Influence of Machining Parameters on the Structural Performance of Finger-Joined Black Spruce
Bibliographic record
Abstract
In Eastern Canada, black spruce (Picea mariana (Mill.)B.S.P.) has recently been introduced in the finger-jointing industry.However, little information is available on some of the key manufacturing parameters that influence the finger-jointing process.Therefore, the main objective of this work was to evaluate the effect of wood machining parameters on the ultimate tensile strength (UTS) of finger-joined black spruce in order to optimize the performance of the product.Parameters investigated in this study were the chip-load and the cutting speed.A feather profile was selected with an isocyanate-based adhesive and an end-pressure of 3.43 MPa.A factorial analysis showed a statistically significant interaction between cutting speed and chip-load on the UTS.Within the range of values studied, the cutting speed was the most significant variable affecting finger-joined black spruce.The influence of chip-load on the tensile strength of finger-joints was lower, being apparent only at lower cutting speeds.Results indicated that suitable finger-jointing could be achieved within a range of 1676 m/min and 2932 m/min of cutting speeds with a chip-load between 0.64 mm and 1.14 mm.However, within this range the best result was obtained at 2932 m/min cutting speed and 0.64 mm chip-load.Scanning microscope image analysis of the damaged cells confirmed the effect of cutting speed on the finger-jointing process.In general, the depth of damage was more severe as the cutting speed increased.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.007 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".