Phase-field simulation of effect of lateral constrains on dendritic spacing change
Bibliographic record
Abstract
The mechanical properties of materials are strongly dependent upon their microstructures, and the lateral constrains in presence of melt have a significantly effect on the microstructure evolution. A non-isothermal phase-field model for pure metal was implemented to simulate the microstructure evolution in the presence of lateral constrains of different shapes during the solidification of pure Ni, in order to study the effect of lateral constrains on the dendritic spacing changes caused by these lateral constrains. The results indicate that lateral constrains have a direct influence on the dendrite development, and the lateral constrains of different shapes can lead to different influences on the dendrite arm spacing changes. The constrains of triangle with sharp corner at the bottom has the most significant influence on the dendrite spacing changes, and rectangle and triangular constrains with its sharp corner above show a controlling effect on the dendrite arm spacing, that is, the dendrite growth of different primary arm spacings has the same developing manner with these two kinds of lateral constrains, the new developing dendrite arm spacing is determined by the shape of constrains, and has less relationship with its primary arm spacing. When the lateral constrain of trapezoid is introduced, the dendrite arm spacing can be determined by changing the size of the hemline of constrains. Therefore, the lateral constrains in the solidification process can significantly change the dendrite arm spacing.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".