A Technique for the Evaluation of Instantaneous Heat Fluxes for the Horizontal Strip Casting of Aluminum Alloys.
Bibliographic record
Abstract
Transient heat transfer between solidifying light metals strips and a moving substrate has been investigated. For this purpose, an experimental apparatus was constructed, consisting of a cold moving substrate onto which molten metal from a containment mold is deposited. The substrate was flame sprayed with various commercial coatings while its speed and the thicknesses of strip produced matched industrial values. The primary objective of this work was to study the effects of some important variables, such as roughness of substrate, type of coating, thickness of strip and initial superheat, on heat fluxes. Substrate speeds in the range of 0.4–1.2 m/s were employed and strips with thicknesses between 1 and 5 mm were produced. The heat fluxes were determined "inversely" by an inverse heat transfer technique, using temperature measurements from thermocouples embedded within the substrate. Peak heat fluxes between 0.6 and 3.0 MW/m2 were found for the diverse experimental conditions investigated. The heat transfer coefficients were deduced using a one-dimensional, finite-difference model, based on the corresponding calculated heat fluxes. Values of h ranged from 700–5000 W/m2·K. The various coatings used, and the different levels of substrate roughness, contributed to the wide range of h values reported. The heat transfer coefficient was found to increase with initial superheat, thickness of strip and smoother coatings. Correlations were derived between peak heat fluxes and the most significant variables. More importantly, the transient evolution of q and h after their peak values were assessed and good correlations could be derived. The findings of this work are believed to be useful for industrial processes, since they give a better picture of the influence of some important variables on the heat transfer involved for this particular type of metal-substrate contact. This is relevant, for example, to horizontal direct strip casting processes currently under investigation for the production of low carbon steel strips.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".