Susceptibility of Adiabatic Shear Band Formation in AZ31B Magnesium Alloy during High Strain Rate Impact
Bibliographic record
Abstract
Abstract Adiabatic shear bands (ASBs) are known to be the dominant damage mechanisms in structural materials under high strain rate loading such as Magnesium (Mg) alloys. Therefore, to tailor the mechanical performance of Mg alloys for structural applications, there is a need to understand their susceptibility to strain localization and formation of ASBs, including the mechanism of crack initiation and propagation. In this study, as-fabricated (extruded) and heat-treated (annealed at 400oC) AZ31B Mg alloys were subjected to high strain rate loading using the direct impact hopkinson pressure bar (DIHPB) under different strain rates (834–2435 s− 1) at room temperature. The impact specimens failed through the occurrence of strain localization, formation of diffused ASBs and initiation/propagation of micro-cracks along the path of evolved ASBs. Thus, strain localization results in crack initiation and propagation despite the inherent brittle nature of the Mg alloys. Also, the presence of fractured second-phase particles dispersed within voids and along shear band path suggests particle fragmentation and refinement due to the strain localization. This also resulted in void nucleation, growth and coalescence at a later stage during the deformation. In addition, there seems to be a threshold strain rate ( ~ > 2225 s− 1) beyond which the specimen fractures regardless of the initial microstructure of the Mg alloys.
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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) | 0.002 | 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".