Role of Li and Sc Additions and Machining Conditions on Cutting Forces on Milling Behavior of A7075-Based Alloys
Bibliographic record
Abstract
The present study focuses on the dry and wet end milling of three distinct Aluminum 7075 alloys: A7075, A7075–Sc (with a 0.18% Sc addition), and A7075–Li–Sc (containing 2.2% Li and 0.18% Sc additions). The main objective is to explore how cutting parameters (cutting speed and feed rate), heat treatment, alloy composition, and cooling methods influence A lcutting force. In the initial phase of the investigation, all three alloys underwent heat treatment. Subsequently, the machining process centered on the softest and hardest conditions, aiming at analyzing the impact of hardness on machinability behavior of the three studied alloys, using the same milling tool and a consistent depth of cut under both dry and wet conditions. The investigations also highlight the role of Li and Sc additions on the quality of surface finish, as well as burr and chip formation. In total, a sum of 108 operations have been performed on the present alloys.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".