Tensile properties of partially austenitised and austempered ductile irons with dual matrix structures
Bibliographic record
Abstract
In the present study, an unalloyed ductile iron containing Fe–3·50C–2·63Si–0·318Mn–0.047Mg (wt-%) were intercritically austenitised (partially austenitised) in two phase region α+ γ at various temperatures of 795, 805, 815 and 830°C for 20 min and then quenched into salt bath held at austempering temperature of 365°C for various times to obtain different ausferrite volume fractions (AFVFs). Results showed that dual matrix structure containing proeutectoid ferrite, new ferrite (also called epitaxial ferrite) and ausferrite (bainitic ferrite+high carbon austenite, which is retained or stabilised austenite) has been developed. Within each of the austempered series in α+ γ temperature range, new ferrite volume fraction increased with increasing intercritical austenitising temperature (ICAT). Although, transforming percentage of new ferrite from parent austenite present at ICAT increased with decreasing ICAT. Some specimens were also conventionally austempered from 900°C for comparison. The new ferrite was absent in these samples. The volume fraction of proeutectoid ferrite, new ferrite and ausferrite can be controlled to determine the strength and ductility. Austempered specimens in α+ γ temperature range exhibited much greater ductility than conventionally austempered ones. The tensile strength increased while ductility decreased with increasing AFVF. On the other hand, the ductility increased with increasing proeutectoid ferrite and new ferrite volume fractions at the expense of strength. The specimen with ∼47·2%AFVF exhibited the best combination of high strength and ductility. The strength and ductility of this material is much higher than that of ferritic grades. Its strength is at the same level as while ductility almost more than four times higher than that of pearlitic grades. Meanwhile, the specimen with ∼ 75%AFVF exhibited the best combination of high strength and ductility compared with those of pearlitic grades. The strength of this material is much higher and its ductility is almost more than two times higher than that of pearlitic grades yet slightly lower than that of ferritic grades. This material also meets the requirements for the strength of quenched and tempered grades and its ductility is higher than that of this grade.
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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 | 0.000 | 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) | 0.002 | 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".