Permeability evolution during equiaxed dendritic solidification of Al–4.5 wt%Cu
Bibliographic record
Abstract
The evolution of permeability in Al–4.5 wt%Cu during equiaxed dendritic solidification has been determined through physical and numerical modelling for solid fractions from 0.35 to 0.8. Cast samples solidified with a variety of cooling rates and quenched at different stages during dendritic solidification were used to generate 3D geometries of solidifying microstructure using x-ray microtomography. The permeability was then characterized (i) physically by passing glycerin through large-scale analogues of the microstructure and (ii) numerically by solving the continuity and momentum equations for the corresponding unstructured meshes of the 3D geometries used for the physical models. The numerically determined values of permeability are in good agreement with those measured and within the scatter of related studies. The permeability results have been compared with the Carman–Kozeny expression to determine the value of the Carman–Kozeny constant. Moreover, the correlation of secondary dendrite arm spacing and solid/liquid interfacial area per unit volume of solid with solidification time has been investigated for use as a practical means of characterizing the length scale for permeability determination.
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 | 0.000 |
| 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".