Kinetics of Austenite Formation in a Medium-Carbon, Low-Alloy Steel with an Initial Martensite Microstructure: Influence of Prior Austenite Grain Size
Bibliographic record
Abstract
The impact of prior austenite grain size (PAGS) on the kinetics of austenite formation with an initial martensite microstructure was investigated in a medium-carbon, low-alloy steel. Two distinct PAGS of 117 and 330 μm, representing the range of grain sizes encountered in industries, were considered. In this analysis, high-resolution dilatometry was used to study the formation of austenite during continuous heating experiments. The analysis of the dilatometry results revealed that grain refinement accelerated the rate of austenite formation without impacting its austenite formation temperature. Intermittent quenching tests were conducted to elucidate the nucleation and growth mechanisms of austenite formation using a combination of optical, scanning electron microscopy (SEM), and electron backscatter diffraction (EBSD). The differences in austenite formation kinetics as a function of prior austenite grain size were quantified and modeled in the framework of diffusion-controlled nucleation and growth theories using the genetic algorithm optimization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".