Characteristic Evolution of Residual Stress in Shape Memory Fe-Mn-Si-Cr Alloys
Bibliographic record
Abstract
Since the matrix phase is transformed to martensitic phase in shape memory alloys (SMAs) during plastic deformation, complicated residual stresses may arise during deformation, and they may affect the shape recovery ability of the alloys. Thus, it is important to be able to characterize the residual stresses formed in SMAs during plastic deformation and annealing. In this study, X-ray diffraction was used to characterize the residual stress formed in a Fe-Mn-Si-Cr SMA, which was deformed in the tensile direction and subsequently annealed. The results showed that the compressive stress persisted in the tensile direction of the face-centered cubic (fcc) matrix upon tensile deformation and unloading. Compressive stress is believed to result from the hexagonal close-packed (hcp) phase formed during stress-induced martensitic transformation. After the deformed samples were annealed to recover their shapes, the residual stress was considerably reduced. This is believed to be due to the decrease in the formation of the hcp phase or to the recovery of their shapes during annealing. Our results indicated that residual stress in the fcc matrix phase is associated with the shape recovery characteristics of the alloys after martensitic and reverse martensitic transformations.
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 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) | 0.001 | 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".