Numerical Simulation of the Sintering Process
Bibliographic record
Abstract
Sintering is a thermal process of converting loose fine particles into a solid coherent mass by heat without fully melting.Sintered ore manufactured from a sintering plant is used as a raw material of the blast furnace.The sintering process discharges harmful gases, such as SOx, dioxin and CO2 because of the use of coal.Therefore, sintering process has been improved continuously in order to solve the disadvantages of sintering process.In particular, waste gas recirculation system can reduce the total amount of waste gas and energy.In this study, mathematical model that predicts the sintering process was developed.This model calculates the flow rate distribution, temperature and composition of waste gas and sinter bed profile in basic sintering process.Also, waste gas recirculation model is applied in addition.Pot test was performed in order to improve the accuracy of the model.The pot has a window to observe fine line and it is possible to change the composition and temperature of the injection gas in order to simulate the gas recirculation process.This model will be used as a potential tool for the basic design of sintering process including waste gas recirculation system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".