Comparison of Austempering and Quench-and-Tempering Processes for Carburized Automotive Steels
Bibliographic record
Abstract
Carburized parts often see use in powertrain components for the automotive industry. These parts are commonly quenched and tempered after the carburizing process. The present study compared the austempering heat treatment to the traditional quench-and-temper process for carburized parts. Samples were produced from SAE 8620, 4320, and 8822 steels and heat treated across a range of conditions for austempering and for quench-and-tempering. Distortion was examined through the use of Navy C-Ring samples. Microstructure, hardness, and Charpy toughness were also examined. X-ray diffraction was used to compare the residual stress found in the case of the components after the quench-and-temper and the austempering heat treatments. Austempering samples showed less distortion and higher compressive residual stresses, while maintaining comparable hardness values in both case and core. Toughness measurements were also comparable between both processes.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".