Scripts to Insert Cohesive Elements at the Interfaces between Matrix and Precipitates with Irregular Shapes in Representative Volume Elements in ABAQUS
Bibliographic record
Abstract
A MATLAB algorithm was developed to insert cohesive elements at the interfaces between the matrix and precipitates in two dimensional (2D) representative volume elements (RVEs) of metals. The RVEs were created using OOF2 and imported into the “Complete ABAQUS Environment” (CAE) interface. These RVEs are based on actual images of the metal at the microscale, where the precipitates have irregular shapes. The RVEs contain precipitates that are dispersed into matrix materials. Commercial finite element (FE) ABAQUS software does not provide the option to automatically generate cohesive elements at the interfaces. The presented algorithm enables the insertion of cohesive elements at the interfaces between the matrix and precipitate in a convenient manner. This algorithm enables the simulation of the fracture process, including initiation at the interfaces and propagation at microscale, for metals that contain precipitates and/or particles. This algorithm extends the simulation capabilities of the FE solver ABAQUS.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.074 | 0.020 |
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".