The micromechanics of fracture of zirconium hydrides
Bibliographic record
Abstract
Zirconium alloys are susceptible to hydrogen embrittlement and hydride precipitation. The precipitation of hydrides is accompanied by a transformation strain, but the contribution of this strain to the fracture of hydrides is not well-understood. In this study, deformation mechanisms and the micromechanics of fracture of hydrides are investigated by conducting in-situ and interrupted ex-situ tensile experiments on hydrided zirconium specimens. Electron backscatter diffraction (EBSD) is used to measure the macro-EBSD maps that contain the grains located in the gauge section of the specimens’ surfaces. Further, high spatial resolution EBSD is used to determine orientation variations induced by the precipitation of hydrides and by the external mechanical load. The measured grain orientations are mapped into a crystal plasticity finite element (CPFE) model to examine the performance of eight different crack initiation criteria. It is shown that a multiscale approach is essential for studying the fracture of hydrides as the details of hydride morphology, orientation, local grain neighborhood, and hydride-hydride interactions are important in such analysis. It is shown that neglecting the effects of hydride-induced transformation strain leads to inaccuracies in predicting both the location and direction of microcracks within hydrides. Among the examined methods, the combination of resolved shear stress and resolved shear strain on slip systems, i.e., the highest shear energy density, consistently predicts the correct locations of hydride microcracks as well as their propagation direction. Further, it is shown that the significant deformation that takes place within hydrides is the main driving force for the fracture of hydrides.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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".