Energy Saving Melting and Revert Reduction Technology (Energy-SMARRT): Clean Steel Casting Production
Bibliographic record
Abstract
Inclusions in steel castings can cause rework, scrap, poor machining, and reduced casting performance, which can obviously result in excess energy consumption. Significant progress in understanding inclusion source, formation and control has been made. Inclusions can be defined as non-metallic materials such as refractory, sand, slag, or coatings, embedded in a metallic matrix. This research project has focused on the mold filling aspects to examine the effects of pouring methods and gating designs on the steel casting cleanliness through water modeling, computer modeling, and melting/casting experiments. Early in the research project, comprehensive studies of bottom-pouring water modeling and low-alloy steel casting experiments were completed. The extent of air entrainment in bottom-poured large castings was demonstrated by water modeling. Current gating systems are designed to prevent air aspiration. However, air entrainment is equally harmful and no prevention measures are in current practice. In this study, new basin designs included a basin dam, submerged nozzle, and nozzle extension. The entrained air and inclusions from the gating system were significantly reduced using the new basin method. Near the end of the project, there has been close collaboration with Wescast Industries Inc., a company manufacturing automotive exhaust components. Both computer modeling using Magma software and melting/casting experiments on thin wall turbo-housing stainless steel castings were completed in this short period of time. Six gating designs were created, including the current gating on the pattern, non-pressurized, partially pressurized, naturally pressurized, naturally pressurized without filter, and radial choke gating without filter, for Magma modeling. The melt filling velocity and temperature were determined from the modeling. Based on the simulation results, three gating designs were chosen for further melting and casting experiments on the same casting pattern using the lip pouring method. It was observed again that gating designs greatly influenced the melt filling velocity and the number of inclusion defects. The radial choked gating showed improvements in casting cleanliness and yield over the other gatings, even though no mold filters were used in the gating system.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".