured and computed temperatures at some selected points on the outer surface. The minimum value of the cost function is searched in an iterative manner. This paper presents a practical guideline for estimation of the erosion line through numerical simulation. It is demonstrated that there is a region of existing erosion lines which can be well estimated from a several mumber of initial shapes of the erosion line by finding the minimum value of the cost function.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".