Study of Martensitic Transformation in 304L Austenitic Stainless Steel after Tensile and Low Cycle Fatigue Tests
Bibliographic record
Abstract
There are many studies on austenitic stainless steels with transformation induced plasticity (TRIP). Basically, in these steels, there is a significant increase in strength and toughness with the transformation of austenite to martensite. 304L steel finds extensive application in industry. Studies relating to martensitic transformation with plastic deformation are quite common. Many studies involve monotonic loading relating to the martensite formed. In practice, 304L steels are subject to distinct types of loading and possibly with stress concentrators. Thus, also in smaller quantities, it is possible to find in the literature studies involving cyclic loading with the TRIP effect. To contribute to the literature on the analysis of the TRIP effect on these steels, 304L steel samples with stress concentrators underwent interrupted monotonic tensile tests. Optical microscopy (OM) and x-ray diffraction (XRD) technique characterized the martensitic transformation. Other 304L steel samples with a stress concentrator underwent a low cycle fatigue test. The martensitic transformation, in this case, was possible to follow with the electron backscatter diffraction technique (EBSD). The samples after the interrupted monotonic tests show a high martensite volume fraction formed 1mm away from the notch (30% to 50%), due to the plastic deformation suffered. From 5.5mm of the notch, the samples again display a microstructure like that of the as-received (AR) sample. For the low cycle fatigue tested sample, the high concentration of deformation-induced martensite was within 15mm of the discontinuity. Approximately 0.5mm from the circular discontinuity, the sample again has a microstructure like the initial sample (IS).
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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 | 0.003 | 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 | 0.001 |
| 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".