A FEM Analysis on the Influence of Manganese on Carbon and Chromium Macrosegregation in Large Size Steel Ingot
Bibliographic record
Abstract
In this study, 3D numerical simulations were performed to study the effect of Mn on the macrosegregation behaviors of carbon and chromium in a 40 MT steel ingot using Finite Element Modeling (FEM). Two Mn contents of 0 and 5 wt.% were investigated. Thermophysical properties such as specific heat, density and phase fractions were determined using thermodynamic software Thermo-Calc®. Simulation results indicated that higher Mn content increases the carbon macrosegregation while it tends to lower the one of chromium. Moreover, it changes the solute poor band into rich one in the case of chromium and no bands were obtained for carbon. These results are analyzed in terms of the changes of thermophysical properties, interactions between alloying elements and the change in the primary solidification mode from δ-ferrite to austenite resulting from the increase of Mn concentration.
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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".