The development of grain resolved stress fields around notch tips in soft-textured zirconium polycrystals: A three-dimensional synchrotron X-ray diffraction study
Bibliographic record
Abstract
Texture, microstructure, and local grain neighbourhood contribute to the development of localized stresses in polycrystals. For hexagonal close-packed materials, crystal's elastic and plastic anisotropy can also be a major contributing factor, yet there is a paucity of experimental studies focusing on the extent of contribution of such parameters on the magnitude of localized stresses at microscales. This study focuses on addressing this knowledge gap by deforming double-edge-notched soft-textured α-zirconium specimens in-situ, while measuring grain scale tensorial stresses using high energy synchrotron X-ray diffraction. The specimens were subjected to cyclic loads to study the evolution of stresses in the vicinity of both shallow and deep notches. The soft-texture of the specimens is such that there are no c-axes of grains aligned along the macroscopic loading direction thereby inhibiting deformation twinning. The “as-measured” microstructures and notch geometries were imported into a crystal plasticity finite element model for further analysis. Results show that despite the absence of c-axes of grains aligned along loading direction, the developed stresses were substantially influenced by crystallographic orientations. Stress drop was observed near the onset of plasticity with further loading and the orientation and position effects were highlighted. A plastic deformation mechanism was revealed where, upon specimen loading, the mechanical constraints enforced during grain-grain interactions led to hardening. Accordingly, a parameter was devised to quantify the grain level hardening arising from this mechanism. It was shown that grain-scale stress concentration factors vary significantly before the onset of plasticity, but they settle in the plastic zone and with the progression of cycles.
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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) | 0.000 | 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 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".