Cutting forces and noise in helical planing black spruce wood as affected by the helix angle and feed per knife
Bibliographic record
Abstract
A conventional straight knife cutterhead and three helical knife cutterheads were tested for planing black spruce wood (Picea mariana (Mill.) B.S.P.). Effects of helix angle and feed per knife (FK) on maximum cutting forces and sound level were evaluated. A 3-axis dynamometer and an array microphone were used to simultaneously record the forces and the sound level, respectively. Parallel (FP), lateral (FL), resultant (FR) forces, and sound level increased as FK increased. Helical tools produced lower FP, positive and negative normal forces (FNP and FNN), and FR. Parallel forces tended to decrease as helix angle increased at high FK (4.7 mm). Differences among helical tools were not significant for normal and resultant forces. Cutterheads with the two highest helix angles (50° and 60°) produced higher FL at low (1.3 mm) feed per knife. Impacts of these cutting forces on the production of surface defects and ways to reduce them were discussed. Helical cutterheads considerably generated lower sound pressure level, with a maximum difference of up to 11.5 dB(A).
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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 | 0.000 | 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) | 0.001 | 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".