Tool wear and surface integrity during high-speed turning of hardened steel with polycrystalline cubic boron nitride tools
Why this work is in the frame
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Bibliographic record
Abstract
This paper examines the tool wear characteristics and surface integrity during high-speed turning of D2 tool steel. The effects of different process parameters, including tool wear and edge preparation, on the surface and subsurface damage were examined using a scanning electron microscope (SEM). Modes of tool wear were investigated under different cutting conditions. The X-ray diffraction technique was also employed to measure the residual stress distributions beneath the machined surface. Various forms of surface damage were observed under different cutting conditions. A wide range of residual stress distributions beneath the machined surface were obtained depending on the cutting conditions and edge preparation. The unfavourable tensile residual stresses were minimized at high cutting speeds and high depths of cut. This reveals the possibility of optimizing the cutting conditions for favourable residual stresses.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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