Experimental Characterization of Tool Wear Morphology and Cutting Force Profile in Dry and Wet Turning of Titanium Metal Matrix Composites (Ti-MMCs)
Bibliographic record
Abstract
Metal-matrix composites (MMCs) are made of non-metallic reinforcements in metal matrixes, which have excellent hardness, corrosion, and wear resistance. They are also lightweight and may pose a higher strength-to-weight ratio as compared to commercial titanium alloys. One of the MMCs with remarkable mechanical properties are titanium metal matrix composites (Ti-MMCs), which are considered a replacement for super-alloys in many industrial products and industries. Limited machining and machinability studies of Ti-MMCs were reported under different cutting and lubrication conditions. Tool wear morphology and life are among the main machinability attributes with limited attention. Therefore, this study presents the effects of cutting and lubrication conditions on wear morphology in carbide inserts when turning Ti-MMCs. To that end, maximum flank wear (VB) and cutting forces were recorded, and the wear morphologies within the initial period of the cut, as well as the worn condition, were studied under dry and wet conditions. Experimental results denoted that despite the lubrication mode used, abrasion, diffusion, and adhesion mechanisms were the main wear modes observed. Moreover, built-up layer (BUL) and built-up edge (BUE) were the main phenomena observed that increase the tendency of adhesion at higher cutting times.
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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".