Prediction of Friction Stir Processed AZ31 Magnesium Alloy Micro-Hardness Using Artificial Neural Networks
Why this work is in the frame
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Bibliographic record
Abstract
Friction stir processing (FSP) is a microstructural modification technique. In FSP, the material undergoes intense plastic deformation, yielding a dynamically recrystallized fine grain structure. One of the most important issues that need to be tackled in this field is the lack of predictive tools. That enables the selection of the optimum parameters required to achieve the desired modifications on the mechanical properties of the processed materials. In this study, the effects of different FSP parameters (rotational and translational speeds) on the resulting micro-hardness of friction stir processed AZ31 magnesium sheets are examined. Variations of micro-hardness with longitudinal and through-thickness positions are also investigated. Artificial neural networks (ANNs) are used to model and predict the resulting micro-hardness.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it