Numerical Study of Variation of Mechanical Properties of a Binary Aluminum Alloy with Respect to Its Grain Shapes
Bibliographic record
Abstract
To study the variation of the mechanical behavior of binary aluminum copper alloys with respect to their microstructure, a numerical simulation of their granular structure was carried out. The microstructures are created by a repeated inclusion of some predefined basic grain shapes into a representative volume element until reaching a given volume percentage of the α-phase. Depending on the grain orientations, the coalescence of the grains can be performed. Different granular microstructures are created by using different basic grain shapes. Selecting a suitable set of basic grain shapes, the modeled microstructure exhibits a realistic aluminum alloy microstructure which can be adapted to a particular cooling condition. Our granular models are automatically converted to a finite element model. The effect of grain shapes and sizes on the variation of elastic modulus and plasticity of such a heterogeneous domain was investigated. Our results show that for a given α-phase fraction having different grain shapes and sizes, the elastic moduli and yield stresses are almost the same but the ultimate stress and elongation are more affected. Besides, we realized that the distribution of the θ phases inside the α phases is more important than the grain shape itself.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".