Mould heat transfer and continuously cast billet quality with mould flux lubrication Part 1 Mould heat transfer
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Bibliographic record
Abstract
With the drive to cast higher quality, many minimills are adopting mould powder as a lubricant for the continous casting of steel billets. Over the past three decades considerable experience has been accumulated on the relationship between mould behaviour and billet quality for oil lubrication, but comparatively few studies have been conducted for mould powder lubrication. This study, conducted at a Canadian minimill, involved instrumenting four faces of a copper mould with thermocouples and monitoring mould temperatures during casting of 208 × 208 mm billets with mould flux lubrication. Billet samples were also taken to coincide with periods of measurements. Mould temperatures were monitored for two different mould powder compositions, for different mould oscillation frequencies, two mould cooling water velocities, and a range of steel compositions. An inverse heat conduction model was developed to calculate mould heat transfer from the measured temperatures. In this paper, which is the first part of a two part series, details of the inverse heat conduction model and mould heat transfer data are presented. The results obtained for mould flux lubrication have been compared with those for mould heat transfer for oil lubrication. For peritectic steels, with carbon content in the range 0·12–0·14%, it was found that lubricant type has little influence on the measured mould heat flux distribution at the centreline of a face. The peak mould heat flux was found to be approximately 2500 kW m-2 . In contrast, for medium carbon steels, mould heat transfer with mould powder was significantly lower than when oil was employed as a lubricant. For instance, at the meniscus, the peak heat flux with mould powder was approximately 2500 kW m-2 , which was half that recorded with oil as a lubricant. The influence of oscillation frequency, mould cooling water velocity, and mould powder type on mould heat flux has also been presented.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it