MOUTH-LIKE CRACKING IN A HIGH-STRENGTH MULTIPHASE STEEL AND ITS RELATIONSHIP TO FRACTURE TOUGHNESS
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Bibliographic record
Abstract
The effect of microstructure on crack growth behaviour in steels has always been a subject of considerable research interest. Based on a quenching and partitioning process (Q&P), and the transformation of a nano-scaled bainite in advanced high-strength steels, a novel quenchingpartitioning-austempering process (Q-P-A) has been developed for manufacturing a multiphase microstructure in a medium carbon steel (55Mn2SiCr). The processing sequence consists of the following steps: austenitizing at 900C for 0.5 h; controlled quenching and cooling to 200C, i.e. slightly below Ms (the start temperature for martensite transformation) for 5 s; austempering at 170C for 5 min; up-heating to 250C for 120 min; final air cooling to room temperature. An ultimate tensile strength (UTS) above 2 GPa, as well as an acceptable elongation of 3%, is obtained due to a multiphase formation comprising prior martensite (PM), bainitic ferrite (BF), retained austenite (RA) and nanoscaled structure ((BF + RA(+C))nano). Mouth-like cracks are observed on the fracture surface and the crack arrest behavior is investigated. When a microstructural cluster with (BF + RA(+C))nano fully covered PM is formed, a mouth-like crack can be formed and a superior crack resistance can be obtained. The crack initiates from the PM boundary and propagates along the interface between the PM and (BF + RA(+C))nano over a distance of a few millimeters and before being arrested in the (BF + RA(+C))nano. This behaviour is mainly attributed to the uniform distribution of film RA and needle BF with nano-level spacing in the (BF + RA)nano. The stress concentration energy at the crack tip can be absorbed by the martensitic transformation of the film RA. The results are important when designing a multiphase microstructure for a commercial high-strength steel.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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