On the role of stress state in the failure behavior of alumina ceramics via stereolithography: Quasi-static and dynamic loading
Bibliographic record
Abstract
The current research examines the failure response and mechanical performance of additively manufactured (AM) alumina ( Al 2 O 3 ) ceramics subjected to varying rates of strain and stress states. Using stereolithography (SLA), samples were produced in three orientations and tested under combined shear-compression and indirect tension loading. To monitor the failure progression and analyze full-field strain components, the testing was recorded using a high-speed camera and examined through the digital image correlation (DIC) technique. The findings indicated that when the printing orientation (PO) is aligned perpendicular to the loading direction, the material exhibits greater strength in both stress states. This is likely attributable to the sequential layer printing process and how the corresponding processing-induced microstructural defects contribute to the damage propagation. Additionally, the results demonstrated that peak stress decreases as shear strain increases, attributed to earlier damage initiation. The examination of fracture surfaces indicated that intergranular failure dominated under quasi-static loading, whereas dynamic loading exhibited a mix of intergranular and transgranular fracture modes. This study comprehensively informs on the failure performance of AM Al 2 O 3 ceramics across various stress conditions and strain rates, which is rarely investigated in the literature, offering insights for modeling and designing AM ceramic structures with tailored mechanical properties.
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 | 0.001 |
| 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".