Axial Solidification Experiments to Mimic Net-Shaped Castings of Aluminum Alloys—Interfacial Heat-Transfer Coefficient and Thermal Diffusivity
Bibliographic record
Abstract
Net-shaped casting processes in the automotive industry have proved to be difficult to simulate due to the complexities of the interactions amongst thermal, fluid, and solute transport regimes in the solidifying domain, along with the interface. The existing casting simulation software lacks the necessary real-time estimation of thermophysical properties (thermal diffusivity and thermal conductivity) and the interfacial heat-transfer coefficient (IHTC) to evaluate the thermal resistances in a casting process and solve the temperature in the solidifying domain. To address these shortcomings, an axial directional solidification experiment setup was developed to map the thermal data as the melt solidifies unidirectionally from the chill surface under unsteady-state conditions. A Dilute Eutectic Cast Aluminum (DECA) alloy, Al-5Zn-1Mg-1.2Fe-0.07Ti, Eutectic Cast Aluminum (ECA) alloys (A365 and A383), and pure Al (P0303) were used to demonstrate the validity of the experiments to evaluate the thermal diffusivity (α) of both the solid and liquid phases of the solidifying metal using an inverse heat-transfer analysis (IHTA). The thermal diffusivity varied from 0.2 to 1.9 cm2/s while the IHTC changed from 9500 to 200 W/m2K for different alloys in the solid and liquid phases. The heat flux was estimated from the chill side with transient temperature distributions estimated from IHTA for either side of the mold–metal interface as an input to compute the interfacial heat-transfer coefficient (IHTC). The results demonstrate the reliability of the axial solidification experiment apparatus in accurately providing input to the casting simulation software and aid in reproducing casting numerical simulation models efficiently.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".